High Technology, Productivity and Networks: A Systemic Approach to SME Development

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Author: Mario Davide Parrilli | Roger Sugden | Patrizio Bianchi

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High Technology, Productivity and Networks A Systemic Approach to SME Development

Edited by

Mario Davide Parrilli, Patrizio Bianchi and Roger Sugden

High Technology, Productivity and Networks

Also by Mario Davide Parrilli SME CLUSTER DEVELOPMENT A Dynamic View of Survival Clusters in Developing Countries

High Technology, Productivity and Networks A Systemic Approach to SME Development Edited by Mario Davide Parrilli Patrizio Bianchi and Roger Sugden

This publication is co-funded by the European Union The views expressed in this publication do not necessarily reflect the views of the European Commission.

Selection and editorial matter © Mario Davide Parrilli, Patrizio Bianchi and Roger Sugden 2008 Individual chapters © Contributors 2008 All rights reserved. No reproduction, copy or transmission of this publication may be made without written permission. No paragraph of this publication may be reproduced, copied or transmitted save with written permission or in accordance with the provisions of the Copyright, Designs and Patents Act 1988, or under the terms of any licence permitting limited copying issued by the Copyright Licensing Agency, 90 Tottenham Court Road, London W1T 4LP. Any person who does any unauthorized act in relation to this publication may be liable to criminal prosecution and civil claims for damages. The authors have asserted their rights to be identified as the authors of this work in accordance with the Copyright, Designs and Patents Act 1988. First published 2008 by PALGRAVE MACMILLAN Houndmills, Basingstoke, Hampshire RG21 6XS and 175 Fifth Avenue, New York, N.Y. 10010 Companies and representatives throughout the world PALGRAVE MACMILLAN is the global academic imprint of the Palgrave Macmillan division of St. Martin’s Press, LLC and of Palgrave Macmillan Ltd. Macmillan®is a registered trademark in the United States, United Kingdom and other countries. Palgrave is a registered trademark in the European Union and other countries. ISBN-13: 978−0−230−55353−8 ISBN-10: 0−230−55353−2

hardback hardback

This book is printed on paper suitable for recycling and made from fully managed and sustained forest sources. Logging, pulping and manufacturing processes are expected to conform to the environmental regulations of the country of origin. A catalogue record for this book is available from the British Library. Library of Congress Cataloging-in-Publication Data High technology, productivity and networks : a systemic approach to SME development / edited by Mario Davide Parrilli, Patrizio Bianchi and Roger Sugden. p. cm. Includes bibliographical references and index. ISBN 0 230 55353 2 (alk. paper) 1. Small business Growth. 2. Small business Technological innovations. 3. Industrial productivity. 4. Business networks. I. Parrilli, Mario Davide. II. Bianchi, Patrizio, 1952 . III. Sugden, Roger HD62.7.H538 2008 658.5’1 dc22 2007052973 10 9 8 7 6 5 4 3 2 1 17 16 15 14 13 12 11 10 09 08 Printed and bound in Great Britain by CPI Antony Rowe, Chippenham and Eastbourne

Contents List of Tables

vii

List of Figures

ix

List of Contributors

xi

Foreword

Part 1 1

3

4

6 7

3

Hi-tech Promotion

The Regional Innovation System in Emilia-Romagna Laura Ramaciotti

35

Small and Medium-Sized Firms in High-Technology Industries: The Experience of Biotechnology Firms in the United States Stuart O. Schweitzer and Marco R. Di Tommaso

57

The Start-up Process of Knowledge-based Companies in Latin America Hugo Kantis and Pablo Angelelli

71

Part 3 5

Introduction

Hi-tech Development, Productivity Increases and Networking: A Systemic Approach to the Development of Small and Medium Enterprises Mario Davide Parrilli

Part 2 2

xiii

Productivity Increases

Business Support Services: A Conceptual Framework and Some Interesting Practices Nicola Bellini

95

Entrepreneurship, Small Firms and Self-employment David Audretsch, Maria Callejon and Mari Jose Aranguren

117

Competitiveness Based on Low Production Costs or on High Specialization and Productivity: The Case of SMEs in Costa Rica Justo Aguilar and Maikol Elizondo

138

v

vi

Contents

Part 4 8 9

10

11

Trust and Social Capital in Glo-cal Networks Lisa De Propris

155

Local and Global Linkages of Small and Medium Enterprises in Local Production Systems in Brazil Wilson Suzigan, Renato Garcia and João Furtado

175

Industrial Cluster Trajectories and Opportunities for Endogenous Upgrading in Developing Countries Peter Knorringa

193

A Sectoral Approach to Policies for Clusters and Value Chains in Latin America Carlo Pietrobelli and Roberta Rabellotti

209

Part 5 12

Networking

Conclusions

Conclusions Patrizio Bianchi

233

Notes

240

Index

247

List of Tables List of Tables 1.1 1.2 2.1

Correlation with SME performance Actions implemented from May 1997 to the end of 1999 Small and medium-sized industries’ distribution in Emilia-Romagna based on relationships with other firms, 1999/2000 2.2 GDP formation per sector 2.3 Number of active firms in Emilia-Romagna and value added 2.4 Personnel and cost of intra-mural R&D. Italian regions in 2001 2.5 Lecturers and researchers per subject area in Emilia-Romagna, 2000 2.6 In Emilia-Romagna 80 applications were presented in these sectors 2.7 Mixes between the research network and the production network 4.1 Level of education of entrepreneurs by sector (%) 4.2 Previous work of entrepreneurs by sector (%) 4.3 Motivations to create new firms by sector (%) 4.4 Context for job and skills acquisition by sector (%) 4.5 Composition of networks that helped to identify ideas by sector (%) 4.6 Previous evaluations of firm creation by sector (%) 4.7 Networks and access to resources by sector (%) 4.8 Sources of finance by sector (%) 4.9 Client companies’ profile by sector (%) 4.10 Main problems in the first years by sector (%) 4.11 Sources of support by sector (%) 5.1 Strengths and weaknesses of business support services providers 5.2 The evaluation framework 6.1 Net entry (with 0 employees) 6.2 Net entry (with 0 employees) 6.3 Net entry (with 1–2 or more employees) 7.1 Number of interviewed enterprises (SME) 7.2 Number of interviewed enterprises by size 7.3 Discrimination measures and eigenvalues vii

10 16

39 39 41 43 47 47 50 74 75 76 78 79 81 82 83 85 87 87 104 107 132 133 133 145 145 147

viii

7.4 9.1 11.1 11.2 11.3 11.4 11.5 11.6

List of Tables

SMEs organized by deciles according to the technology and qualifications combined index (QUAL-TEC) Typology of production systems Basic characteristics of the Latin American clusters in this study Index of collective efficiency: average External economies and joint actions (averages) Upgrading (averages) A menu of actions to support cluster development A sectoral approach to policy design

148 177 213 215 216 216 221 223

List of Figures List of Figures 1.1 2.1 2.2 2.3 4.1 4.2 4.3 5.1 5.2 6.1 6.2 6.3 6.4 6.5 8.1 9.1 9.2

A tripartite framework for SME development Company ideas Technological transfer projects Technological transfer projects Analytical framework Evolution of firms’ average annual sales by sector Evolution of firms’ average number of jobs by sector CATAS as a network node The customer portfolio of CATAS Demographic rates 1994–2000. Breakdown by size class Rate of surviving firms according to size class Net entry rates Evolution: number of new firms Evolution: number of exiting firms Network capital Global commodity chain in the international footwear market Domestic commodity chain in the footwear industry

ix

18 53 53 54 72 73 74 100 112 130 130 131 131 132 171 185 186

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List of Contributors Justo Aguilar, Full Professor and Director of the Institute for Research in Economic Sciences, University of Costa Rica, San Jose. Pablo Angelelli, Expert in the division on Small and Medium Enterprises, Inter-American Development Bank, Washington. Mari Jose Aranguren, Director of the Department of Economics, University of Deusto and Orkestra Institute of Competitiveness and Development, San Sebastian. David Audretsch, Full Professor, University of Indiana and Director of Entrepreneurship, Growth and Public Policy, Max Planck Institute of Economics, Jena. Nicola Bellini, Full Professor, University School Sant’Anna, Pisa. Patrizio Bianchi, Rector and Full Professor, University of Ferrara. Maria Callejon, Full Professor, University of Barcelona, and Director of SME Policies, Ministry of Industry, Tourism and Trade, Spain. Lisa De Propris, Senior Lecturer, Institute for Economic Development Policy, University of Birmingham. Marco Di Tommaso, Associate Professor, Faculty of Economics, University of Ferrara. Maikol Elizondo, Research assistant and PhD student, Institute for Research in Economic Sciences, University of Costa Rica. João Furtado, Lecturer, Polytechnic School, University of Sao Paulo. Renato Garcia, Lecturer, Polytechnic School, University of Sao Paulo. Hugo Kantis, Full Professor, University of General Sarmiento, Buenos Aires. Peter Knorringa, Associate Professor, Institute of Social Studies, The Hague. xi

xii

List of Contributors

Mario Davide Parrilli, Coordinator of the ‘Latin American Graduate School in Industrial Development and SME Policy’, Institute for Economic Development Policy, University of Birmingham. Carlo Pietrobelli, Full Professor, University of Rome Three, Rome. Roberta Rabellotti, Associate Professor, University of Eastern Piedmont, Novara. Laura Ramaciotti, Lecturer in Applied Economics, University of Ferrara. Stuart Schweitzer, Full Professor, University of California, Los Angeles. Roger Sugden, Full Professor and Director of the Institute for Economic Development Policy, University of Birmingham. Wilson Suzigan, Full Professor, University of Campinas.

Foreword This book represents the search for a systemic approach to the development of small and medium enterprises (SMEs) in developing areas; this approach is thought to contribute a novel recognition of the key role that these socio-economic actors play in the development of their own local and national economies where they represent very large proportions of production and employment. This approach is also deemed to systematize the learning process that SMEs, national and international institutions, experts, business associations and, in particular, the firms and their entrepreneurs and workers, have accumulated on the basis of successful international experiences and day-to-day competitive struggles occurring in local and global markets. This volume focuses on a wide variety of production systems in both industrialized and developing economies; however, it has in mind to generate and share knowledge that may be particularly helpful in the context of developing economies. In fact, within these systems a poor contribution of SMEs to the process of national and local development is frequently observed; large firms are often the only firms that are able to join international markets and to absorb and produce processes of knowledge and technology generation as well as to produce higher value added for the national economy. The variety of industry and country experiences presented in this book are to be seen within a tripartite framework for the analysis of industrial development; a framework that tries to respond to the need implicitly raised by the different types of small and medium firms operating in global markets; overall, the three proposed development drivers are to be viewed as complementary and mutually reinforcing within the development of local and national production systems. The first driver emphasizes the importance to promote high-tech industries and SMEs; this strategy expresses the prospect of pushing forward the production technology frontier that adds new knowledge and higher value added to the local system; the second line stresses the importance to increase the productivity of traditional enterprises that work for standard consumption in local markets and that also needs to respond to the demand for more, better and cheaper goods and services for all segments of consumers; the third strategic driver specifies that a global coordinated approach is needed to pull together the work realized in the previous two strategic lines and with the previous two types of firms, on the one xiii

xiv Foreword

hand the modern large, medium and few small firms and, on the other, the traditional sector of mainly micro, small and some medium-sized enterprises. This integrated approach may produce a thorough development process that is more likely than standard trickle-down models (large firms-led strategies, e.g. FDI) to present the ‘human face’ of an inclusive and healthy development, where all persons and firms are actively and democratically involved. The strengths of this publication are mainly two: the first is the richness of knowledge and of international experiences that are contributed by this group of experts and that confirm the relevance of each of the aforementioned lines of industrial development. The second asset is represented by the joint effort of a large number of academics and experts from several universities and institutions of different countries, including Brazil, Italy, Argentina, Holland, the UK, Costa Rica, Spain and the US as well as from other countries and institutions that were involved in previous steps of the joint effort and project (e.g. France, Chile, Mexico, Nicaragua, Haiti, El Salvador, Canada, Peru, Bolivia, Colombia and Guatemala) such as the EU–ALFA project (2004–7) ‘European-Latin American Network for Research and Learning in Industrial Development Policy’ and the ‘Latin American Graduate Summer School in Industrial Development and SME Policies’ – organized itinerantly in Latin America – on which bases a previous publication on SME Development Policy (in Spanish: Mexico, 2005) set the bases for the current academic effort. This is an innovative effort in which research and development capabilities of participants have closely coordinated in expressing a common development aim for SME-based economies in developing economies. The editors would like to express special thanks to the authors of this volume and to L’Institute and DARE communities with whom this research project has been developed, as well as to the European Union, ALFA Programme, that financed a round of key summer schools in Latin America and in Europe where these topics have been analysed and thoroughly discussed, and where the next steps of academic cooperation have been identified and promoted. Paris and Mexico May 2007 MDP

Part 1 Introduction


1 Hi-tech Development, Productivity Increases and Networking: A Systemic Approach to the Development of Small and Medium Enterprises Mario Davide Parrilli

1. Small and medium enterprises in the global context The current context of market globalization has been significantly changing the economic reality in all countries. Technological progress in telecommunications and infrastructures in general, and the strict adoption of the liberalization doctrine within the framework of the World Trade Organization, has promoted the entry of a large number of new competitors within national and local markets, including developing countries. Economic analysis needs to incorporate these changes and to propose models and strategies to be modulated according to each specific context (e.g. developing countries, economies in transition, industrialized countries). The first 60 years of the twentieth century represented the era of large Fordist companies, which were based upon productive structures that guaranteed important scale economies and the related cost reduction. During the 1960s and 1970s these firms fell into deep crisis, due to their productive and organizational rigidities, and lost significant market shares in many sectors. In this phase, small and medium enterprises (SMEs) were extremely successful, in particular within industrial districts and clusters, which were able to promote their production and export capacity (Piore and Sabel, 1984). By the end of the 1980s, most large companies were able to modernize and exert a pressure on SMEs operating in international markets. As a consequence, SME stability has been jeopardized in both economic terms (e.g. income and employment) and social terms (e.g. social cohesion and entrepreneurial spirit). 3

4 High Technology, Productivity and Networks

These big changes do not impede SMEs from maintaining a very relevant position in all continents and countries; in Latin America (Peres and Stumpo, 2002), Asia (CFR, 1998) and Europe (European Observatory for SMEs, 2003) they represent more than 90 percent of the total number of firms, 40–70 percent of employment and 30–60 percent of GDP (Bianchi et al., 2006). SMEs are important not only in economic terms, but also in political and social terms. When SMEs take an important role in production, the democratization of economic and social life is more likely to progress. This occurs for two main reasons: 1) a large number of people assume economic responsibilities and value more their own skills and capabilities, which constitute key elements in a dynamic society (Cooke and Wills, 1999; Becattini, 2000; Parrilli, 2004a); 2) an economic system that is based on several dynamic SMEs can help individuals and their social and family nuclei to structure systemic networks of interaction among firms and between firms and other institutional actors. This organizational form (network) promotes social cohesion, which helps to spur local economic development by means of joint actions (Becattini, 1990; Putnam, 1993; Platteau, 1994; Schmitz, 1995; Cowling and Sugden, 1999; Bianchi, 2000; Parrilli, 2004a). However, these potentials remain hypothetical, at least until the competitive role and the prospective impact of SMEs in their own countries are clarified. These doubts assume a special importance in developing economies, due to the technological disadvantage and the competitive gap these countries and their enterprises face vis-à-vis foreign/multinational companies in open markets. This situation motivates us to study the capacity and characteristics of production systems in which an effort is required to shift from a ‘low-road’ to a ‘high-road’ type of competition and development. This means passing from a kind of competition based upon the reduction of costs and on conflictive relations among entrepreneurs, workers, supplier and clients, to a kind of competition that is based upon innovation and cooperative actions that represent the new routes to growth at the international level (Pyke and Sengenberger, 1992; Kaplinsky and Readman, 2001). In this sense we intend to analyse the development process of SMEs and to emphasize the strategic approach that, in our opinion, can strengthen their competitive position. In this respect, three aspects can be signaled: hi-tech development, productivity increase in traditional enterprises, strengthening of linkages and networks (Bianchi et al., 2000; Bianchi and Parrilli, 2002; Parrilli, 2004b). As a way to develop this argument, we deem it appropriate to adopt a comparative analysis. For this reason we analyse

Mario Davide Parrilli

5

a few international experiences, mainly the experience of some European and American countries and regions that display the impressive growth of SMEs and their economies. For this purpose in this academic project we have benefited from the richness of the joint effort of a network of experts, international institutions and universities that spurred deep reflection on development strategies for those local production systems that are densely populated by small and medium-sized firms.

2. Different approaches to SME development Before developing the proposed systemic approach, we regard it as important to discuss the approaches that are being adopted by the main international organizations that promote SME development in developing countries; for practical reasons we may focus in particular on Latin America. In this section the neoclassical/neoliberal approach is discussed on the basis of the World Bank view and operations. The neostructural approach adopted by the Economic Commission for Latin America and the Caribbean (ECLAC), and the transition approach taken by Inter-American Development Bank, are also presented and discussed. 2.1 The neoclassical/neoliberal approach With the foreign debt crisis at the beginning of the 1980s, the development policy paradigm transformed notably. The main international organizations, such as the World Bank and the International Monetary Fund, called for the closure of import substitution industrialization policies (ISI), which were considered a failure because of the large inefficiencies and the widespread phenomenon of corruption connected to them (Singh, 1992; World Bank, 1993). As a consequence, these organizations promoted a significant change in the policy approach towards a neoclassical/neoliberal model based upon macroeconomic stabilization, market liberalization and efficiency as well as on the adoption of a production scheme endorsing the concept of comparative advantages (Krueger, 1983; World Bank, 2002). This approach was deemed useful to promote the development of SMEs by creating conditions in which these could prosper. Within this view the main conditions were the elimination of policies oriented to the promotion of large firms (i.e. the so-called ‘national champions’) that were extensively implemented in both collectivist regimes and western economies throughout the second half of the twentieth century (Bianchi, 1998). The second refers to the adoption of the Heckscher–Ohlin (H–O) comparative advantage trade model.


This development strategy focuses on generating the most efficient allocation of economic resources (e.g. land, capital and labor) as a means to generate the highest possible welfare for the population. If import substitution industrialization supports large firms mainly, the neoclassical/neoliberal approach, by refraining from public intervention, generates the important effect of equalizing the condition of small and large firms. Eliminating these measures (e.g. direct subsidies to export; protection of specific internal markets) is likely to produce an improvement in the competitive position of SMEs within the national economy (Krueger, 1983; Balassa et al. 1986).1 With reference to the second condition, liberalization policies are supposed to promote the adoption of the neoclassical model of comparative advantages. This logic should induce many developing countries to specialize in productions linked to their natural endowment. For example, in Latin America some countries would invest in the factor ‘land’ (e.g. Argentina, Chile, Bolivia, Paraguay, etc.) and others in ‘labor’ (e.g. El Salvador, Guatemala, Brazilian Coast, Central Mexico, etc.). Since SMEs are actually oriented to traditional agriculture and basic processing activities as well as to labor-intensive manufacturing, their enterprises would benefit from increases in efficiency and labor productivity due to the application of these neoclassical policies.2 Within this perspective industrial policies constitute a distorting factor because they tend to allocate resources to sectors that present a relatively poor natural endowment. This is what happened with ISI policies that hindered the free flow of market forces and led to an inefficient allocation of production inputs, with the consequent reduction in public welfare (Krueger, 1983). Complementary to increasing economic efficiency, the elimination of industrial policies leads to reducing the decision-making power in the hands of monopolies and oligopolies and to favor a more competitive market, which also benefits consumers in terms of higher volumes and cheaper prices of goods and services. Similarly, it is easier to control the phenomenon of corruption that can take place between the private sector and public institutions and that represents a side effect of import substitution policies. For these reasons this approach prefers to depend upon stabilization policies as bases to start a steady development process within these countries and among their actors (e.g. the SMEs). Analysing the support to this economic and social sector, the Department for SMEs of the World Bank3 assumed the basic principle of the ‘market economy’, for which the state should focus only on maintaining a competitive environment, correcting market failures and supplying


7

public goods; in contrast, it does not have to focus on delivering private goods that the market can supply more efficiently (World Bank, 1993; 2002). Within this approach most firms supply private goods and services; thus they should find their optimal development through the (free) market. With reference to the provision of business development services to small firms as a way to promote their growth, the Bank affirms that ‘with the appropriate design, distribution and payment mechanisms these services can be supplied at adequate prices even to the poorest segments in the SME sector’ (World Bank, 2002: 27). These reasons explain why there is no need to define state policies for the development of SMEs. Overall, the neoclassical/neoliberal approach is interesting in particular for its objective of maintaining a balance between large and small firms in order to avoid the existence of disproportionate advantages or discriminatory policies and benefits which may favor one specific sector over the other. However, this approach does not clarify some doubts that arise with the observation of the process of development in Latin America and in other developing economies in the past 20 years of market liberalization. For instance, it is not clear why the rate of under-employment and the informal economy have been booming over this period (the first is currently estimated at around 50 percent of the economically active population in most of the less developed countries). It seems that, instead of benefiting from the neoliberal and neoclassical policies applied over these years, SMEs have suffered a competitive setback (Portes et al., 1989; Tokman, 1992; Speer, 1997). The answer to this situation by the World Bank is to intervene in the market through actions that target small groups of SMEs. In some cases, it refers to the most competitive firms (the medium-sized firms), but in general refers to the smallest enterprises that show the least competitive capacities (i.e. rural subsistence micro enterprises). In both cases the World Bank risks adopting a reductive approach: on the one hand by focusing its support only on a few leading medium-sized firms; on the other, by becoming ‘aid-led’4 through a strategy of helping mainly subsistence microfirms (World Bank, 2002). Although this approach can respond to real needs of poor sectors of the population in developing economies, it does not seem to constitute a systemic type of answer for the growth of these economies and of their SMEs. 2.2 A neostructuralist approach In the past 50 years, the history of economic policy in Latin America has been very much linked to the Structuralist school of thought, which supported the development process of the region through the


import substitution paradigm. After the crisis of foreign debt (1982) and the application of the structural adjustment programs, the Structuralist school had to rethink its theoretical approach. This gave origin to the Neostructuralist approach (Fajnzylber, 1988; Sunkel, 1990; Esser et al., 1994; Ocampo, 2001). For decades, the Economic Commission for Latin America and the Caribbean (ECLAC) of the United Nations maintained a clear leadership in the theoretical formulation and in the technical assistance to the region’s governments. Its neostructuralist approach displays substantial divergences with respect to the neoclassical/neoliberal approach. These differences are based upon the neostructuralist recognition of the market incapacity to auto-regulate and to automatically produce the best possible welfare for the system as a whole. The most evident causes for this incapacity are related to the size of enterprises and to market failures (Peres and Stumpo, 2002).5 Within this logic, the SMEs do not have the same competitive capacities of large firms; this is due to scale and scope economies that lead them to face high per unit costs of production and commercialization (ibid.).6 For this reason, they tend to underinvest in various key areas of entrepreneurial initiative in this era of globalization and that constitute competitive advantages for the new flexible large companies (e.g. activities that generate knowledge and innovation, marketing and publicity, as well as those linked to the flow of information and communications within and outside the firm). All these strengthen the gap produced by market asymmetries among agents of different size and market power.7 The analysis of market failures shows that SMEs find it more difficult to acquire instruments that spur their competitiveness in global markets (ibid.). For example, financial institutions located in developing countries would meet high costs to collect information on SMEs in rural areas (prospective clients) and would face high risks on investments; for this reason, they prefer renouncing to serve this potentially important productive sector.8 In this way, these financial institutions leave a large number of actors with little possibility to access credit and to invest in better techniques of production. This situation represents a market failure, where thousands of SMEs remain without a service that they demand and that they could pay for, but for which no suppliers are currently available. In this case demand is not capable of catalysing supply and the two schedules meet at a sub-optimal short-run equilibrium. On these bases ECLAC experts analysed the past 20 years of market liberalization and tried to verify whether the structural reforms generated


9

welfare or not among SMEs in Latin America. Their extensive research on the SME universe and performance based upon 14 country studies verified that, in the recent process of market liberalization, these firms are neither ‘losers’ nor ‘winners’ (Peres and Stumpo, 2002). In this sense, their development seems to represent well the ambivalent economic evolution in Latin America, which simultaneously presents cases of growth and others of stagnation. SMEs increased their labor productivity and, in some cases (in Brazil and Costa Rica), even reduced their labor productivity gap with respect to large companies. This led to big increases in competitiveness and, as an effect, to increases in sales. However, this outcome comes also in response to an important strategy that is typically implemented by large firms, but that in Latin America has also been practiced by SMEs. This is the process of substitution of capital for labor, for which SMEs tried to increase productivity and efficiency on the basis of a substantial technological effort (e.g. purchase of modern equipment and machinery) which led to dismissal of part of the workforce (Parrilli, 2004b, 2007). Complementarily, the informal economy became a widespread phenomenon, which explains what happened to the many workers laid off by large companies and formal SMEs. In the past 20 years the number of self-employed, cottage workers and family enterprises has been increasing on a large scale.9 These enterprises represent a low-productivity economic group that generate low value added; these firms are usually localized in traditional sectors (e.g. constructions, street retail trade, personal services), through which less favored segments of the population (e.g. women and young people) as well as unemployed people search for employment and income opportunities. Through the above-mentioned study on 14 Latin American countries, ECLAC economists analysed the factors that had an impact on SME performance over the past 20 years. In this sense, they proposed four hypothetical factors: advances in liberalization, relevant weight of capital goods in SME production, macroeconomic management and implementation of active SME promotion policies (see Table 1.1). From this analysis a positive correlation between the first factor (liberalization) and SME performance is not proved, because this did not improve in various cases despite the increasing market liberalization (e.g. Chile and Mexico in the 1990s in positive, Chile in the 1980s, Uruguay and Venezuela in the 1990s in negative). With respect to the fourth determinant (SME policies), the authors verify the extreme weakness of industrial and SME policies in every country of the region (Peres and Stumpo, 2000; Dussel Peters, 2003). This consideration is based on the poor financial support given by governments to SMEs over the selected

10

Table 1.1 Correlation with SME performance

Argentina 1984–94 Chile 1990–96 Chile 1981–90 Mexico 1988–93 Colombia 1991–96 Cost a Rica 1990–96 Ecuador 1991–96 Peru 1992–94 Brasil 1985–97 Uruguay 1988–95 Venezuela 1990–95

Output: SME performance

Determinant I: Increase in liberalization

Determinant II: Weight of industrial SME

Determinant III: Macroeconomic conditions

Determinant IV: SME policies

++ ++ −− ++ + + + + + − −−

Large None Small Small Large Large Large Large Large Small Small

Significant Non significant Non significant Significant Non significant Non significant Non significant Non significant Significant Non significant Non significant

+ ++ − + + + + + + + −−

Non significant Non significant Non significant Non significant Non significant Non significant Non significant Non significant Non significant Non significant Non significant

Source: Based upon Peres and Stumpo, 2002: 31.


11

period. Moreover, the few public policies and programs focused only on limited groups of SMEs, without responding to the need of the wider number of SMEs (Parrilli, 2004b). In addition, the recipients (firms) were (and are) often micro enterprises that do not represent firms with the highest potential to create imitation and trickle-down effects on the rest of the production system. This may also explain the limited effect of public resources and policies on SME performance (IADB, 2003; World Bank, 2002). With respect to the second factor of analysis (strength of equipment and machinery production among SMEs), Peres and Stumpo verify that a significant SME production of capital goods exists in Brazil, Argentina and Mexico. But considering the statistics, a positive correlation cannot be found between this strength and SME performance. In fact, SME performance is positive in countries that do not have a strong SME industrial sector (e.g. Colombia, Ecuador, Peru, etc.) and negative in countries that are thought to have a more solid industrial structure (e.g. Argentina in the second half of the 1990s). In contrast, these scholars find a highly significant correlation between SME performance and the fourth factor (macroeconomic management). Stability of prices (inflation) and the national economic growth are related positively to SME performance. This result is explained with the structural orientation of SMEs towards the internal market, since operating in a stable macroeconomic environment that presents moderate inflation and an expansionary national economy permits the SMEs to assume more risks, to invest more resources to widen the scope of their initiatives, and to grow. Despite the impressive and exhaustive capacity of this research, some doubts remain. From a theoretical point of view, this study seems to confirm the neoclassical/neoliberal approach and weaken the neostructuralist hypotheses. In fact, the industrial structure and the policy support do not seem to determine the SME performance; in contrast, the sound management of the main macroeconomic variables results in the most relevant factor, which was the main strategy of the World Bank’s ‘structural adjustment programs’. On the other hand, the factor ‘economic growth’ can also be thought of as connected to the large number and weight of SMEs within the Latin American economies, which implies an almost necessary correlation between economic growth and SME performance, which would limit the sense of the correlation. This consideration motivates the classic question about which comes first (the ‘egg or the chicken’): is it economic growth and price stability that spur good SME performance or is it the latter that generates the former?

12


2.3 Features of a new approach in Latin America One of the most relevant development organizations in Latin America is the Inter-American Development Bank. It is a multilateral financial organization in which all Latin American countries are represented and the main industrialized countries with special linkages to the region, such as the United States, Italy, Spain, Great Britain among others. The first group of countries represents the beneficiary group of IADB, whereas the latter group represents the main financial supporters. Among the main structures of this organization, the International Investment Corporation (IIC) is dedicated to financing SME projects. This is an organization that manages significant funds (IADB, 2003).10 The majority of the projects implemented by the IIC for SMEs tend to focus on individual cases of successful firms (e.g. medium-sized firms) that are capable of presenting coherent projects with reference to strategic design, financial investment and that are capable of achieving significant profits in the short to medium term.11 In this sense, the IADB shows a strong preference for a market economy and sound financial management of projects. In the case of SMEs the IADB adopts a different scheme from the World Bank that tends to support mainly (groups of ) less dynamic enterprises; in contrast, the Inter-American Development Bank finances mainly medium-sized competitive firms. On the whole, this approach presents a structural constraint: the success achieved through the support of IIC to specific cases of competitive enterprise does not imply that particular efforts are implemented to favor an effective transfer of lessons and spillovers to the whole of the local and national production system. The idea of a development process generated through trickle-down effects from a few successful cases was never demonstrated (Perroux, 1950; Hirschman, 1958) as it is shown also more recently by the analysis of FDI and operations of transnational companies in both industrialized and developing economies (Dunning, 1988; Cowling and Sugden, 1994). In contrast, the variety of situations and competitive conditions of firms (in Latin America and, more in general, in developing countries) and the lack of mechanisms to transfer the best practices to local and national production system can make this process more difficult. Despite these difficulties, the recent realization of researches financed and carried out by the IADB on this topic permits us to identify the growing attention of this organization towards the dynamics of clustering and of global value chains (Pietrobelli and Rabellotti, 2004). These methodologies of research and development emphasize the force of a critical mass of small enterprises and of interconnected systems of production


13

and distribution; these aspects are a step beyond the idea that development can be produced automatically on the basis of a few individual cases of enterprise success. Higher results can be achieved when a critical mass of economic and institutional agents are integrated through cooperative horizontal and vertical networks (Humphrey and Schmitz, 2004).12 Simultaneously, the IADB shows growing interest in the analysis of the internal features of competitive local contexts, such as those aspects that favor entrepreneurship and endogenous dynamism within local and national production systems. The most explicit element is the recent research project on entrepreneurship in a number of Latin American and Asian countries (Kantis et al., 2001) and of the public policies that can promote a diffuse, dynamic entrepreneurship that stems from scientific knowledge and the management of high technology (Kantis, 2004). In general, the IADB shows a new tendency, above all, in research. Through this novelty the institution seems to be oriented to change its overall traditional approach (led to financing the most sound operations and projects). For the future, the IADB seems more likely to focus its investment operations where a thick institutional setting is present (e.g. a dense network of business associations, trade unions and local institutions, agencies and governments) and strong collective work is implemented (e.g. shared local development projects). If these research prospects are going to spread on a wider basis within the IADB, thus, a relevant hypothesis can be made. This involves a passage from the traditional type of project management oriented to support individual profitable (ideas of) firms to a new institutional approach that emphasizes the importance of organizing collective initiatives and dynamic local production systems. This capacity of organizing programs and projects is rooted in the more complex logic of joint action and external economies (that represent the dual nature of ‘collective efficiency’), industrial territories (e.g. clusters and districts), and global value chains (Pietrobelli and Rabellotti, 2004). These wider development contexts (industrial territories and value chains) are more likely to set up the basis of successful prospects for SME development and for creating the environment where industrial development policies can work more effectively.

3. The European experience with SMEs: old and new trends Europe has a very important history of SME development. Over time, the European Union has been forming and applying policy models that

14


helped the SMEs to reach an outstanding success. In 2003 in the European Economic Area (EEA) 19.3 million SMEs employed 97.4 million workers, while 40 000 large firms (firms with more than 250 workers) employed 42.3 million workers (Commission Europeenne, 2003: 9). Micro and small firms have been gradually increasing in number and employment, while large and medium firms show a decreasing trend in terms of employment creation over the past 15 years (ibid.: 9–10). In the period 1990–2001, labor productivity (value added/employee) in the SME sector has been growing substantially. It increased from a basis of 100 in 1990 up to 109.8 in 2001, whereas large companies simultaneously decreased their labor productivity from 100 to 87.5 (European Observatory of SMEs, 2005). These data show that in the European economic development, the SMEs had and currently have a very important role, complementing, and in some phases even leading, the regional economic process. Of course, this cannot be considered a uniform trend, since there are significant differences of approach among the various countries. For example, in the past the Anglo-Saxon system privileged a market approach, with poor public intervention, while other countries, such as Italy, supported the enterprise system more intensely through specific legal devices deemed to protect the position of SMEs in the economy. Scandinavian countries supported the private initiative within a concept of ‘State-Providence’ and emphasized the role of associationism as a key feature for SME competitiveness. Germany and Belgium implemented the ‘principle of subsidiarity’, urging the state to complement the private sector in the services they do not provide. A number of countries were used to favoring decentralization in decision-making (e.g. Germany, Spain and Switzerland), thus they shifted responsibilities to local governments; in contrast, in Italy, Great Britain and France the national authorities kept decisionmaking highly centralized (European Observatory of SMEs, 2003). These different approaches produced relevant variations in SME performance across Europe that may be observed also today; for example, SMEs tend to be very relevant in Italy in terms of production, export, productivity, remuneration of workers, among other aspects. In contrast, in Germany, France and Great Britain the ‘national champions’ remain extremely important (Bianchi, 1998). In spite of these historic differences, the European development process has been giving progressively more attention to the support of local production systems and their SMEs. Simultaneously, the long process of debating and interacting that has taken place in Europe has


15

created processes of mutual learning, for example benefiting from the benchmarking experiences of industrial districts in Italy and Denmark; the technological-scientific parks in England and France, the defense of competition in Spain, among others. These processes of mutual learning have led policy-makers as well as the private sector to identifying common policy approaches and development models and have progressively reduced the major differences that existed a few decades ago. As a consequence, the present policy landscape within the European Union tends to present an increasing homogeneity in norms and behaviors (Bianchi et al., 2006).13 Table 1.2 highlights the growing uniformity of development policies achieved in the past few years in Europe. These countries realize that, without appropriate systems for the promotion of the competitive position of SMEs, these firms can face increasing problems responding to the challenges imposed by market liberalization and by the considerable flexibility and competitiveness achieved by large firms. In spite of the extraordinary awareness that European policy-makers and entrepreneurs exhibit, this homogeneous and complete type of approach (see Table 1.2) remains too open and may spur large numbers of extremely specific, confined operations that lack a common planning process and that may not create sufficiently wide-reaching operations; in turn, this may not generate efficient and effective operations at the local, national and international level. This aspect is particularly important in the context of developing economies, which need a scheme to interpret the development process and to structure strategies that support the private sector; they need a flexible scheme that may be controlled and modified in the short term on the basis of effective market responses. This is necessary because policy-makers in developing countries work with scarce resources; thus they need to define priorities to support the private sector and the SMEs. For these reasons, on the bases of the wide variety of theoretical approaches, experiences and opportunities, we identify a circular approach made up of three strategic drivers for SME development, which are complementary and interdependent and which can help determine effective industrial development policies. These are the promotion of high technologies, the productivity growth of traditional enterprises and the systemic networking of firms. These are seen in detail in the next section.

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Table 1.2 Actions implemented from May 1997 to the end of 1999 Administ. incentive Belgium Denmark Germany Greece Spain France Ireland Italy Luxemburg Holland Austria Portugal Finland G. Britain Switzerland Norway

X X X X X X X X X X X X X X X X

Delay in payment

X

X X

X X

Finance

Internationalization

Information

Employment training

R&D

Entrepreneurship




X X X X X X X X X


X X X X X X X X

Source: Observatoire Europeenne des PME, Sixieme Rapport, Bruxelles, 2000: 17.

X X X X X X

X X X X X X


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4. A systemic approach to the development of SMEs 4.1 Three strategic development lines and their complementarity These three aspects (high-tech development, productivity growth in traditional sectors and systemic networking) are relevant and complementary for the following reasons. The development of high technology gives dynamism to the system; it promotes the creation and accumulation of new competitive advantages such as the presence of highly qualified personnel, and the availability of specialized networks of service providers, among others. This effort helps to push the technology frontier further ahead and to undertake the transition from the ‘lowroad’ of competition and development to the necessary ‘high-road’ (Pyke and Sengenberger, 1992). Productivity growth in the large sector of traditional enterprises accelerates their competitiveness, sales and capital accumulation and sets up the bases to upgrade their technology and to shift to higher value-added stages of productions. It also creates room for more uniformity and harmonization between the former high-tech sector and this traditional sector of SMEs that may promote effective cooperation between the two and favor the working of the third strategic driver. In fact, the simultaneous development of strong production linkages among the most innovative firms and the segment of traditional enterprises is more likely to prevent the formation of new forms of dualism and fractures (Bianchi et al., 2000; Parrilli, 2004b), which may spread to the social environment in the form of social and political conflicts (for instance, by keeping down wages and payments to suppliers and subcontractors). On the whole, this strategy of strengthening linkages and networking is more likely to ease the process of shaping a systemic national policy that promotes the development process in local and national production systems. These strategic lines (see Figure 1.1) are thought to complement each other within the development system, which means that the system needs innovative firms to spur the overall growth of the (local and/or national) system. This objective requires efforts in high-technology development. Simultaneously, the growth of the system impels these leading firms to rely upon a large number of healthy traditional firms (e.g. through an extended network of suppliers and subcontractors). This requirement is guaranteed only when these traditional enterprises increase their productivity levels. The actions that promote networking and inter-firm cooperation can help connect these apparently separate sectors and can, thus, support the national development process by means of upholding the above-mentioned systemic approach.

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Hi-tech development

Productivity Increase

Networking

Figure 1.1

A tripartite framework for SME development

4.2 High technology development The current globalized market does not allow the SMEs (e.g. in Europe as well as in Latin America) to compete on the basis of low prices; in fact there are countries (e.g. China) that exploit scale economies that are hard to offset. The structural upgrading in production represents the solution that advanced countries have undertaken in the past 20 years and that currently represent the major challenge for the majority of small firms, particularly in traditional manufacturing sectors (Pyke and Sengenberger, 1992; Cooke, 1996; Kaplinsky and Readman, 2001). Innovation in product, process, market channels and organization structures and procedures are the means that permit SMEs to reach the market with new advantages with respect to traditional large companies that benefit from economies of scale (Pyke and Sengenberger, 1992; Kaplinsky and Readman, 2001). Radical innovation is based upon the development of advanced technology and the participation of highly qualified human resources. These two factors are among the most important bases for a significant innovation policy (Lall, 2001). For this reason these two aspects need to be measured, assessed and promoted. The Latin American region presents important human resources that can sustain the strategy of innovation, but that are underutilized and often leave their own countries in what is known as the ‘brain-drain’ process (Cimoli and Katz, 2001). In this wide developing region containing more


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than 500 million people there are countries that display an abundance of skilled and qualified human resources, such as Brazil, Mexico, Argentina, Costa Rica, among others. Nonetheless, this capacity is not adequately distributed across the local populations, which still suffer a deep segmentation of capabilities and opportunities that hinder the local and regional development process (UNDP, 2002). However, these countries remain among the main recipients of Foreign Direct Investments (FDI) and, simultaneously, remain among the main recipients of international aid (CEPAL, 2004).14 In this sense, the financial resources that are needed to spur a strategy of production and commercial innovation are available. The objective should thus be to identify the most effective ways to promote technology transfer from FDI by avoiding the typical attempt of multinational companies to invest in low value-added activities meanwhile keeping the most innovative activities in their own headquarters, e.g. R&D, financial and marketing departments (Hymer, 1972; Cowling and Sugden, 1997). Only a group of firms can focus on generating radical innovations because special capabilities are required to be able to work on the technology frontier; just a few particularly dynamic firms have these capabilities and, for this reason, represent the leading firms within their national and local production systems. After the phase of experimentation and startup of innovative productions, direct (e.g. through training programs or technical assistance from mother firms) and indirect (e.g. by spillovers) transfer of these technologies can cause these practices to trickle down to the rest of the production system, elevating its competitive capacity. The experience of various Latin American countries shows their capacity to reach extraordinary levels of innovativeness and development in sectors of high technology, as in the case of production of aircraft and auto-motive industries in Brazil, software in Costa Rica and Mexico, automobiles and automotive industry in Argentina and Mexico, pharmaceuticals in Chile, among others. For this reason ‘innovation policies’ are very important in these contexts. These can promote the creation of value in sectors of high technology, multiplying the opportunities for employment above all for the young generations that enjoy an adequate level of formal and applied education; these efforts may help create a series of services that are extremely useful for the existing firms in the manufacturing sector and, in this way, may help to diversify the national economic structure (Lall, 2001). Several important cases are available in terms of best policy practices, which include some experiences of academic spin-off, scientific and technological parks, business incubators, among others, which altogether represent relevant cases of

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public programs that can promote this attitude towards innovation in the local production system (EU, 1998; 2002; Baroncelli, 2000; Bianchi and Parrilli, 2002; 2004; Kantis, 2004). Within this area of innovation promotion among SMEs this book presents some relevant studies and international experiences. In Chapter 2, Laura Ramaciotti presents one of the main institutional innovations that was recently introduced in the Italian university system to promote the innovation capacity of regional and local production systems. The author emphasizes the importance of university programs for firm creation in areas of science and technology. The case of the region Emilia-Romagna shows the dynamism of local universities that increase their coordination with the private sector by means of promoting the creation of new firms of high scientific content that may boost the technological capacity of the local production system; this effort may also help the private sector to benefit in a more efficient form from scientific knowledge developed within universities. This contribution details, in the specific case of the region Emilia-Romagna, Italy, the current opportunities of hi-tech development based on cross-sector specializations within both the research system and the production system. In Chapter 3, Stuart Schweitzer and Marco Di Tommaso describe the characteristics that favor the involvement of SMEs in high-tech sectors, among which are the diseconomies of scale that disadvantage large firms vis-à-vis small firms (and which also have effects on initial sunk costs and risk aversion). This chapter shows the relevant features of the biotechnology sector in the United States with special reference to the difficulties and risks faced by SMEs that attempt to enter this high value added production (e.g. uncertainties in return on investments, firms mortality); it also stresses the importance of clustering as a means to overcome these difficulties by creating a protected environment for SMEs. This work ends up indicating a few policy keys that may promote the creation of high-tech SMEs in the context of developing economies; by this means a new window of opportunities are opened to more traditional and less developed economies. The analysis presented in Chapter 4 by Hugo Kantis and Pablo Angelelli examines the features of ‘entrepreneurship’ in high technology sectors in Latin America, and compares them with those that are found in traditional sectors. The authors analyse both the problematic areas of new hi-tech firms (e.g. less support from social networks and uneasy access to credit and to clients in the first few years), and the strategic strengths (e.g. higher knowledge and more support from professional sources of competence; more involvement with relevant institutions, capacity to


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provide advanced services to large companies). On these bases, this chapter focuses on the key aspects in the policy attempt to target the development of SMEs in high-tech sectors that include wider objectives (e.g. promoting entrepreneurial culture and specialist/technical education) and more specific contributions (e.g. creating business incubators and providing technical assistance in the start-up phase). Overall, these chapters display relevant features and strategies for the promotion of firms based on high scientific content and hightechnologies; these are deemed to create new competitive advantages in local and national production systems, which is a novel but necessary task for developing economies in the current context of globalization. 4.3 Productivity growth of traditional SMEs The second strategic driver for SME development refers to the growth of productivity, particularly labor productivity within the traditional sector of small and medium-sized enterprises. This is needed because most firms in any country, and more specifically in developing countries, operate in traditional sectors (e.g. textiles, shoes, furniture, among others) where they use non-qualified human resources and often adopt obsolete technology or craft techniques of production. As a consequence, they tend to compete only on the basis of low prices; this represents a ‘low-road’ type of competition and development (Pyke and Sengenberger, 1992; Kaplinsky and Readman, 2001). This approach leads to conflicts within the production chain (e.g. entrepreneurs vs. workers, producers vs. suppliers and subcontractors, producers vs. clients), which make it difficult to consolidate the competitive position of local SME systems. For this reason, the structural upgrading of traditional SMEs becomes a key target, which can be implemented through substantial growth in their labor productivity. This can take place through a set of measures that facilitate the transfer of technical systems that have been successful in other contexts. In this case we cannot focus on innovation mechanisms, but rather on imitation and technology transfer policies and mechanism (Romjin, 2002), which have been useful in the relatively recent growth of the newly industrialized south-east Asian economies (Amsden, 1989; Wade, 1990). Programs and mechanisms that support the quality upgrading of processes and products become extremely important. This has been recently promoted at the international level through procedures of standardization and certification (e.g. ISO 9000 for quality, ISO 14000 for the environment, SA 8000 for social accountancy); these systems permit traditional firms to learn and follow development trajectories that have been used in the past to increase SME productivity and competitiveness

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in industrialized economies. Through these procedures the majority of traditional SMEs can be connected with processes of innovation spurred by the small sector of modern (mainly large) firms; by this means the overall productivity of the enterprise system can be increased. On this aspect, the concept and practice of ‘EU structural policies’ can be emphasized (EU, 1998; 2002). These are oriented to improve the productive structure of less developed territories by enhancing their productivity and competitiveness. In this line, in the past 10 years the EU promoted a series of advanced experiences in Northern Africa (e.g. Tunisia and Morocco) under the scheme called Mise-à-niveau (‘renewal’). This program includes a number of actions (e.g. technical assistance, training, credit for technology upgrading) that permit developing countries to update their technology and production standards in order to access the European market on a more competitive and organized basis (UNIDO, 2001). Within this strategic area this volume includes three valuable contributions that help understand how it is possible to identify and support the SMEs in their daily effort to upgrade their productivity. In Chapter 5 Nicola Bellini analyses the business development services that proved to be key for the development of Italian industrial districts and of other local production systems worldwide, and whose development is currently particularly relevant in Latin America. This analysis discusses the typologies of service providers and the policies that support the provision of these services with special reference to the role that public and private institutions may hold for an efficient and effective delivery of these services to SMEs. This is a key issue to promote the necessary division and specialization of labor within local production systems and, as a consequence, the productivity of traditional SMEs. In Chapter 6 David Audretsch, Maria Callejon and Mari Jose Aranguren, analyse the concept of ‘entrepreneurship’ reviewing the academic literature and apply it to the case of Spain to verify the material opportunities for the growth of micro, small and mediumsized enterprises in open markets. This analysis shows that the dynamic entrepreneurship that may promote an effective growth of local economies is also associated with the size of the firms (within the category of small firms); firms that start with few employees present higher development prospects than enterprises that are based on selfemployment; this is due to the poor entrepreneurial approach taken by the second type of firms that are more typically oriented to satisfy basic demands for employment and income rather than to find new successful ways to compete in the market. Important consequences for


23

policy-making can be drawn from these findings that can support the promotion of traditional SMEs. Chapter 7, by Justo Aguilar and Maikol Elizondo, presents the experience of SMEs in Costa Rica and shows that public policies oriented to the promotion of industrial restructuring and exports (e.g. the formation of industrial areas, upgrading in technical education and training, attraction of high-tech FDI, subsidies for export promotion) have promoted a significant strengthening of the national SME sector, including the traditional firms. This process is generating a transition from a production system based on low-cost competitiveness to a system based on specialization and on improvements in productivity. This strategy has promoted a better and deeper insertion of SMEs in international markets insofar as they have become relevant actors in the country’s process of economic development. Overall these contributions highlight strategies of growth for the traditional SME sector; exploiting business development services, selecting business-oriented firms and promoting specialization and quality to access international markets represent strategies that proved successful in Spain, Costa Rica, and in other countries. Other systems may be adopted; however, the objective is relevant in that it focuses on increasing productivity as a means to upgrade the competitiveness of small firms’ systems employing average skilled labor, producing average quality products for medium-income segments of consumers in both developed and developing economies.

4.4 Networking The third strategic driver of this systemic approach to SME development points to the creation of a critical mass of firms at the local, regional and national levels. The geographical aggregation of enterprises represents the traditional way that SMEs adopt to produce scale and scope economies via wider economies of agglomeration and deeper division and specialization of labor, and that make them able to compete with larger firms in global markets. Different systems may help achieve the aforementioned critical mass; ‘clustering’ is the most typical form (Brusco, 1982; Piore and Sabel, 1984; Becattini, 1990; Best, 1990; Schmitz, 1992, Brioschi and Cainelli, 2001); however, also ‘associationism’ (Platteau, 1994), ‘subcontracting’ (Caddy, 1998; Innocenti and Labory, 2002) and other local and trans-local forms of more or less voluntary networking (Gilly and Torre, 1998; Storper, 1998; Fujita et al., 2001; Guerrieri and Pietrobelli, 2004) represent potentially relevant solutions.

24


The main idea is to create groups of firms in local territories that may cooperate and also benefit from a number of important external economies (e.g. flow of skilled workforce, flow of innovations and information, flow of clients and traders) that represent the known aspects of ‘collective efficiency’ (Schmitz, 1995). These forces represent the strengths of local systems based on small firms that permit them to compete with larger firms thanks to their notable flexibility and capacity to supply orders with high quality standards (Best, 1990). These competitive aggregations (i.e. clusters and districts) represent potential bases to link up the most innovative firms with the most traditional SMEs. In this way, the creation of an ‘inclusive’ type of growth could be stimulated and could permit all types of firms to grow simultaneously, overcoming ‘excluding’ modalities, in which some firms grow while other close down operations and dismiss workers (Bianchi and Parrilli, 2002; Parrilli, 2004b). This can be further spurred by opening discussions at the local level on territorial development plans in the medium to long term. In this way, the entrepreneurs could be able to understand the scenario where they operate and, on this basis, may establish more prosperous synergies and complementarities with other firms and institutions. This approach could embody, for example, policy actions oriented to stimulate relatively horizontal networks of subcontracting (more balanced in terms of market power), which could promote a thorough development of local firms and territories (Sacchetti and Sugden, 2003). This consciousness certainly needs to be complemented with the increasing weight that global value chains have recently been assuming and which have been linking the dynamics of local development to international markets (Gereffi and Korzeniewicz, 1994; Humphrey and Schmitz, 2004; Pietrobelli and Rabellotti, 2006). These academic constructs lead the policy analysis to surpass local and national borders (e.g. local clusters) and to focus on useful trans-local and trans-national networks that may contribute important elements to the growth of the national production system (e.g. specialized knowledge and information; marketing and distribution channels). The policies that can promote this development logic, and the related strengthening of SME-based economies, can be called ‘linkage policies’ because they try to create competitive connections among firms and between them and other economic and institutional agents in general. This is the third key element of the suggested approach for the promotion of SMEs and their production systems competing in globalized markets. Part 4 contains relevant contributions that analyse the strengths of SMEs that operate in geographically and sectorally bounded contexts


25

such as clusters and local networks that are created among actors in the cluster and in local/regional production chains that may help increase the competitiveness of local systems. In Chapter 8, Lisa De Propris presents a thorough analysis of social capital together with the issue of trust within clusters of firms and in networks spanning beyond localities (glo-cal networks). This is a socio-economic concept that is particularly relevant for the process of economic development in SME-based economies because it sets the bases to promote the much needed cooperative actions among small firms (which create scale and scope economies). The author examines different academic interpretations of trust and values the importance of a ‘systemic’ kind of trust at work within SME production systems as opposed to ‘calculative trust’. She emphasizes the importance of promoting trans-local networks as a form to create a particularly dynamic social capital that may help in creating further competitive capabilities at the local level. From a policy point of view, these considerations stress the role of systemic trust and social capital, which in former decades contributed to the development of several industrial districts; this focus on the roots of trust and cooperative behaviour should currently extend the promotion of collective and mutually enriching actions to systems of firms that exchange competences and products beyond their geographical location. In Chapter 9, Wilson Suzigan, Renato Garcia and João Furtado analyse the system of governance with reference to specific local production systems (clusters) in the South of Brazil. The linkage of local SMEs to global value/commodity chains driven by large multinational corporations may elicit more hierarchical and less dynamic relationships in the local production system; in contrast, clusters that present more horizontal governance relationships seem to be able to promote higher dynamism (e.g. active entrepreneurship, firm creation and innovation) that has positive impacts on local and national economic development. This conclusion delivers key lessons for the promotion of dynamic clusters in local economies. In Chapter 10, Peter Knorringa investigates the most common typologies of clusters that are found in developing economies and opens a debate on what growth trajectories may be prospected in these contexts. In particular, despite praising the model of ‘marshallian industrial districts’ (horizontal systems populated only by SMEs) and its past success, the author identifies a trend of strengthening of local production system that include large firms within the locality (the so-called ‘huband-spoke cluster’; see Markusen, 1996). Evidence is provided on the transformation (materialized or attempted) of other types of clusters,

26


such as ‘satellite clusters’ (where the local SME system is driven by large firms located outside the cluster) and ‘marshallian industrial districts’ from their original configuration to the aforementioned ‘hub-and-spoke cluster’. In this way, Knorringa proposes a less ideological view of clustering that, however, maintains the importance of creating a critical mass of firms as a way to increase their competitiveness within international markets. Finally, in Chapter 11 Pietrobelli and Rabellotti identify a variety of successful clusters in Latin America (specifically in Mexico, Brazil, Nicaragua and Chile), and analyse their upgrading prospects in terms of product, process, function and inter-sectoral innovations. Combining the key concepts of collective efficiency and global value chain with Pavitt’s industrial taxonomy, the authors classify these clusters in natural resource-based, traditional manufacturing, complex production systems and specialized suppliers. On these bases they provide both detailed descriptions of the main production features in each kind of cluster and suggestions for public policies and programs likely to promote growth in these kinds of clusters. All chapters in this part of the volume highlight the importance of networks; these may be built up at both levels, the locality (e.g. the cluster) and beyond (e.g. global value chain or global production network). In all cases, they represent the creation of an ‘inclusive system’ that is able to pull together collective forces of large numbers of firms and that permit local and national economies to transfer the benefits of growth from the most modern enterprises within and outside their economies to the more traditional SMEs operating within their production systems. Overall, it is a key strategy to promote homogeneous growth and income distribution in developing countries.

5. Conclusions In conclusion, this selection of studies helps to characterize a systemic approach to the development of SMEs and of their local production systems. The promotion of new technologies, the increase in productivity and the development of networking represent three strategic drivers for promoting SME competitiveness in local and global markets. These are based on specific experiences and scientific analyses some of which are presented in this volume. For instance, the EU explicitly prioritizes these policy drivers (e.g. innovation policies, structural policies, among many others); thus it implicitly recognizes the relevance of the proposed policy framework with special reference to the context of developing economies


27

that need to deal with issues of scarcity of public resources and public goods. These strategic lines are deemed to help SMEs acquire new competitive advantages, mainly through knowledge acquisition and through economies of agglomeration. This approach may permit SMEs to respond to the entry of new competitors in the global market insofar as they affect their own local markets, where global competitors start to join in. In addition to these considerations, through this volume we argue that these policies are more likely to be successful when they are not taken independently, but systematically connected. They can reinforce each other and permit the system to grow as a whole without any fractures. The complementarity and interdependence among the three strategic drivers is in line with a systemic approach that is thought to avoid the fracture currently arising in the context of increasing global competitive pressures between modern and traditional sectors in many developing economies (Bianchi et al., 2000; Bianchi and Parrilli, 2002; Parrilli, 2004b). This approach could help stimulate the enterprise system as a whole and favor the development of the entire spectrum of social and economic agents that operate within these economies.

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Bianchi, P., Di Tomaso, M. and Rubini, L. (2000), Le api audaci, Angeli, Milano. Bianchi, P., Labory, S., Paci, D. and Parrilli, M.D. (2006), ‘Small and MediumSized Enterprise Policies in Europe, Latin America and Asia’, in Bianchi, P. and Labory, S. (eds), Handbook of Industrial Policy, Edward Elgar, Cheltenham. Brioschi, F. and Cainelli, G. (2001), Diffusione e caratteristiche dei gruppi di piccole e medie imprese nelle aree distrettuali dell’Emilia-Romagna, Fondazione Giordano dell’Amore, Giuffré, Milano. Brusco, S. (1982), ‘The Emilian Model: productive decentralisation and social integration’, Cambridge Journal of Economics, Vol. 6. Caddy, J. (1998), ‘The changing role of SMEs in Japan’, CFR, op. cit. CEPAL (2004), Balance Preliminar de las economías de América Latina y el Caribe, Santiago. Cimoli, M. and Katz, J. (2001), ‘Structural reforms, technological gaps and economic development: a Latin American perspective’, ECLAC Discussion Paper, Santiago. Commission Europeenne (2003), Highlights from 2003 Observatory, Brussels. Consorzio Ferrara Ricerche (CFR) (1998), The role of SMEs: Asian and European experiences, AESMEC, University of Ferrara, Naples. Cooke, P. (1996), ‘Building a twenty-first century regional economy in EmiliaRomagna’, European Planning Studies, Vol. 4(1). Cooke, P. and Wills, D. (1999), ‘Small firms, social capital and the enhancement of business performance through innovation programmes’, Small Business Economics, Vol. 13, September. Cowling, K. and Sugden, R. (1997), Beyond Capitalism, Pinter, London. Cowling, K. and Sugden, R. (1999), ‘The wealth of localities’, New Political Economy, Vol. 4(3). De Soto, H. (1989), El otro sendero, Editorial El Barranco, Lima. Dunning, J.H. (1988), Explaining International Production, Unwin Hyman, London. Dussel, Peters E. (2003), ‘Condiciones y retos de las MIPYME en Centroamerica’, in Hernandez R., Competitividad de las MIPYME en Centroamerica, CEPAL-GTZ, Mexico. Esser, K., Hillebrandt, W., Meyer-Stamer, J. and Messner, D. (1994), La competitividad sistemica, Instituto Aleman para el Desarrollo, Berlin. E.U. (2002), ‘Produttivitá: la chiave della competitivitá delle economie e delle imprese europee’, COM(2002) 262, Bruxelles. E.U. (1998), ‘The competitiveness of the European enterprises in the face of globalisation: how it can be encouraged’, COM (1998) 718, Brussels. Fajnzylber, F. (1988), International competition: agreed goals and tasks, CEPAL Review no. 36, Santiago. Fujita, M., Krugman, P. and Venables, A. (2001), The spatial economy, MIT Press, Cambridge, Massachussets. Gereffi, G. and Korzeniewicz, M. (1994), Commodity Chains and Global Capitalism, Greenwood Press, Westport, Connecticut. Gilly, J.P. and Torre, A. (1998), Dinamica di prossimitá e reti: introduzione, L’Industria, Vol. XIX, (3), July–September. Guerrieri, P. and Pietrobelli, C. (2004), ‘Industrial districts’ evolution and technological regimes: Italy and Taiwan’, Technovation, Vol. 24(11), November. Heckscher, E. (1919), ‘The Effect of Foreign Trade on the Distribution of Income’, Ekonomisk Tidskrift, Swedish Journal of Economics, Stockholm.


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Hirschman, A.O. (1958), The strategy of economic development, New Haven, Connecticut, Yale University Press. Humphrey, J. and Schmitz, H. (2004), ‘Chain governance and upgrading: taking stock’, in Schmitz, H. (ed.), Local enterprises in the global economy, Edward Elgar. Hymer, S. (1972), ‘The multinational corporation and the law of uneven development, in Bhagwati, J., Economics and world order, Macmillan, London. Innocenti, A. and Labory, S. (2002), ‘The advantages of outsourcing in terms of information management’, Quaderni del Dipartimentodi Politica, no. 370, University of Siena. Inter-American Development Bank (2003), ‘Annual Report: the year’s lending by country’, Washington. Kantis, H., Komori, M. and Ishida, M. (2001), Entrepreneurship in emerging economies: cases from Latin America and South East Asia, Banco Inter-Americano de Desarrollo (BID), Washington. Kantis, H. (ed.) (2004), El proceso emprendedor en America Latina y otras experiencias internacionales, Banco Inter-Americano de Desarrollo, Washington. Kaplinsky, R. and Readman, J. (2001), ‘Integrating SMEs in global value chains: spreading the gains from globalisation’, IDS Bulletin, Vol. 32(3), Sussex University. Krueger, A. (1983), Trade and employment in developing countries, Chicago University Press, Chicago. Krugman, P. (1994), ‘Does Third World growth hurt First World prosperity?’, Harvard Business Review, July. Lall, S. (1992), ‘Technological capabilities and industrialization’, World Development, Vol. 20(2). Lall, S. (2001) Competitiveness, Technology and Skills, Edward Elgar, Cheltenham. Locke, R. (1995), The remaking of the Italian economy, Cornell University Press, Ithaca. Markusen, A. (1996), ‘Sticky places in slippery space: a typology of industrial districts’, Economic Geography, Vol. 72, Clark University. Observatory of European SMEs (2005), SME statistics, Brussels, www.eim.nl/ Observatory_Seven_and_Eight/start.htm. Observatory of European SMEs (2003), Highlights from the 2003 Observatory, Observatory of European SMEs, no. 8, http://europa.eu.int/comm/enterprise/library/ lib-entrepreneurship/series_observatory.htm Observatoire Europeenne des PME (2000), Sixieme Rapport, Brussels. Ocampo, J.A. (2001), Una Decada de Luces y Sombras: America Latina y el Caribe en los Años Noventa, UN Publications, New York. Ohlin, B. (1933), Interregional and International Trade, version published in 1968, Harvard University Press, Cambridge. Parrilli, M.D. (2004a), ‘A stage and eclectic approach to industrial district development: two policy keys for survival clusters in developing countries’, European Planning Studies, Vol. 12(8). Parrilli, M.D. (2004b), ‘Integrating the national industrial system: the new challenge for Chile’, Review of International Political Economy, Vol. 11(5). Parrilli, M.D. (2007), SME cluster development, Palgrave Macmillan, Basingstoke and New York. Peres, W. and Stumpo, G. (2002), Las pequeñas y medianas empresas industriales en America Latina, CEPAL, Ediciones Siglo XXI.

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Pérez Sáinz, J.P. (1995), ‘Globalización y neoinformalidad en América Latina’, in Nueva Sociedad, No. 135, Caracas. Perroux, F. (1950), ‘Economic Space: Theory and Applications’, Quarterly Journal of Economics Vol. 64, 89–104. Pietrobelli, C. and Rabellotti, R. (2004), Upgrading in clusters and value chains in Latin America, Inter-American Development Bank, Washington. Pietrobelli, C. and Rabellotti, R. (eds) (2006), ‘Upgrading to compete’, InterAmerican Development Bank, Harvard University Press. Piore, C. and Sabel, M. (1984), The second industrial divide, New York, Basic Books. Platteau, J.P. (1994), ‘Behind the market, where real societies exist’, Journal of Development Studies, Vol. 30(3), April, 533–77. Portes, A., Castells, M. and Benton, L. (1989), The informal economy: studies in advanced and less developed countries, Johns Hopkins University Press, Baltimore. Putnam, R. (1993), Making democracy work, New York. Pyke, F. and Sengenberger, W. (1992), ‘Introduction’, in Pyke, F. and Sengenberger, W. (eds), Industrial districts and local economic regeneration, ILO Geneva. Redding, S. (1999), ‘Dynamic comparative advantages and the welfare effects of trade’, Oxford Economic Papers, Vol. 51(1). Reinhardt, N. and Peres, W. (2000), ‘Latin America’s New Economic Model’, World Development, Vol. 28(9). Romjin, H. (2002), ‘Small enterprise development in developing countries: innovation or acquisition of technological capabilites’, in van Dijk, M.P. and Sandee, H., Innovation and small firms in the Third World, Edward Elgar, Cheltenham. Sacchetti, S. and Sugden, R. (2003), ‘The governance of networks and economic power: the nature and impact of subcontracting relationships’, Journal of Economic Surveys, Vol. 17(5). Schmitz, H. (1992), ‘On the clustering of small firms’, IDS Bulletin, Vol. 23, Institute of Social Studies, Sussex University, Brighton. Schmitz, H. (1995), ‘Collective efficiency: growth path for small-scale industry’, Journal of Development Studies, Vol. 31. Schmitz, H. (ed.) (2004), Local enterprises in the global economy, Edward Elgar, Cheltenham. Singh, A. (1992), ‘Industrial policy in the Third World in the 1990s: alternative perspectives’, in Cowling, K. and Sugden, R., Current issues in industrial economic strategy, Manchester University Press. Speer, J. (1997), ‘The Urban Informal Economic Sector’, in Walker, T.W. (ed.), Nicaragua Without Illusions: Regime Transition and Structural Adjustment in the 1990s, Scholarly Resources, Wilmington, DE. Stiglitz, J. (2001), ‘Globalization and the economic role of the state in the new millennium’, Industrial and Corporate Change, Vol. 12(1). Stiglitz, J. (1998), ‘Towards a new paradigm for development’, 9th Raul Prebisch Lecture, UNCTAD, Geneva, 19 October. Sugden, R. and Wilson, J. (2002), ‘Development in the shadow of the consensus: a strategic decision-making approach’, Contributions to New Political Economy, Vol. 23. Sylos Labini, P. (2000), Sottosviluppo: una strategia di riforme, Editori Laterza. Tokman, V. (1992), Beyond the informal economy, PREALC-ILO, Geneva. UNDP (2002), Human Development Report, New York.


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UNIDO (2001), Support to SMEs in the Arab region: the case of Tunisia, Coord. Di Tommaso, M., Rubini, L. and Lanzoni, E., Bologna. United Nations (1999), World Investment Report: trends and determinants, New York and Geneva. Wade, R. (1990), Governing the market, Princeton University Press, Princeton. World Bank (2002), Review of Small Business Activities, Report, Washington. World Bank (1993), The East Asian Miracle: economic growth and public policy, Oxford University Press. Ybarra, J.A. (2003), ‘Viaggio all’interno della nuova economia sommersa in Spagna’, L’Industria, Vol. 24 (1), Il Mulino, Bologna.


Part 2 Hi-tech Promotion


2 The Regional Innovation System in Emilia-Romagna Laura Ramaciotti1

1. Introduction: the evolution of the Emilian model Since the 1980s the Emilia-Romagna constitutes a benchmark for specialists in industrial districts and more generally in local production systems (Piore and Sabel, 1984). Since then there has been a remarkable evolution of industrial leaders that have been establishing their brands in global markets and have been controlling supplies via global networks. Many firms in this position sold their businesses to multinational companies, which ended up buying and controlling the whole production network. As a result, by the end of the 1980s, a significant process of consolidation of leaders occurred by means of mergers, acquisitions and cross-exchange of minority shares (Bianchi and Gualtieri, 1990). On the basis of this experience, an approach to industrial clustering has been consolidated, the so-called ‘Emilian Model’, which is centred on the capacity to pull local businesses together and to supply them with good quality services provided by local institutions (Leonardi and Nanetti, 1990). Economic development is thus linked to the consolidation of civic commitment that is related to a strong sense of cultural belonging as well as to good management practices; this civic aspect works as a positive externality for the growth of specific productions/sectors that benefit from collective trust provided by a strong civil society (Putman et al., 1985). The development of what is commonly known as ‘social capital’ has been strengthened through several local government interventions oriented to push the development of firms towards higher quality levels that would consolidate the best practices (Cossentino et al., 1997). The regional network of centres (led by regional and local governments, business associations and leader firms) providing services to firms played a significant role in the success of this model; this network 35

36


provided services (e.g. analyses of fashion trends, quality certificates, technical trials on machinery) that traditional manufacturing firms were not able to guarantee. These business development centres were used as catalysts for the development of industrial districts and operated, in the initial phase, as accelerators in the process of ‘tertiarization’ of the economy in an area dominated by an industrial culture (Bellini et al., 1997). Over the years this model evolved significantly and opened a debate on the definition of territorial agglomeration that would be wider than the concept of ‘industrial districts’ because of the institutional character that makes different local institutional systems compete with one another (Poma, 2003). It should however be noted that the old ‘Emilian Model’ materialized essentially in the central area of the region, between Bologna and Parma along the Emilian road, and only later expanded towards Ferrara and Ravenna, which were areas dedicated to chemical industries, and towards other marginal areas of the region (Leonardi and Nanetti, 1990). In the 1990s globalization introduced new elements within the international markets. The appearance of a new form of competition in low-tech productions, the success of new technologies and trade expansion towards new markets promoted a significant change in organization and internationalization strategies. Large companies coped with the difficulties connected to this new competitive scenario through a deep reorganization based on technological innovation. Small companies relied mainly on operational flexibility aimed at producing less standardized products; these trends led to increasing the productivity gap with respect to large companies (Unioncamere, 2003). In 2000, the Emilia-Romagna region reformed its interpretation of local development by approving the national law 317/1991; it therefore abandoned the region’s former approach to industrial districts development. With this law the economic importance of industrial districts was recognized and the role of identifying these areas was given to regional governments in order to allow groups of local businesses to benefit from the incentives guaranteed by this law. Such an approach was strengthened by the national law 140/1999 that focused on local production systems based on small and medium firms, including basic concentrations of firms and industrial districts where a strong sectoral and geographical specialization may lead to a need for more complex local services. As regards to the homogeneity that characterized these areas in the past, district firms (including both those with direct access to the market

Laura Ramaciotti

37

and those that produce intermediate goods and services for other firms), have developed in different forms. Size growth is observed and it is connected to new functions operated by firms, such as research and development, trade and management, selection of suppliers that are currently part of a multiple-tier structure, and appearance of business groups within districts that may involve subsidiary companies abroad. After having experienced for years a number of adjustment processes that led to the exclusion of marginal companies, at the beginning of the 2000s industrial districts undertook a new phase of internal transformation that led them to a process of qualitative evolution based on endogenous formation of new business configurations that include larger-sized businesses as well as new structures, strategies and core competences of firms and districts. In this dynamic prospect of industrial districts, firms may assume a leadership based on their orientation to innovation rather than on routines. The redefinition of district boundaries represents an opportunity for leader firms and, simultaneously, a threat to the survival of more marginal businesses that work as suppliers. Small firms cannot compete with foreign companies on the same ground because of the large competitive gap. In some Eastern European countries the cost of labour is ten times lower compared with local prices; simultaneously, in many sectors exposed to competition – such as metallic products and the more traditional fashion industry – strategies to innovate products and processes are not feasible because these types of production do not offer significant margins for improvement vis-à-vis rivals (Unioncamere, 2003). The regional government of Emilia-Romagna drew up its Three-Year 2000–2003 Plan with the purpose of overcoming that type of planning. It did not promote the application of law 317/1991 in industrial districts; however, it did propose an action (Measure 5.1) to improve the local systems. This Plan proposed the integration of public institutions and universities alongside firms. Notwithstanding this, it is significant that no Provincial Administration, to which the intervention was directed, has used any of these effective innovative measures (Poma, 2003). Abandoning the old concept of industrial districts, the regional government is now reforming its own development project through a set of interventions addressed to accelerating technological and scientific development. These actions include the valorization of old and prestigious universities that had not been previously able to create a systematic relationship with the industrial sector, and actions targeted at promoting the growth of new research-based industries.

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2. Industry trends in Emilia-Romagna The ‘Emilian model’ was characterized by the strong interaction between businesses and institutions; in this it was different from more general industrial aggregations, called clusters. Time marked institutional and social limitations and the connected economic risks of this model. In particular, it was argued that an economic system bound to local society could suffer the process of aging of local communities. For this reason, the system had to promote growth either by means of a massive decentralization to other areas (essentially outside the European market) that were not sharing the same social capital, or through important waves of migration from outside Europe that could help building a new and different civil society (Bianchi, 1997). The industry profile in Emilia-Romagna (apart from the chemical productions in Ravenna and Ferrara) implied the risk of concentrating production in specific low-tech and/or traditional sectors. However, these sectors showed remarkable innovative vitality in both products/markets and process/organization; in this way, after nearly 30 years, Emilia-Romagna’s industrial profile exhibits continuity with the initial stylization of the model as well as the phenomenon of discontinuity; these latter include the novel presence of large companies that have become world leaders in large-size segments of production, as well as the presence of multinational companies that bought out old businesses localized in expanding clusters. The stylization of the Emilia-Romagna’s industries that described this system as able only to create incremental process innovation should be partially reviewed. The 1990s reorganization introduced substantial process innovations through the use of electronics which, in turn, produced important product innovations that led local industries to be able to elaborate customized products (predominantly machinery) for their clients (Regione Emilia-Romagna, 2002). In 1999, the businesses groups in Emilia-Romagna included fewer than 13 000 firms; this included firms controlled by other firms or controlling other firms (with shares of over 50 percent of the firm’s capital). With reference to stock companies, one firm out of four is part of a group; about 60 percent of the workforce and of turnover is attributable to companies that control or are controlled by other companies. Resorting to new forms of organization does not wear out with the exchange of share capital. All those companies bound by participation are linked in less formal networks with suppliers and sub-contactors that are equally diffused in this region. Outsourcing and spin-off are examples

Laura Ramaciotti

39

of ties that are seldom formalized through capital share exchange; however, these ties imply a strong dependence between firms whose growth strategies are closely related (see Table 2.1). The new local production system is characterized by the presence of one or more leader companies with a dense network of small and very small sub-contracting companies. Therefore, this type of organization has a large enough group dimension (both economically and strategically) to have an active role in the market. In some specialized nodes of the network (not necessarily leader companies) research and internationalization activities are concentrated; these nodes may have responsibility to promote and spread innovations and foster international relations. Although firms work in the global market, the network maintains powerful local roots. This ‘organized network’ does not represent the best solution for every sector or for every company. The risk of extinction in traditional sectors is particularly high because innovative products and processes are not the key competitive factors and the smallest firms are bound to one purchaser only. The tendency seems to indicate that economic expansion will not spread to all economies, but only to those that have the ability to Table 2.1 Small and medium-sized industries’ distribution in Emilia-Romagna based on relationships with other firms, 1999/2000 (values in percentages)

As a supplier As a work customer As a service customer

Yes

No

44.8 37.1 24.5

55.2 62.9 75.5

Source: Unioncamere survey – Istituto Tagliacarne, 2003.

Table 2.2 GDP formation per sector

United States Germany Great Britain France Spain Italy Emilia-Romagna

Agriculture

Industry

Services

2.0 1.0 1.7 3.3 4.0 3.2 4.0

18.0 28.0 24.9 25.7 28.0 29.1 34.1

80.0 71.0 73.4 71.0 68.0 67.7 61.9

Source: CIA data processing Unioncamere Emilia-Romagna, World Factbook 2002.

40


innovate and invest in the production and commercialization of highly technological products. There is a correlation between exportation and the high technology content of products. Markets reward goods that are developed in hi-tech sectors and that incorporate high technologies. Industrial districts’ specialization in traditional sectors is well known given their poor participation in sectors that involve high economies of scale and high technology. The Emilia-Romagna region, as well as most European regions, is suffering from insufficient diffusion of new technologies in both creation and production activities. Since the sectors that produce information technologies are those with the highest productivity growth, the different sector composition of production may have relevant effects on productivity. It is interesting to note that in the second half of the 1990s the only European countries with a high productivity growth have been Ireland, Finland and Sweden, where the production of technology makes up a relevant proportion of value added and occupation. This gap in technology production is an obstacle for the growth of Europe and, even more, of countries such as Italy which excel in sectors intensive in unskilled labour and which present weaknesses in high technology sectors. The entrepreneurial structure of Emilia-Romagna is the following: over 400 thousand firms; one firm per ten inhabitants; 58 percent are one-man businesses; over a third are handcraft businesses; 94 percent have less than ten employees. Despite this unfavourable business picture, the number of companies is in constant growth particularly in advanced services and in constructions. In 2003 for the first time the number of firms operating in constructions overtook the number of manufacturing firms. During the years spanning 1995 to 2001 the reduction in the number of manufacturing firms did not determine a reduction of value added (Table 2.3). On the contrary, the value added in the manufacturing sectors increased over time. The reasons are to be found not only in the process of transformation that led companies to organize themselves within specific legal frameworks (as demonstrated by the growth of stock companies) but also in the development of the ‘Emilian Model’ based on both formal networks (e.g. ‘formal groups’) and informal networks (e.g. districts and sub-contracting practices) that permitted smaller firms to obtain significant benefits (Unioncamere, 2003). In Italy, the investment in research and development is still below the European average (less than 1 percent of GDP compared to the European average of 1.8 percent). Over 54 percent of the total national investment is realized by large companies. Expenditure is concentrated in

Table 2.3 Number of active firms in Emilia-Romagna and value added (millions of euros, constant values 1995) 1995 Companies

MANUFACTURING INDUSTRY – Food industry – Textile and clothing industry – Tan industry – Paper manufacture and publishing – Cokery, refinery, chemical, pharmaceutics – Minerals non metal – Metal and production of metal products – Mechanics – Other manufactures BUILDING

2001 Value added

Companies

Fluctuation % Value added

Companies

Value added

59.825

21.408

59.043

23.322

−1.3

8.9

7.984 10.408 1.556 2.876 694 2.024 11.575 12.885 9.823

2.878 2.059 351 1.062 1.264 2.652 2.896 6.401 1.845

8.440 8.698 1.238 3.040 673 2.029 12.544 13.076 9.305

2.821 2.090 211 1.256 1.004 3.011 3.308 7.545 2.076

5.7 −16.4 −20.4 5.7 −3.0 0.2 8.4 1.5 −5.3

−2.0 1.5 −39.9 18.3 −20.6 13.5 14.2 17.9 12.5

41.135

3.533

55.554

4.696

35.1

32.9

TRADE

102.553

11.143

98.252

11.675

−4.2

4.8

HOTELS, RESTAURANTS, SHOPS

122.278

2.937

118.419

3.511

−3.2

19.6

20.410

5.260

19.773

6.217

−3.1

18.2

6.535

4.405

8.793

5.301

34.6

20.3

29.346

11.829

40.857

14.062

39.2

18.9

300.977

69.839

326.453

78.282

8.5

12.3

TRANSPORT, STORAGE, COMMUNICATION CREDIT ADVANCED SERVICES TO BUSINESSES TOTAL ACTIVE COMPANIES (excluding agriculture)

41

Source: Processed by Unioncamere, data from Movimprese and ISTAT data.

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Northern-central Italy (Lombardy and Piedmont) while in EmiliaRomagna results are slightly lower. The reason for this is to be found in different productive structures. In Emilia-Romagna, small to mediumsized industries predominate whereas surveys carried out confirm the close correlation that exists between the diffusion of innovations and the R&D expenditure on the one hand and the size of the company on the other. Regarding personnel in R&D, data confirm that regional firms have good innovative capacity and a substantial quota of professionals in research (8 percent of the national total). Emilia-Romagna’s population represents less than 7 percent of the Italian population and its productive structures have few big companies; notwithstanding this, some indicators result particularly significant. The number of workers in R&D is noticeably higher than in other regions with comparable productive structures and dimensions as in Veneto and Tuscany. If personnel in R&D is considered, its number is clearly higher. This applies also to the expenditure in R&D. The high number of R&D personnel within firms (that complements the personnel operating within universities and public companies) represents a point of strength for regional competitiveness. In 2001 Emilia-Romagna spent 1.15 percent of its GDP on research, behind Lazio, Piedmont, Friuli-Venezia-Giulia and Lombardy. In terms of researchers, in Emilia-Romagna there are 3.7 researchers per 1000 inhabitants, a value that is higher than those registered in other regions, except Lazio and Piedmont. The Italian average is 2.8 researchers per thousand inhabitants, compared with 5.4 in the European Union, 6.2 in France and 6.4 in Germany. In the Emilia-Romagna region the productivity in R&D has increased over recent years. In 1998 Emilia-Romagna realized over 15 percent of total registered patents for industrial inventions in Italy, amounting to 1359 patents in constant growth over the years. In 1998 regional technology exports showed an increase of 23 percent against a national drop of 9 percent. Although Emilia-Romagna lacks big companies and has few structures for public research, it counted for only 5 percent of the revenues for technology sales, yet alone invoices more than the rest of the north-east of Italy. Intense innovative activity is also due to the fact that firms in Emilia-Romagna efficiently use the laws on incentives for innovation. Regarding the laws which support product innovation through R&D Emilia-Romagna absorbed 14.4 percent of national resources in 1998 and 16.2 percent in 1999, much more than what they absorbed from the laws that finance process innovation and building of factories. Analysing the disposition of research and innovation in different

Table 2.4 Personnel and cost of intra-mural R&D. Italian regions in 2001 REGIONS

Personnel in R&D

Public Admin.

Piedmont – V. d’Aosta Lombardy Trentino A.A. Veneto Friuli V.G. Liguria

University

Firms

Total

Cost for R&D (thousands of euros) Numbers per 1000 inhabitants

Total

% of GDP

1077 3345 536 1063 656 956

3093 6660 484 3677 1928 1483

13 853 18 691 849 4215 1475 2124

18 023 28 696 1869 8955 4059 4563

4.09 3.16 1.99 1.98 3.42 2.81

1 832 926 3 011 216 143 026 686 691 348 477 331 132

1.71 1.22 0.54 0.62 1.24 0.89

Emilia Romagna Toscany Umbria Marche Lazio Abruzzo – Molise Campania Puglia Calabria – Basilicata Sicily Sardegna

1614 1839 198 223 13 424 263 1704 963 432 929 543

5528 5159 1696 1300 8331 1607 6254 2767 1441 5676 1785

7704 2922 419 915 5795 1184 2555 947 358 996 269

14 846 9920 2313 2438 27 550 3054 10 513 4677 2231 7601 2597

3.72 2.80 2.76 1.66 5.21 1.90 1.82 1.14 0.84 1.50 1.57

1 229 510 886 668 138 240 177 685 2 549 523 226 990 752 927 318 471 153 410 602 180 183 397

1.15 1.07 0.81 0.56 2.07 0.80 0.93 0.56 0.43 0.85 0.69

TOTAL

29 765

58 869

65 271

153 905

2.76

13 572 469

1.11

North Centre South

9247 15 684 4834

22 853 16 486 19 530

48 911 10 051 6309

81 011 42 221 30 673

3.14 3.79 1.47

7 582 978 3 752 116 2 237 375

1.14 1.47 0.75 43

Source: Elaborated by Unioncamere on ISTAT data.

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territories within the region we find evident disparities. For example, in the number of patents deposited in 1998, the total national number was 5150 and Bologna was in first place with 2048 patents, whereas Ravenna was last with only 162 patents. Although motivated by a different attitude towards innovation, such disparity is also due to the different stock of companies (27 000 local to Bologna and 10 000 to Ravenna). This trust towards structured innovation emerges from R&D data, where Emilia-Romagna has a positive growth tendency, in terms of both expenditure and personnel; the latter is higher than the national average (growing from 7.8 percent in 1996 to 9.5 percent in 1998 on the total national personnel; from 7.1 percent to 8.1 percent on the national total expressed in terms of expenditure in intra-mural R&D). The number of industrial patents is valued at 1519 in Emilia-Romagna in 1998 (1991 = 100), while on a national level it is steady for the whole period (101.6 in 1998, 89.1 in 1999: Regione, 2002: 25). Demand for innovation by firms in Emilia-Romagna proves their interest in using the national laws on incentives for innovation. In 1999 firms in the region received 17.4 percent of these grants-in-aid according to the law 140/97 (a tax credit for costs of research and development), 12.7 percent of funds in applied research, 21.5 percent of funds for innovative technology (law 46/82). Since 2000, research funds under the law 140/97 were transferred to the region’s district office where these funds were put into a Fund for Productive Activities that encouraged firms to double their applications for research projects. However, the innovative potential of Emilia-Romagna is still bound to innovations within traditional sectors where the regional innovation system supported its existence and is centred on old large universities and national research centres (CNRs). Despite this, the extraordinary scientific structure did not generate new business groups focusing on research that may contribute to the regeneration of the regional industrial system. This difficulty in creating a positive spin-off from research to production is not, however, just an Emilian problem, but a national and European problem that highlights the ‘European paradox’: when measured in terms of academic importance, the results of university research display significant levels and, at times, are excellent; however, when measured in terms of productive spin-offs these results are marginal.

3. Research trends in Europe Within Europe differentiated situations outline distinct viewpoints (EC, 2002: 20). Comparing the amount spent on R&D with GDP per capita in

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European countries, a positive relation between the level of income and the funds spent on research can be found. Four groups of countries with distinct strategies can be indentified: 1. Finland and Sweden are high income countries that heavily invest in research (around 3.5 percent of their GDP), even more than the United States and Japan; 2. Greece, Portugal and Spain are low income countries that proportionally spend less on research (between 0.5 and 1 percent of their GDP); 3. France, Germany, UK, Belgium, Holland and Denmark, the central European countries, spend less than Japan and the US, though approaching the US figures (between 1.8 and 2.5 percent of GDP); 4. Ireland, Austria and Italy, although they are among the richer economies, spend as little as the lower income countries on research (between 1 and 1.8 percent of the GDP). With regard to Italy the effects of continuous innovation are underestimated in those figures as are the informal ties that involve university teachers. However, despite this, in the context of Italy the European tendency of low investment in research is more grievous. Analysing the relationship between European research in the public and private sectors, we find that a country’s position (taking into account the finance spent on R&D and its GDP) is principally due to the existence of a number of innovative regions, despite the significant differences that may exist across regions in this country (EC, 2002: 28). It is demonstrated that the driving force in research does not only come from the money spent on research but also from its territorial concentration, economic dimension, numbers of researchers, scale and variety of laboratories, previous researches on whose bases new researches are developed, introduction of researchers and laboratories into the international scientific community and trans-national research network. Over time an approach to ‘national innovation systems’ has been developed (Lundvall, 1992, Nelson, 1993). This development tends to redefine itself at a local level, and to find its place in a union of regional research centres that activate new local industries (Cooke and Morgan, 1998, OECD, 2000: 18). The concept of a National Innovation System is developed to signal how different institutions intertwine at the national level through the generation and the diffusion of innovations. This concept has only been partially used to identify local networks of R&D supporting the generation and diffusion of industrial innovations (Quadrio Curzio and Fortis, 2002).

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In countries where less funding is spent on research, the presence of diffuse industries in traditional sectors tends to characterize a more limited demand for research from the private sector than in countries that can rely on large companies that are in the position to demand research as well as to value and acquire intangible assets (OECD, 2000: 45). These factors (that are linked to poor mobility of researchers within universities, public bodies and industry) determine not only a more limited process of technological transfer but also a European limited tendency to generate new industrial aggregations originating from scientific research, however found in countries with a strong entrepreneurial thrust. In particular, research spin-offs as well as those from high-tech industries have limited or marginal results compared with broader industrial dynamics (OECD, 2001; IPTS, 2001).

4. The research system in Emilia-Romagna The research system in Emilia-Romagna is based on four old universities, among which is the University of Bologna, which has recently opened subsidiaries in other cities in Romagna as well as in Piacenza (the ‘University Cattolica’). In addition to these universities there are the National Research Council (CNR) and the Italian Institute for new technologies, energy and the environment (ENEA). The universities in Emilia-Romagna have a long history, i.e. Bologna and Ferrara first, then Modena (now called Modena and Reggio) and Parma. The data on the number of researchers operating in Emilia-Romagna are an important indicator of the large scale of these universities and of the strong diversification of skills (see Table 2.5). In 2000, an analysis per subject conducted on lecturers and researchers working in Emilian universities showed a massive presence of personnel in scientific areas with an average of nearly 70 percent and a peak of 80 percent in Ferrara. In Emilia-Romagna nearly 5000 university lecturers and researchers operate and represent 10.2 percent of the country’s total.2 Together with the universities and national research bodies there exists a strong presence of private labs and private research centres. Finally, in the last few years the network of business support centres has been consolidating and increasing; this trend represents a successful experience at the national level. The centres for innovation formation and for technology innovation currently operating number 38. They are present in the whole regional territory and operate coherently with territorial vocations, in sectors such as mechanics, textile/clothing, ceramic,

Laura Ramaciotti Table 2.5

Scientific Social Classical Total

47

Lecturers and researchers per subject area in Emilia-Romagna, 2000 Bologna

Parma

Modena-Reggio

Ferrara

Total

%

1711 449 586 2746

732 136 14 982

526 119 12 657

492 64 53 609

3461 768 765 4996

69.3 15.4 15.3 100

Source: MIUR site, 2002.

Table 2.6 In Emilia-Romagna 80 applications were presented in these sectors Priority

Bologna Ferrara Modena-Reggio Praccaza Parma TOTAL

1. Genomics 2. Inform. soc. 3. Nanotechnology 4. Space 5. Food 6. Ecosystem 7. Government Others Total

6 6 2 2 3 11 2 1 33

2 2

1 5 6

5

3 2 2 8

2

15

7

2 2 4 1 2 3 1 2 17

11 20 12 3 8 18 5 3 80

Source: Revised on the basis of ASTER, 2002.

footwear, agricultural machinery, animal and vegetable production, food processing, constructions, and certification and plastic materials. An analysis on the capacity of the regional innovation system to prepare scientific proposals for research programmes has been conducted by ASTER3 (see Table 2.6).

5. Regional laws and agency for innovation In recent years a new view has consolidated around the factors and mechanisms that drive firms’ production systems to reach higher levels of competitiveness, efficiency and, in particular, systemic, continuous and diffuse innovation.4 From the literature it is evident that production systems of small firms risk being trapped (if they do not continuously strengthen their acquisition of new knowledge) in the path of hyperspecialization in predominantly traditional sectors and find it difficult to reconvert their accumulated knowledge and integrate it with new

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knowledge (because of their specific role) when they are strongly pressed to change. The new role of advanced and innovative regions is to contribute to the development of knowledge as a competitive regional factor. For those regions characterized by small firms it is particularly important that:

• their productive systems increase their internal complexity, leading towards horizontal diversification and vertically integrated technological knowledge that can bind together different productive sectors; • strengthen and consolidate connections with systems of codified knowledge in the region or with external bodies such as universities, research centres, specialized schools; • these sources of advanced knowledge promote the creation of new firms as well as the generation of new firm systems based on higher knowledge content and operating in innovative activities. The ambitious goal is to create effective channels that transfer technology towards a productive system and to promote entrepreneurial innovation in a way to generate extensive impact on knowledge diffusion and innovation in the whole region’s economy, thus accelerating changes and technological development. This should happen when the following lines of action are undertaken: 1. building an open territorial network and coordinating structures dedicated to applied research in the industry and to transfer of technology; 2. promoting new high-tech firms and high research contents, particularly in spin-offs deriving from research; 3. forming new innovative professional figures and/or updating leading professional figures with new technologies. The strategic choice of the Emilia-Romagna Region is to push the economic system towards a knowledge economy base that has demonstrated substantial capacity to take in new technologies and to transfer these technologies into advanced productive assets. To the traditional vision of regional economy as a network of relationships between production actors (a consolidated view in the collective perception of regional development) one must add the network of research actors in order to intensify the interrelation between complex circuits of production and knowledge. In this way the excellences of the region could be strengthened insofar as these areas of excellence and their driving force could be deepened

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and extended to the whole regional productive and bureaucratic system. Moreover, this may also help to extend the frontier of knowledge and transform it into new productive intelligence. Rewarding the mix between the research network and the production network signifies singling out the scientific and technological multipliers of local development so as to be able to realise interventions (depending on the type of intervention justified by law) that accelerate the transformation of the research base into innovation and widespread knowledge. Table 2.7 shows some of the possible intersections between the regional production system and the applied research system in Emilia-Romagna. Other combinations could be created on the basis of specific projects that cannot be anticipated. The main economic areas are determined, on the one hand, by the intersection between mechanics and automation, motor engineering, environment and health (including biotechnologies and genomics) and, on the other, by micro and nanotechnologies, advanced multimedia and distributed computer science. An innovation factor that can guarantee the continuity of the Emilian model and its regional production system can be generated by the synergies that may be created between the scientific academic system and the regional private sector. An example is the case of the academic spin-offs and the creation of high-tech firms derived from research and promoted through the ‘Spinner’ program that is explained later in this chapter. These companies represent casual events tightly linked to opportunities that the academic sector has managed to seize recently as a result of the interconnection between these two sectors. To make the regional socio-economic system grow alongside the creation of these new types of companies, the creation of new interconnections needs to be stimulated; this would maintain a more flexible production fabric.

6. The creation of new companies based on research In this framework, sustaining universities and public and private research structures, and setting up spin-offs based on research become a priority. The instrument is called ‘Global Subsidy’. It is a form of financial intervention based on the rules established by the European Union for its Structural Funds. These funds are used preferably to promote local development projects; therefore, they are strongly rooted in the local territory and in its distinctive conditions. The reasons for the regional government of Emilia-Romagna to use this instrument (the European Social Fund used it for the first time in Emilia-Romagna) are linked to

Relevant socioeconomic areas

Enhancing technologies

X

X

Source: Author’s elaboration.

X

Micro and nanotechnology Microelectronic and sensor intelligence Robotics and advanced systems of planning Laser optoelectronics Electronics, realizing systems and network control

Advanced multimedia information and distribution

Fluid-dynamic and combustion technology

Separated processes and chemical technologies and electrochemical

X X X X X X X

X

X X

X

X X

X

X

X X

X

X X

X

X

X

X X X

X X X X X X X

X X

50

X

Structural and functional material technology

Mechanics, automation Information and multimedia Medical and precision Design/ Engineering Chemistry and plastics Ceramics and construction Food Furniture and fashion Environment Energy Health Arts Biomedical Technologies

Biotechnologies

Table 2.7 Mixes between the research network and the production network

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the strong territorial values of the actions that are required to pursue the expected objectives. Among them are the measures D3 (Development and consolidation of entrepreneurial abilities giving priority in new areas of employment) and D4 (Improving human resources in areas of research and technological development). It is therefore important to underline that at the territorial level a variety of interventions should and could be integrated in appropriate environments promoting consensus with the objective to multiply the positive effects of public intervention and so to confirm the region’s central role in interventions that valorize knowledge and qualified human resources. Spinner’s Global Subsidy operates with a networking approach that takes place through partnership created by the region’s universities and research centres. They pursue objectives of integration and complementarity with ongoing and planned actions and instruments operating at local, national and European level. They also try to avoid duplications of effort. Apart from European programs, national and regional laws, a series of initiatives promoted by public and private actors (e.g. universities, research centres, business associations, local development agencies, training centres, and business incubators) are being set up in the territory, and in particular in the area of new innovative entrepreneurship support. The three guidelines that Spinner Global Subsidy follows are:

• technology transfer interventions that support researchers and their projects when their point of reference is a working company operating either within or outside the regional contest; • interventions to support the creation of new firms by university researchers and research centres; • scholarships and fellowships for thesis that may generate effective spillovers in production. One element that characterizes this activity is the structuring and management of eight offices for territorial intervention (‘Spinner Points’) localized within university premises and research centres that operate within the region. These Spinner Points have guaranteed a constant presence in the territory and have been able to identify the crucial needs of the system in order to structure specific activities that respond to the needs of receivers while working in agreement with the universities and referred research institutes. From May 2001 to December 2002, 1702 people requested assistance from the network to develop their projects; 1033 of them presented a project of which 616 were financed. 55 percent are young people aged

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between 25 and 29 years, for the most part men (63 percent) of which 68.3 percent hold a first degree. Among the approved projects dealing with technology transfer activities, nearly 50 percent are located in the electronic sector (computer science, mechanics, industrial automation) which represents the heart of this regional industrial structure. It is also significant that 18.6 percent is based in the area of ‘life science’ (agroindustry, food processing, biotechnologies, pharmaceutical and electro-medical); 11.5 percent are in industrial chemistry and new materials. These indications show that a new phase of adjustment is taking place, which requires significant support to adapt the regional production structures to the new global competition. An indirect confirmation comes from the large volume of projects explicitly directed to innovation in organization. A further proof is based on 48.7 percent of new approved projects (firms) that target the realization of studies, researches and consultancies for industrial sectors on how to develop joint activities between universities and firms that may help academic research insofar as they also support the private sector in specific ways, and in particular within the ways that are relevant to this strongly diffuse and articulated regional production system. The analysis of 245 firms originating from the Spinner project, that represent actions of technology transfer, shows the significant attention that has been paid to the private sector (two third parts of the interventions), and to regional subjects (two third parts of the interventions in territorial terms). Academic spin-offs are usually small and medium-sized firms with limited company responsibility. The majority employ between 3 and 15 workers or collaborators6 and between 3 and 7 partners. Within them there are lecturers who, during the start-up phase, both scientifically and commercially support the business team. A few are other industrial and banking sectors involved in the project. The majority of these firms are service companies or these offering sub-contracting within manufacturing in Emilia-Romagna, in particular within the electronic, mechanic and agricultural sectors (see Figure 2.1). Particularly interesting are the data related to the emergence of new sectors such as biotech and genetics. Activities refer above all to studies and consultancy on environmental, artistic and industrial issues. In the start-up some spin-offs do not involve production activities, whereas these may take place in a second phase when venture capital is needed and can effectively be found. In the case of high-tech firms, risk depends on a poor organization and management because attention is paid exclusively to technological aspects. In general the Italian spin-off model (and in some cases the European)

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Recipients involved in Spinner actions 5.4%

Agricultural industry Food industry Environment Pharmacology chemistry Industrial chemistry Building andrepair Electro-medical Electronics Computer science Mechanics Multimedia Nuclear Organization Consulting services Services for computer science and telecommunications Studies, research and consulting Studies, research and consultancy on environmental issues Studies, research and consulting in the goods sector Studies, research and consulting in industrial sector Textile industry Transportation

Per sector

1.4% 4.1% 2.7% 2.7% 4.1% 2.7% 9.5% 2.7% 6.8% 4.1% 1.4% 2.7% 2.7% 5.4% 4.1% 10.8% 6.8% 16.2% 1.4% 2.7%

0.0

2.0

4.0

6.0

8.0

10.0

12.0

14.0

16.0

18.0

(%) Figure 2.1

Company ideas

Recipients involved in Spinner action Per sector Agricultural company Food industry Environment Industrial automation Biotechnology Pharmacology chemistry Industrial chemistry Building and repair Electro-medical Electronic Computer science Mechanics Nuclear New materials Organization Services for computer science & telecom Transportation 0.0

1.4% 1.4% 0.5% 1.9% 9.1% 4.3% 9.6% 0.5% 1.9% 18.3% 15.9% 13.5% 1.0% 2.4% 17.3% 0.5% 0.5% 2.0

4.0

6.0

8.0

10.0

12.0

14.0

16.0

18.0

20.0

(%) Figure 2.2

Technological transfer projects

is different from the American model for the more contained level of risk and propensity to take risks. In particular, spin-offs from hi-tech present barriers to entry linked to the purchase of expensive equipment and machinery; for this reason for a first period they may want to locate within their local university to be able to utilize such instruments. During the start up phase the market targeted by spin-off enterprises is predominantly local or national, whereas it tends to increase in the consolidation phase. The main problems refer to access to finance, and to commercial management; the latter is often tied to lack of specific skills

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Recipients involved in Spinner action Impact analysis: Approved plans for technological transfer (TT)

208

Number of companies involved in TT

200

Number of firm cases

245 69.4%

Regional 26.1%

National Abroad

4.5%

18.0%

Public Administration Capital company

63.7% 18.4%

Other 0.0

10.0

20.0

30.0

40.0

50.0

60.0

70.0

80.0

(%) Figure 2.3

Technological transfer projects

within the business team in the start-up phase. The evaluation of the market segment in terms of the real demand may also constitute a significant problem for high-tech and academic spin-offs (Baroncelli, 2001).

7. Can universities be the new promoters of regional development? In recent years there has been an increase in the awareness of the competitive challenges that the so-called ‘Emilian model’ (which has been able to maintain a satisfactory competitiveness up to now) will face in the near future and that will need improvement in the technological and organizational innovation capability of local economic systems. There is now a consensus that the capacity to implement this objective relies on the cooperative development between research centres and firms and the increase in scientific and technical knowledge within the work environment and across firms. In Emilia-Romagna, alongside an extremely versatile productive structure, there is a concentration of skilled professionals and of large scientific and training infrastructures that are

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represented by the university system and public and private research centres. This system is among the most developed at the national level. The re-orientation of the region’s industrial policy makes it possible to better identify the meaning of actions for technological upgrading; the latter implies the creation of new knowledge related to the integrated system ‘research-innovation-production’ that supersedes the former model of the industrial district. The process of technological upgrading also includes the creation of specific organizational knowledge that promotes firm creation in R&D activities thanks to a favourable environment for business development. This re-interpretation sheds light on the strategic importance of increasing the capacity of scientific absorption by users (both people and firms) and not only of increasing the capacity of universities and research centres to transfer knowledge. In other words, the definition of a ‘New Emilian Model’ must include universities and research centres in structured relations within the production system. However, the creation of intermediate subjects that act as interfaces between organizations with different objectives and aims is required to be able to realize this objective. If universities produce research and knowledge at the international level, positive externalities may be produced for the local economy. This depends on communication instruments that may operate between the different actors, and that are especially important if firms are small, because they are not in a condition to promote a demand for codified research that implies the acquisition of patent rights or long-term research agreements. The analysis realized on the first interventions in the new phase of regional politics shows that the capacity to formulate major research projects still relies on university structures and that a channel of communication and integration between research and production can be created through research-based spin-offs or other structured actions targeting technology transfer by means of direct and explicit university (structures) involvement. In this case, no matter the numbers of new employees and the contribution to creating new firms in already dynamic areas, these cases become important because they create a new network of private parties that act as intermediaries between the public research sector and the private sector.

References ASTER (2002), Activity Report 2002, Bologna. Baroncelli, A. (ed.) (2001), Percorsi imprenditoriali generati nell’Università. Il fenomeno ‘spin off accademici’, Clueb, Bologna.

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Bellini, N., Giordani, M.G. and Pasquini, F. (1997), ‘The industrial policy of Emilia Romagna: the business service centres’, in Leonardi and Nanetti, op. cit., pp. 171–86. Bianchi, P. (1997), ‘Emilia Romagna: problemi e prospettive’, in Finzi, R. Storia d’Italia. Le regioni dall’Unità ad oggi. L’Emilia Romagna, Torino, Einaudi editore. Bianchi, P. and Gualtieri, G. (1990), ‘Emilia Romagna and its industrial districts: the evolution of a model’, in Leonardi and Nanetti, op. cit., pp. 83–108. Callan, B. (2001), ‘Generating Spin-Offs: evidence from across the OECD’, in OECD, 2001, op. cit., pp. 14–55. Clarysse, B., Heiman, A., Degroof, J.J. (2001), ‘An Institutional and Resourcebased Explanation of Growth Patterns of Research-based Spin-offs in Europe’, in OECD, 2001, op. cit. Cooke, P. and Morgan, K. (1998), The Associational Economy: Firms Regions and Innovation, Oxford University Press, Oxford. Cossentino, F., Pyke, F. and Sengerberger, W. (1997), ‘Local and Regional Response to Global Pressure: the Case of Italy and its Industrial Districts’, International Institute for Labour Studies, Research Series, 103, Geneva. European Commission (2002), ‘Benchmarking of National Policies. Public and Private Investments in R&D, Final Report’, Expert group, June, Brussels. IPTS (2001), ‘Corporate and Research-based Spin-offs. Drivers for knowledgebased innovation and entrepreneurship’, European Commission, May, Brussels. Leonardi, R. and Nanetti, R. (1990), The Regions and European Integration: the case of Emilia Romagna, London, Pinter. Ministry for University and Academic Research, www.MIUR.it. Nelson, R. (ed.) (1993), National innovation systems: a comparative analysis, Oxford University Press, Oxford. OECD (2000), ‘DSTI/TIP, 16 Part II: Trends in Innovation and Knowledge Distribution, Paris. OECD (2000), DSTI/TIP, Part III: Firms in Knowledge Markets, Paris. OECD-STI (2001), ‘Special Issue on Fostering High Tech Spin-Offs: a public strategy for Innovation’, STI Review, Special Issue, no. 26, Paris. Piore, M. and Sabel, C. (1984), The second industrial divide, Basic Books, New York. Poma, L. (2003), Oltre il distretto: imprese, istituzioni nella nuova competizione territoriale, Milano, Angeli. Putnam, R., Leonardi, R. and Nanetti, R. (1985), La pianta e le radici, il radicamento dell’istituto regionale nel sistema politico italiano, Bologna Il Mulino. Quadrio Curzio, A. and Fortis, M. (2002), Complessità e distretti industriali. Dinamiche, modelli: casi reali, Il Mulino, Bologna. Regione Emilia-Romagna (2002), ‘Promozione del sistema regionale delle attività di ricerca industriale, innovazione e trasferimento tecnologico, relazione di accompagnamento’, Progetto di legge regionale, Bologna. Unioncamere (2003), Rapporto sull’economia regionale nel 2002 e previsioni per 2003, Bologna. Unioncamere (2004), Rapporto sull’economia regionale nel 2003 e previsioni per 2004, Bologna.

3 Small and Medium-Sized Firms in High-Technology Industries: The Experience of Biotechnology Firms in the United States Stuart O. Schweitzer and Marco R. Di Tommaso

1. Introduction Many nations and regions throughout the world are attempting to promote development of high-technology industries. Firms in hightechnology industries tend to be small and medium-sized, suggesting that industrial policy toward this sector might optimally be different from policies that would be directed toward firms in other industries and sectors. In industrialized economies high-technology industries are considered desirable because it is hoped that they will protect economies from challenges of international trade and employment migration. In addition, research suggests that high-technology industries tend to create positive externalities and support for one another. Conversely, a decline in one of these industries (e.g. biotech) is often associated with declines in others (e.g. computer chips and genetics). In developing economies the benefits of successful hi-tech industries are similar. In addition, development of these industries may attract relatively high-wage jobs from industrialized countries through outsourcing, and also may help retain the country’s brightest people and prevent human capital outflows – the ‘brain drain’. These justifications for promoting hi-tech industries explain why development policy toward hi-tech industries exists in countries that span a wide income range. Industrial policy directed at this sector is likely to be different, however, in the wealthiest and industrialized countries, from those in countries that are less affluent. 57

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New views of the hi-tech sector suggest that its industries tend to reinforce one another (Di Tommaso and Schweitzer, 2004a). These economic spillovers have two implications. The first is that these firms tend to locate near one another in multi-industrial clusters, as they attempt to take advantage of economies of agglomeration. The second is that growth in one hi-tech industry may stimulate growth in other hi-tech industries, and that successful growth in these industries has a synergistic effect, reflecting back upon all industries to increase innovation. Many of our observations pertain to high-technology industries in general, but we look especially at the experience of one particular industry, biotechnology. This chapter draws from analyses that we have done on the biotechnology industry in the United States. We will highlight areas in which the experience of biotech in the United States is likely to be generalizable to other industries and other countries, and also areas where this experience may not be so generalizable. This chapter will focus on three issues.

(a) First, we discuss the comparative size of hi-tech firms. In doing so, we will attempt to better understand why it is that biotechnology and other hi-tech firms tend to be smaller than firms in other industries. A better understanding of the reasons for relatively small firm size will suggest more appropriate policies that might be undertaken in order to promote hi-tech industries. (b) Next, we discuss the clustering phenomenon of hi-tech firms. At first glance, it appears to some that hi-tech clusters are an anomaly, because many characteristics of hi-tech industries, including biotech, have been thought to be inconsistent with the explanations that have been offered for clustering behavior in older, more traditional industries. (c) We conclude with observations on industrial policy toward hightechnology industries and especially biotechnology. We will attempt to differentiate between industrial policies that are likely to be most effective in industrialized countries, and those that might be best adapted to less industrialized countries and regions. We will draw from our observations on firm size, the unique nature of the firms’ knowledge base, and the phenomenon of clustering to point out industrial policies that are best suited to this unique group of industries.

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2. Firm size in high-technology industries High technology industries are those industries that embody a high proportion of intangible, intellectual capital (see Di Tommaso et al., 2004, Malecki, 1997). One of the most striking observations one can make about firms in the high-technology sector is that so many of them are relatively small. There are large firms in the biotechnology, aerospace, computer chip, and dot-com industries, to be sure, but they are few in number. When one looks at the traditional manufacturing sector, the proportion of large firms tends to much larger (Acs and Audretsch, 1990; Nooteboom, 1994). The US Department of Commerce reports that in the year 2000 the average firm in Basic Industries and Materials had 5106 employees, and the average firm in Machinery Manufacturing had 3865. On the other hand, the average firm in the Information and Electronics Manufacturing and Services classification had 3249 employees and the average firm in Nondiagnostic Biological Product Manufacturing (which includes biotechnology) only had 360 employees (US Department of Commerce, 2004). There are several reasons for the predominance of small firms in high-technology industries: (a) their genesis, (b) diseconomies of scale, (c) outsourcing, and (d) risk. (a) The process of creation of hi-tech firms has been discussed by Schweitzer et al., (2004). They note that in the case of biotechnology, firms in the US are often spin-offs from universities and other research institutes. Other industries, such as software, genomics, and electronics, are similar. This spin-off process starts, especially in the US, the UK, and Israel, with a scientist-entrepreneur based in an academic or research setting. But the costs of this enterprise are substantial and there is little prospect of producing income for a substantial period of time. Therefore, these start-up firms need a source of capital for several years. In the countries mentioned, this is achieved by the scientist forming linkages with a venture capitalist. If venture capital is unavailable, as it is in most other countries, other sources of capital must be developed. Possibilities include direct government investment, investment by ‘parent’ firms, and investment by individual private investors. At this early stage, the scope of the firm’s activities is narrowly defined by a single scientific discovery or ‘platform’. The nature of the inputs is entirely intellectual capital, and the output is similarly knowledgebased, rather than a manufactured product. The labor input consists of the founder and a small number of colleagues, often from the same university or research institute. This process of combining intangible

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assets to produce innovation is described in detail by Bianchi and Labory (2004). As the development process proceeds, its complexity increases, requiring more specialized personnel to deal with various aspects of the scientific project. This is likely to increase the size of the enterprise over time, and will certainly do so when the firm matures and begins to develop additional products – but this comes later. In the case of pharmaceuticals and biotechnology, the process of developing a saleable product includes dealing with government regulatory agencies, such as the Food and Drug Administration. The FDA requires extensive testing, first on animals, and then on human subjects, which impose enormous costs on companies attempting to develop drugs for human use. Other hi-tech industries, such as computer chips, telecommunications, and aerospace must cope with the normal activities of product development and marketing, but do not have this additional set of hurdles to overcome. (b) High-technology firms have unique characteristics that lessen the importance of economies of scale that apply to firms in other industries, as suggested by Di Tommaso et al., 2004). It is possible, for example, that in traditional, mature industries, there are ‘diseconomies of scale inherent in the bureaucratic process which inhibits both innovative activity and the speed with which new inventions move through the corporate system towards the market’ (Audretsch and Stephan, 1996: 642). For example, small firms may better compete and innovate than larger firms because of reduced bureaucratic rigidities (Audretsch, 1999). Many examples have been raised in the popular press of the inability of very large firms, such as the American giants, General Motors, Kodak, and Boeing, to compete aggressively in the world market. This size-rigidity relationship is not universal, of course. There are some examples of very large firms that are successful on the world stage (e.g. General Electric). And there are even examples of large firms that have apparently learned to innovate and compete, such as IBM. It is therefore difficult to generalize across industries, and even across firms within an industry, as to economies of scale and the ability of firms to innovate and compete aggressively. (c) Outsourcing has become an important aspect of hi-tech firms. Outsourcing entails creation of linkages between firms, and the shifting of responsibilities from the initiator firm to subsidiary firms. These opportunities arise especially in firms with high intellectual capital content for two reasons. The first, seen in the case of biotechnology, is that the scope of the original entrepreneur-scientist is limited to scientific areas, and academics are often unskilled in other aspects of management, product


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development, testing, manufacturing, and marketing. Information technology also encourages outsourcing in high-tech industries because ideas and intangible assets – the heart of the hi-tech firm – are best able to move through the virtual space of Information Technology (IT). New developments in IT have the dual roles of facilitating outsourcing by initiator firms (creating a demand for outsourcing), and enabling outsourcing firms to exist by taking on specialized functions (creating a supply for outsourcing). Without IT, firms could not easily outsource because they would be unable to communicate their particular needs with potential suppliers and they would be unable to compare alternative offers by outsourcing firms. On the other hand, without IT, outsourcing firms could not function because it would be impractical for firms with only narrow capabilities to exist. Linkages between firms occur along two stages of economic activity: research and product development. Major pharmaceutical companies, for example, seek linkages with small biotechnology firms to do their biotech research. Why these pharmaceutical firms do this is not wellunderstood, but the pattern is clear: Large pharmaceutical companies are successful in traditional biochemistry paradigms, but they discover only a very small fraction of biotech drugs. Apparently traditional pharmaceutical firms find it difficult to conduct basic and applied research in biotechnology themselves, preferring to outsource these functions. Thus, they acquire this knowledge that is produced by small biotech firms. The acquisition process takes many forms, including outright acquisition of the biotech firm, licensing of technology, and joint marketing relationships. Product development of drugs, whether of traditional pharmaceuticals or biotechnology products, is complex, relying upon a large variety of distinct steps as a molecule travels from the basic research stage to a final, marketable product. Many of these steps require expertise and equipment that large firms do not have, and so a large number of subsidiary firms have been created to perform single functions, and the large firms contract with these small, single-purpose firms to accomplish specific tasks. Some firms specializing in outsourcing services address chemical processes such as filtering or separation of isomers. For example, Prozac, the popular antidepressant, was found to work well in only a portion of patients who were taking it. It was then discovered that the molecule comes in two shapes, or isomers, and some patients were only responsive to one of the isomers. By filtering the compound, Prozac’s manufacturer, Eli Lilly, found that they could make a version of the drug that would be more potent to all patients, even those who did not respond well to

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the earlier formulation. This filtering was not done by Eli Lilly, itself but rather by a subcontracting firm that has specialized equipment and knowledge of this process. Other functions that are frequently outsourced in the pharmaceutical industry include development of innovative delivery systems such as skin patches, inhalers, or implantable devices. There are a number of firms that have specialized in this particular function – taking existing drugs and creating a different delivery system for them. The conduct of clinical trials has also become highly sophisticated and complicated, and so even the largest pharmaceutical firms frequently find that it is more appropriate to subcontract the conduct of clinical trials to specialized companies, called Clinical Research Organizations (CROs). Subcontracting firms tend to be highly specialized and, as a result, are small. There may be economies of scale among these firms, but their specialized nature suggests that economies of scope are probably absent. Rather, the contrast between large pharmaceutical firms and their much smaller subcontracting collaborators suggests that they have complementary assets as noted by Malerba and Orsenigo, 2001 and Di Tommaso et al., 2004). (d) Risk is also responsible for the relatively small size of hightechnology firms, compared with their counterparts in more mature industries. A high level of risk would be expected to encourage firms to grow so that they can better withstand uncertainty. If size is a protection against risk, why is it that hi-tech firms tend to be small? An explanation is that and that these firms face even greater risk than their mature-industry counterparts and so economies of scale are greater among high-technology firms. If this is so, then one might expect even greater economies of scale (due to risk) for hi-tech firms than for firms in mature industries, and hence hi-tech firms should be larger than firms in mature industries, and not smaller. The answer is related to the presence of risk. We suggest that activities of hi-tech firms are so risky that their ‘mortality rate’ is inordinately high. This high rate of failure and exit of hi-tech firms is matched by a high rate of entry of new firms. One important aspect of hi-tech firms is their intangible asset base, which creates low barriers to both entry and exit. Not only is it easy for new firms to enter an industry, but it is also easy for firms to fail and leave the industry. This suggests a relatively high level of ‘volatility’ in hi-tech industries, with many firms leaving within any time period, while another cohort of new firms is entering. We call this volatility a ‘life-cycle’ model, and its impact on firm size is dramatic. The model suggests that the small size of firms in a hi-tech


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industry is due, not to characteristics of the firm, but rather to their ‘death’ at a young age, before they have had a chance to grow. There is considerable evidence suggesting the validity of this life-cycle model. The capital market, for example, shows that it is difficult for startup hi-tech firms to obtain capital. The usual source of capital in the US and the UK is venture capital, which extracts a high equity interest to compensate for the high risk involved.

3. Clustering as a response to risk and changing technology in high-tech industries We have suggested that the small size of hi-tech firms is a consequence of their relatively recent formation and the high degree of risk to which they are exposed. In other words, the small size and narrow focus of hi-tech firms make them vulnerable to failure. The causality also goes in the other direction, as well. Hi-tech firm vulnerability leads to rapid turnover of firms creating their small size, when compared with firms in other more mature industries. One measure that hi-tech firms take to reduce their vulnerability is to form strategic alliances with other firms through clusters. Ideally these clusters will allow the firms to gain some of the economies of scope and scale, without having to wait until they actually grow in size. It is likely that response to risk is one of the reasons why hi-tech firms in the United States are so often observed to be located in clusters (Schweitzer et al., 2004), is this response to risk. The authors found that most biotech firms in the US are located near one another, in clusters. Furthermore, they found that the clusters tended to be located in close proximity to research universities and institutes, rather than population centers and colleges and universities, in general. The literature on clustering is large and varied. Schweitzer and Di Tommaso (2003), however, have recently suggested two main themes. The first is that specific factors draw particular firms to particular localities. The second is that clustering produces synergies among firms. (a) The location of natural resources was the rationale for the earliest industrial agglomerations. In the eighteenth century and before, economic geography was drawn by the effort to find ways to move raw materials from their sources to production locations where they could be combined with capital and labor to make final products. Because of difficulties in transporting raw materials, industries used to cluster near the sources of those raw materials (Leamer and Storper, 2001). In the ‘old economy’ these factors were ease of transportation, location

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of either supply or product markets, or natural resources (Losch, 1940; Weber, 1909). (b) Synergies from agglomeration are the second theme in the literature. It focuses on economies firms can realize by locating near one another. Firm agglomeration per se offers advantages because of physical proximity. Pioneering papers were focused on ‘market potential’ that tends to be higher where firms agglomerate (Harris, 1954). Other studies recognize the importance of competition at the local level (Porter, 1990). In general, to be close to other firms that are similar is useful, but the proximity to firms that are doing other specialized and complementary activities can also offer benefits. Clustered firms have access to 1) a local market for skills that reduce specialized labor search costs, 2) a local specialized supply of raw materials, equipment, and services, and 3) technical and market flows of specific knowledge (Becattini, 1987; Krugman, 1991; Marshall, 1890). Firms choose a particular location because they can exploit the positive externalities produced by other firms. Firms wish to exploit economies that tend to be characterized by non-rivalry and non-excludability and that are part of a common pool from which any actor can freely draw (Audretsch, 1998; Audretsch and Feldman, 1996; Cooke, 2001). Furthermore, clustered firms can enjoy benefits from the reduction of transaction costs (Williamson, 1975), resulting from the reduction of search costs by consumers (Prevezer, 1995), or from the possibility of integrating different complementary functions (Di Tommaso and Rabellotti, 1999). It is important to recognize that, in general, this advantage has a cumulative and self-reinforcing nature (Arthur, 1990; Harris, 1954; Krugman, 1991). It is also noted, however, that diseconomies can be produced by an excessive agglomeration of firms within the same place, which Krugman refers to as ‘centrifugal forces’ (Krugman, 1991; Swann et al., 1998). Clusters can take several forms. One is the physical proximity of firms to one another. In these agglomerations economies emerge, either directly or indirectly. Firms benefit directly from agglomeration through the possibility of collaboration – a kind of vertical integration of function. Biotech functions that might be done by collaborators, rather than the biotech firm itself, include manufacturing, testing, and marketing. Indirect benefits of agglomeration also arise as the markets for inputs and outputs work more efficiently with more firms acting together. Suppliers of various inputs can more efficiently offer their products to groups of potential buyers, and the same applies to employees. Firms that hire similar kinds of workers will find that the labor market works to their


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advantage if they are in proximity to one another. Similarly, it is easier to market one’s output if one is part of a group of producers. Those demanding the output know to come to a particular area because they will find multiple firms that are offering similar outputs. A second type of ‘cluster’ is more ‘virtual’, in that it is a network among firms that might not actually be in physically proximity to one another. The networks may even include multinational firms with multiple affiliates, each supporting one another. Clusters can represent either vertical or horizontal integration. Firms in vertically-integrated clusters attempt to take advantage of synergy through their complementary functions. Each firm is able to continue narrow specialization, but together all firms are able to achieve economies of scope and scale that neither could achieve alone. The clusters can also represent horizontal integration, with firms duplicating the work of one another. As noted before, there are economies that derive from a larger scale of operation of the cluster, rather than of individual firms, in both input and output markets. The notion that hi-tech firms find advantage in clustering is, to some, an unlikely phenomenon. Many commentators have believed that new technology (and especially the internet) has removed ‘the limitations of geography’, especially in knowledge-based industries. This view suggests that recent advances in transportation and communication technologies are rapidly making agglomeration economies obsolete (Cairncross, 1997; The Economist, 1995; Thurow, 1996). Empirical studies of the location of biotech firms, however, show that the preferred location of firms is strongly in clusters. Especially important in relation to the problem of risk discussed earlier, is the notion that agglomeration may offer advantages that go beyond the ones linked to the ‘passive’ exploitation of other firms’ proximity. At least in principle, a cluster of firms is the right environment for the development of strategic relations among firms. In other words, here the assumption is that firms, inspired by what and who they see around them, may show a greater propensity to cooperate (Becattini, 1987; Bellandi 1996; Cooke, 2001). The forms of cooperation – either vertical or horizontal – may concern aspects such as process and product development, quality control, training, lobbying, or marketing. In this case the strategy of the firm suggests choice of a location because of the wish to establish durable relations with other firms. In contrast to passively-acquired external economies linked merely to proximity, the wish to undertake collective actions with other firms involves active and consciously pursued inter-firm relations (Di Tommaso and Rabelloti,

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1999; Fountain, 1998). Economies associated with collective actions have been observed frequently in the case of Italian industrial districts, where small and medium-size firms cluster together and have shown the capacity to compete at the global level (Bianchi, 1995). The concept has been described with reference to hi-tech industries in the Silicon Valley, as well, by Saxenian, 1994).

4. Policy options to promote development of firms in hi-tech industries Many countries aspire to promote the development of hi-tech industries. Both industrialized and developing countries attempt to increase employment in these industries. A facilitating factor for these firms is that their small initial size implies relatively low start-up costs and barriers to entry. Another strong motive these days is that jobs in hi-tech industries are thought to be less prone to be ‘outsourced’ to low-wage countries. It is ironic that now, even relatively hi-tech jobs are being outsourced to lower-wage countries. Examples are the outsourcing of call center jobs and computer programming positions to India. Meanwhile, India fears that these same jobs could migrate once again, this time to China or Vietnam, countries with still lower labor costs. What policy instruments are available to countries that would like to promote these industries? Three possibilities are discussed below: (a) The first is to facilitate the development of start-up firms. Zucker and Darby (1998) and Schweitzer et al., (2004) model the ‘birth’ of hitech firms as a ‘spin-off’ process from research-oriented universities. It is at these universities and research institutes that innovative ideas are first developed and, in many cases, the linkage between a university scientist and a venture capitalist results in the formation of a start-up company. This model helps explain why most biotech firms in the United States are located close to research universities (Schweitzer et al., 2004). By focusing on the origins of hi-tech firms, a policy instrument becomes apparent. Strengthening the research capacity of universities may enable countries to satisfy one of the criteria for the creation of spin-off companies – a creative scientist willing to take a risk to start a firm that is independent from his or her university. Scientific capability alone, however, is insufficient to create a spin-off company. A start-up firm requires initial capital, and so the capital market must support these ventures. In countries including United States, the UK, and Israel, the primary source of funding is venture capital. In Europe venture capital markets are small and less well developed. Therefore other capital mechanisms have been


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developed. Some rely upon government support, while still others rely upon private funding, either from philanthropy or existing industrialists (see, for example, Benichou and Viens, 2004). (b) A second direction for development policy is to provide startup companies with sufficient expertise that their probability of success is enhanced. Hi-tech firms require more than scientific expertise and capital. They require business acumen and assistance in doing market analyses. Often this knowledge is international in scope and is not readily available to individual firms. Government may have a comparative advantage in providing this kind of knowledge to start-up firms, so that they have a better capacity to identify international markets, both for their input factors and services, and for their outputs. (c) Lastly, a frequent observation is made that some governments are decidedly ‘unfriendly’ to start-up businesses in terms of bureaucratic regulations and procedures. Some regional governments have countered this problem by creating a ‘one-stop’ center at which all necessary permits can be obtained, rather than requiring the entrepreneur to go from place to place, often presenting the same information over and over in order to get approval to start a business. A related point is that firms that are spin-offs from universities and research centers must deal with university bureaucracies, in addition to government agencies. Universities are often government enterprises, themselves, and have been slow to recognize that they have a broader mission than educating students. Many university administrations have not yet realized that there are large opportunities in allowing faculty to split their time between their normal teaching functions and new entrepreneurial activities. If structured properly, universities themselves stand to gain from successful enterprises that grow out of their educational mission. Not only is their teaching function enhanced by offering graduate students additional employment opportunities, but universities can participate in new spin-off enterprises by extracting royalty payments and sharing in patents. This process must be done carefully, of course, in order to protect the university’s mission. But all-too-often universities demonstrate excessive caution in considering outside activities of their faculty members.

5. Conclusions Small and medium size enterprises comprise the overwhelming share of firms in developing countries. One explanation for the large share of small firms is that small firms somehow do not experience economies of scale that apply to larger firms. This chapter has suggested that the

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opposite is true: the high risk of failure actually accentuates economies of scale faced by small firms – especially those in hi-tech industries such as biotechnology. Despite the risks, many countries would like to help develop high-technology industries, whether for reasons of national prestige, employment stability, high-wage employment, or because of hope that the firms in those industries will be especially profitable. What options are available for governments to promote development of small, hi-tech firms? We suggest that several policy options are important. Some policies would promote the creation of start-up firms, often as spin-off enterprises from universities and research centers. Other policies are designed to enhance the likelihood of success of these ventures, such as by providing particular kinds of knowledge and expertise. Other policies address frequently observed deficiencies in the capital markets for start-up enterprises. Taken together, it is possible that development of small firms, especially in hi-tech industries, is feasible for developing countries. In fact, development of these kinds of industries may be an important direction for overall economic development of countries.

References Acs, Z.J. and Audretsch, D.B. (1990), Innovation and Small Firms, Cambridge, MIT Press. Arthur, W.B. (1990), ‘Positive Feedbacks in the Economy’, Scientific American, No. 221. Audretsch, D.B. (1998), ‘Agglomeration and the location of innovative activity’, Oxford Review of Economic Policy Vol. 14(2). Audretsch, D.B. (1999), ‘Knowledge Spillovers and the Role of Small Firms’, paper presented at the International Conference ‘Knowledge Spillovers and the Geography of Innovation: A Comparison of National Systems of Innovation,’ Saint-Etienne, July. Audretsch, D. and Feldman, M. (1996), ‘R&D Spillovers and the Geography of Innovation and Production’, American Economic Review, Vol. 86: 630–40. Audretsch, D.B. and Stephan, P.E. (1996), ‘Company-Scientist Locational Links: The Case of Biotechnology’, American Economic Review, Vol. 86(3). Becattini, G. (1987), Mercato e forze locali. Il distretto industriale, Bologna: Il Mulino. Bellandi, M. (1996), ‘Innovation and Change in the Marshallian Industrial District’, European Planning Studies, Vol. 4(3). Benichou, G. and Viens, G. (2004), ‘High Technology Clusters in France: An Empirical Study of Two Different Models’, in Di Tommaso, M.R. and Schweitzer, S.O. (eds), Health Policy and High-Tech Industrial Development: Learning from Innovation in the Health Industry, Cheltenham, Edward Elgar. Bianchi, P. (1991), Produzione e potere di mercato, Roma, Ediesse. Bianchi, P. (1995), Le politiche industriali dell’Unione Europea, Il Mulino, Bologna.


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Bianchi, P. and Labory, S. (2004), ‘Intangible Assets in the European Health Industry: The Case of the Pharmaceutical Sector’, in Di Tommaso, M.R. and Schweitzer, S.O., op. cit. Cairncross, F. (1997), The Death of Distance: How the Communications Revolution will Change Our Lives, Cambridge MA: Harvard Business School Press. Cooke, P. (2001), ‘Clusters as Key Determinants of Economic Growth: The Example of Biotechnology’, available at http://www.nordregio.se/files/ r0102cooke.pdf. Di Tommaso, M.R., Paci, D., Rubini, L., and Schweitzer, S.O. (2006), ‘Is Distance Dead? High-Tech Clusters Analysis and Policy Perspectives’, in Pitelis, C., Sugden, R. and Wilson, J.R., Clusters and Globalisation: The Development of the Economies, Cheltenham, Edward Elgar. Di Tommaso, M.R., Paci, D., and Schweitzer, S.O. (2003), ‘Clustering for Intangibles’, in Bianchi, P. Labory, S. The Economic Importance of Intangible Assets Aldershot, Ashgate. Di Tommaso, M.R., Paci, D., and Schweitzer, S.O. (2004), ‘The Geography of Intangibles: the Case of the Health Industry’, in Di Tommaso, M.R. and Schweitzer, S.O., op. cit. Di Tommaso, M.R. and Rabellotti, R. (1999), Efficienza collettiva e cluster di imprese: oltre l’esperienza italiana, Bologna, Il Mulino. Di Tommaso, M.R. and Schweitzer, S.O. (2004a), Health Policy and High-Tech Industrial Development: Learning from Innovation in the Health Industry, Cheltenham, Edward Elgar. Di Tommaso, M.R. and Schweitzer, S.O. (2004b), ‘The Health Industry Model: New Roles for the Health Industry’, in Di Tommaso, M.R. and Schweitzer, S.O., op. cit. Di Tommaso, M.R. and Rubini, L. (2007), ‘Industrial policy for “new” industries in “old” Europe: virtual clusters in genetics in Italy’, International Journal of Healthcare Technology and Management, Vol. 8(5): 503–2. Fountain, J.E. (1998), ‘Social Capital: A Key Enabler of Innovation’, in Branscomb, L.M. and Keller, J.H. (eds) Investing in Innovation Cambridge MA and London: MIT Press. Harris, C.D. (1954), ‘The Market as a Factor in the Location of Production’, Annals of the Association of American Geographers, Vol. 44. Krugman, P. (1991), Geography and Trade, Cambridge MA: MIT Press. Leamer, E.E. and Storper, M. (2001), ‘The Economic Geography of the Internet Age’, NBER Working Paper, No. W8450, available at http://papers.nber.org/ papers/W8450. Lösch, A. (1940), The Economics of Location, Jena: Fisher. Malecki, E.J. (1997), Technology and Economic Development: The Dynamics of Local, Regional, and National Competitiveness (2nd ed.), Harlow, Longman. Malerba, F. and Orsenigo, L. (2001), ‘Innovation and Market Structure in the Dynamics of the Pharmaceutical Industry and Biotechnology: Towards a history friendly model’, paper presented at the DRUID Nelson and Winter Conference, Aalborg, June 12–15. Marshall, A. (1890), Principles of Economics, London: Macmillan. Nooteboom, B. (1994), ‘Innovation and Diffusion in Small Firms: Theory and Evidence’, Small Business Economics, Vol. 6. Porter, M. (1990), The Competitive Advantage of Nations, New York: Free Press.

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Prevezer, M. (1995), ‘The Dynamics of Industrial Clustering in Biotechnology’, Small Business Economics, Vol. 9: 255–71. Saxenian, A.L. (1994), Regional Advantage: Cultural and Competition in Silicon Valley and Route 128, Cambridge MA: Harvard University Press. Schweitzer, S.O. and Di Tommaso, M.R. (2003), ‘Why do Biotechnology Firms Cluster? Some Possible Explanations’, in Sugden, R., Chen, R. and Meadows, G.R. (eds), Urban and Regional Prosperity in a Globalized New Economy, Cheltenham: Edward Elgar. Schweitzer, S.O. Connell, J., and Schoenberg, F.P. (2004), ‘Clustering in the Biotechnology Industry’, in Di Tommaso, M.R. and Schweitzer, S.O. op. cit. Swann, G.M. Prevezer, M. and Stout, D. (1998), The Dynamics of Industrial Clustering: International Comparisons in Computing and Biotechnology Oxford and New York: Oxford University Press. The Economist (1995), ‘The Death of Distance’, September 30. Thurow, L. (1996), The Future of Capitalism, New York: William Morrow. US Department of Commerce, Technology Administration (2004), at www. technology.gov/reports/corpR&D_inv/1996-2000_Tables3.xls. Weber. A (1909), Theory of the Location of Industries, University of Chicago Press. Williamson, O.E. (1975), Markets and Hierarchies, New York: Free Press. Zucker, L.G. and Darby, M.R. (1998), ‘Intellectual Human Capital and the Birth of US Biotechnology Enterprises’, American Economic Review, Vol. 88(1): 290–306.

4 The Start-up Process of Knowledge-based Companies in Latin America Hugo Kantis and Pablo Angelelli

1. Introduction Latin American economies have important structural weaknesses. First, they are highly specialized in goods that are intensive in natural resources and activities that compete internationally on the basis of labor costs rather than innovation (Mortimore, 1995). Second, productivity gaps between sectors and firms of different sizes are more marked than in industrialized countries (Peres and Stumpo, 2002). Third, many studies show that national innovations systems have a low performance (Alcorta and Peres, 1998). For instance, many countries of the region are below the thirtieth position in the technology ranking, which is consistent with a percentage of research and development personnel in the total population that is less than half of the East Asia region (World Bank, 2002). In fact, most of the Latin American countries have less than 500 researchers per million people.1 In this context, the start-up of knowledge-based companies could contribute to diversify economic structures and increase the average productivity. Nevertheless, although there is some evidence about the emergence of these types of companies during the last decade (Kantis et al., 2002), many questions about them remain to be solved: What is their economic impact? Which are the factors that encourage their birth and development? Which are the main constraints? How are they affected by structural weaknesses (productive, educative, etc.)? These are some of the questions that will be discussed in this chapter. This chapter analyses the start-up process and early development of dynamic knowledge-based companies in seven Latin American countries (Argentina, Brazil, Chile, Costa Rica, El Salvador, Mexico and Peru). The new knowledge-based companies are compared with a group of dynamic 71

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High Technology, Productivitiy and Networks

Phase

Event

Factors

Figure 4.1

Conception

Start-up

Early Development

– Motivation/Skills

– Planning

– Market

– Opportunity

– Access to resources

– Management

– Final decision

Culture & education

Productive Economic dynamic conditions

Networks Regulations Personal aspects

Analytical framework

companies of the traditional manufacturing sector.2 Dynamic companies are defined as companies between three and ten years of life and at least 15 workers. The study adopts a process approach (Gartner, 1988, Gibb and Ritchie, 1982) and a holistic perspective (Buame, 1992). The phases of the enterprise creation process analysed are: (i) conception, which consists of entrepreneurial motivation, identification of the business opportunity and the project design; (ii) start up, which includes the evaluation and decision to begin a new company; and (iii) early development, in which the company faces the challenges related to the entrance to the market and the phase of solution of problems in the first years (see Figure 4.1).3 The chapter is organized as follows. The first section presents a profile of the entrepreneurs and their ventures in the knowledge-based and traditional manufacturing sectors. The second section discusses the main factors and restrictions in each phase of the enterprise creation process. The last section includes the conclusions and policy implications.

2. Basic profile of firms and entrepreneurs The information available corresponds to 200 new companies of the knowledge-based sector (software, telematics, and internet services) and 437 companies in the traditional manufacturing sector (furniture, metallic products, foods, etc.). The great majority of the knowledge-based

Hugo Kantis and Pablo Angelelli

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Thousands US$

2500 2000

Knowledge sector Conventional sector

1500 1000 500 0 At the start

Third year

Year 2000

Figure 4.2 Evolution of firms’ average annual sales by sector Source: IADB/DBJ/UNGS/FUNDES database.

companies are located in the metropolitan areas, diversely in the most advanced countries, in which regional clusters and local areas represent a more typical location for this type of company (Saxenian, 1994). The investment in the creation of knowledge-based companies during its first year of activity is below 100 000 dollars in 70 percent of cases. In addition, an important fraction of the resources mobilized by the entrepreneurs to make their projects viable is their own working time in research and development activities. Average annual sales are higher for conventional manufacturing sector companies, although growth is more significant for knowledge-based firms. In the first year, annual sales of knowledge-based companies are 0.36 million dollars on average (against 0.572 in the traditional sector), while in the sixth year they are 1.6 million dollars (against 1.3 in the conventional sector; see Figure 4.2). This initial difference could be associated to a ‘double problem of newness responsibility’. Consequently, firms must demonstrate that they are responsible not only because they are new companies, but also because they have to overcome the natural prejudice that exists against the new companies that operate in the region in a non-traditional sector. The differences in the expansion of the number of jobs are less important, indicating a greater growth of the productivity in the companies based on high knowledge (Figure 4.3). These results put in evidence the capacity of the new knowledge-based companies to contribute to the development and dynamic of the small and medium enterprise (SME) sector. Whereas most of the new firms have been founded by teams of entrepreneurs (three partners on average) more than by individuals,

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50 Employees

40

Knowledge sector Conventional sector

30 20 10 0 First year

Third year

Year 2000

Figure 4.3 Evolution of firms’ average number of jobs by sector Source: IADB/DBJ/UNGS/FUNDES database.

Table 4.1 Level of education of entrepreneurs by sector (%)

University graduates Economics/Business Engineering Others Master in Economics/Business Master in Engineering Other Masters Incomplete university education Economics/Business Engineering Others Secondary education Primary education

Knowledge-based sector

Traditional manufacturing sector

82.7 6.6 28.6 12.2 10.2 5.1 16.3 9.7 1.5 4.1 4.1 5.6 1.5

54.2 12.6 181 10.8 6.2 1.8 3.0 9.8 3.0 3.7 3.2 26.1 9.6

Source: IADB/DBJ/UNGS/FUNDES database.

this characteristic is notably more important in the knowledge-based companies (86 percent against 68 percent). The typical entrepreneur in the knowledge-based sector is a university graduate, a profile that appears with much less frequency in the conventional sector. A considerable group of graduates, although it does not predominate, comes from engineering (see Table 4.1). This characteristic is found in a series of studies in other countries (Colombo and Delmastro, 2001; Fayolle and Ulijn, 2001; Litvak and Maule, 1976). Most of the founders are young people of middle-class and upper middle-class families, who study at the university, acquire technical knowledge, work


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Table 4.2 Previous work of entrepreneurs by sector (%)

Employee in a SME Similar sector Other sector, same function Other sector Employee in a large company Similar sector Other sector, same function Other sector Entrepreneur Similar sector Other sector, same function Other sector



35.7 23.5 8.2 8.2 45.9 20.9 13.8 13.8 37.9 26.5 5.6 7.7

44.6 28.1 8.0 13.3 30.9 17.2 4.3 10.5 35.8 24.3 5.5 10.8


some years in companies that allow them to connect with the enterprise world and then, when they are between 25 and 35 years old, they start up their first company with other partners. These results put in evidence the contribution of the new knowledge-based companies in canalizing the creative energy of university graduates, generating high quality jobs in labor markets with difficulties to incorporate these types of human resources. The founders of companies of high knowledge have usually worked previously in big companies, or to a lesser extent, in small or medium companies. On the other hand, the founders of conventional companies, generally, have worked mainly in small or medium companies (Table 4.2).

3. Important restrictions and key factors by firm creation phase In Latin America, the context restrictions to create firms in a new sector, such as software, telematics and internet services, are more severe than in the traditional sectors. In spite of this, the entrepreneurs who founded their companies in these new sectors have obtained greater dynamism. In the following sections the restrictions and key factors that have affected each phase of the firm creation process in both sectors will be analysed.

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Table 4.3 Motivations to create new firms by sector (%) Knowledge-based Traditional sector manufacturing sector Achieving personal fulfillment Putting knowledge into practice Increasing income Contributing to society Being own boss Becoming rich Becoming an admired entrepreneur Gaining social status Continuing the family tradition of being in business Being unemployed

89.8 86.7 66.3 60.2 54.6 30.1 26.5 11.2 28.1

87.9 75.3 76.9 57.7 56.1 26.3 36.8 23.3 32.0

7.7

10.3


3.1 Conception phase Reasons to create a new company The main reasons given by entrepreneurs for creating new companies are the desire for personal accomplishment and to put into practice the knowledge acquired. These reasons have been mentioned by more than 80 percent of the entrepreneurs interviewed (see Table 4.3). The next three reasons are to increase income, the desire of being one’s own boss and to contribute to society (the order of importance varies from country to country). The main differences between knowledge-based and traditional manufacturing firms are the smaller influence of positive role models, the desire to follow family tradition, improvement of income and a greater necessity to put knowledge into practice. The weakness of the role models represents a general characteristic of the Latin American context in previous studies (Kantis et al., 2002), but the comparison between sectors shows that the presence of a positive role model is even lower among founders of knowledge-based companies. This result suggests that the profile of the entrepreneurs who want to create a new company does not depend on having conventional role models in his/her family. This point seems to be confirmed by the percentage of entrepreneurs who said that the decision to create a new company derives from a desire to continue the family tradition. On the other hand, the great desire to put knowledge into practice shows the difference that exists between the professional background of the


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entrepreneurs and the opportunities to find a job adapted to their knowledge in an industrial structure that lacks companies in hi-tech sectors. In sum, the motivations to create new firms are not exactly the same in both sectors. In the knowledge-based sector financial reasons and the influence of role models seems to be less important, while the desire to put knowledge into practice is more pertinent. These results are of particular interest for policy makers. The series of reasons that motivate the creation of companies should include a ‘motivational package’ that surpasses the economic or financial incentives. In the same way, in view of acquiring abilities, this data indicates that more ambitious economic attitudes should become stronger in order to generate a greater will to increase the number of these entrepreneurs. Acquisition of vocation and skills A group of 15 skills were analysed, including attitude aspects, specific technical knowledge, enterprise and managerial abilities. The main environment to form an entrepreneurial vocation is the work experience of almost half the cases (Veciana, 2002). The analysis of the remaining skills confirms the fundamental role of work experience (first in importance in 14 of the 15 skills) and the more limited contribution of the family in the acquisition of certain attitude aspects, such as work ethics and interpersonal abilities (see Table 4.4). Despite the fundamental role of work experience, the entrepreneurs acquire more technical knowledge in the university (70 percent) as opposed to work experience (49 percent). These statistics explain in some way the dissatisfaction of a great number of university graduates with their job, which acts as an impulse for the enterprise motivation. A study (Audretsch and Thurik 2001) suggests that entrepreneurs create knowledge-based firms because of the information imbalance that generates a different evaluation of the enterprise ideas between the future entrepreneurs and the management of the company where they work. This type of enterprise genesis is expected when there is a set of companies from the same sector of the new company, where the entrepreneurs worked before starting up their own business. Latin American countries lack an industrial structure with a strong presence of hi-tech companies. Therefore, the enterprise genesis seems to come from the frustration felt by the professionals unable to use their knowledge in companies with limited innovative capacity, more than by problems of low appreciation of their business ideas from their previous business (Kantis et al., 2002). As mentioned before, the universities contribute enormously to the acquisition of technical knowledge, but they contribute less to the

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Table 4.4 Context for job and skills acquisition by sector (%) Competences

Problem-solving ability Business motivation Social skills in relating to others Risk tolerance Negotiating Team work Creativity Technical knowledge Marketing Management Hard work Planning Communicating

Work experience

University

Family

Knowledgebased sector






78.1 48.0 56.1

72.9 54.6 57.8

46.4 15.5 32.6

49.5 18.6 34.1

29.6 32.7 43.4

30.5 38.5 35.1

62.8 79.6 70.9 43.4 49.5 61.2 69.9 61.7 73.0 62.8

66.7 77.1 69.3 51.4 52.8 54.6 62.6 61.9 61.2 60.3

16.0 11.0 40.9 34.8 70.2 27.1 34.3 17.1 37.0 24.3

17.6 19.4 37.6 39.1 62.4 43.7 47.0 15.8 52.3 29.7

34.2 18.4 13.8 26.5 3.6 3.6 5.6 47.4 11.7 25.5

30.0 17.9 16.1 24.3 6.4 4.1 11.2 45.6 13.8 23.9



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remaining abilities necessary to create an enterprise (see Table 4.4). The contribution of universities in training entrepreneurs in the knowledgebased sector is still lower than in the traditional one. This can be perceived in almost all the analysed skills (especially in marketing, administration, planning, negotiation and leadership). These results indicate that it is fundamental to incorporate the formation of competences to stimulate business-like actions in universities and to foster the articulation with the world of companies and other scientific and technical institutions, and consequently stimulate the creation of companies and entrepreneurs from the universities. Business opportunity/enterprise idea Most of the entrepreneurs identify their business opportunities and develop their enterprise idea from information identified in their previous work experiences and from interactions with their personal contacts. A distinguishing characteristic for knowledge-based entrepreneurs is the use of wider, complementary and more specific sources (e.g. academic magazines, Internet and others). These entrepreneurs also make a more intense search effort to identify the business opportunity/idea, since the average number of used sources is greater (3.7 against 2.6). In reference to personal networks, as the international literature shows ( Johannisson 1998) it is possible to see several aspects of interest. In the knowledge-based sector entrepreneurs tend to trust professional colleagues more, while the interactions with other businessmen/ownermanagers or social contacts are considerably lower (see Table 4.5). This type of contact constitutes a limitation because international literature emphasizes the increasing importance of these kinds of contacts for the generation of innovations. Table 4.5 Composition of networks that helped to identify ideas by sector (%)

Large company executive SME owner Professional Banker Support institution employee Worker Other



25.4 18.1 29.8 1.5 1.2 14.7 7.6

20.1 31.4 17.1 0.7 2.0 13.7 13.0


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This limitation is confirmed when we compare the instability of these contacts with the nature of those that last. More than half of them state that they do not have current contact with people who contributed to identifying the business opportunity and, in the cases in which they do, they are limited to the partners. In other words, the greater presence of colleagues and workers in the initial networks are related to the process of recruiting an enterprise team. If this is not the case, it is because this process is connected to the existence of non-lasting contacts. This situation contrasts with that of the conventional sector, where there is a greater proportion of contacts who continue being suppliers or clients. In other terms, over time the dynamics of development of networks in the knowledge sector tends to become less strong than in the conventional sector. This appears to be a logical result if we consider the small initial participation of college students with the enterprise world. It the beginning, knowledge-based firms are less connected with production networks and new contacts are limited to future associates in fundamental activities. This weakness suggests a need to build connections between those who want to be businessmen and their potential clients, and thus facilitate the identification of the idea/opportunity and also become part of a business support network. 3.2 Start-up phase To create a business, it is fundamental to have the capacity to prepare the project and to have access to various resources, such as information, technology, inputs, services, financing, etc. The entrepreneur can get these resources in two ways: using the market or using networks of contacts. Project design Preparing a project requires the massive collection of commercial and technical data. In the knowledge-based sector entrepreneurs show a certain lack of knowledge in commercial aspects of business; this is not seen in more technical areas. In comparison with the conventional sector, there are some differences, especially in the percentage of businessmen who have information about channels of commercialization (55 percent, against 74 percent in the conventional sector). It is typical that this lack of information is related to what is confirmed in the contact networks analysis, which can be considered as important sources of information, although this can also reflect the most technical profile of these businessmen. Besides, almost half of them have not prepared a business plan


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Table 4.6 Previous evaluations of firm creation by sector (%)

Business plan Cash flow protection ROI Break even Sales and costs Future personal income



55.1 53.6 40.8 46.9 83.2 64.3

49.9 45.1 35.0 45.5 76.2 55.4


(see Table 4.6). In conclusion, the access to commercial information and the planning of projects represent the phases of the process in which businessmen show certain weaknesses. Role of networks in access to resources The majority of the entrepreneurs report having benefited from the support of their contacts, especially with the access to information and technology. Anyway, the support required to have access to other physical resources (services, material, team, etc.) is very limited. The main sources of support are acquaintances, friends and colleagues (see Table 4.7), followed by commercial contacts (especially suppliers/clients from the same region) whose importance grows with the access to technology. This seems logical given the specific nature of the resource. The comparison of the support received between sectors confirms certain flaws in the commercial or production networks of the knowledge based firms, especially in reference to the access to other resources. This can be seen particularly in the cases of Chile and Argentina, while the businesses in Brazil and Mexico receive greater aid from suppliers and clients of the same region, thus revealing the presence of a more integrated local network of production. The institutional networks play a lesser role than the social networks and those of production and, generally, they are limited to the access to information. This is verified in spite of some aspects that differentiate the entrepreneurs from the knowledge sector, who have a greater connection with academic institutions. Nevertheless, in Latin America the universities do not play the same role they play in other areas where they represent key actors of the technological development of the region.4 Institutions such as chambers of commerce or other public institutions, play a less significant role.

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Table 4.7 Networks and access to resources by sector (%) Networks

Social Friends Relatives Acquaintances Friends’ contacts Colleagues Professors Production Local suppliers Regional suppliers Local clients Regional client Institutional Universities Public institutions Chamber of commerce

Information

Technology

Other resources







76.5 51.5 19.4 54.1 25.5 43.9 19.4 69.9 40.8 26.5 43.9 26.5 36.2 24.0 12.2 14.3

76.0 54.2 35.7 47.4 23.8 35.5 11.7 70.0 51.7 28.4 45.5 28.4 30.2 14.0 14.4 19.5

52.6 33.7 8.2 33.2 15.3 28.6 14.3 62.2 43.4 38.3 20.9 15.8 26.0 16.8 4.1 10.7

59.6 32.5 23.6 34.8 18.3 23.6 8.2 56.3 41.2 25.9 22.0 17.4 21.1 10.5 7.8 10.5

42.3 24.5 16.8 19.4 9.2 16.3 2.0 37.2 26.0 17.9 18.9 12.2 9.2 4.1 2.6 4.1

55.6 32.0 25.2 30.2 15.1 17.4 4.1 54.5 42.6 24.7 21.7 15.6 13.7 4.3 5.3 8.7



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In synthesis, the development of the networks is a key factor of a policy to support business. The institutional construction is crucial for this objective. The universities and I&D institutions, the business chambers, the public agencies of development and the city halls should be part of any policy design implemented in the future. Sources of financing The majority of the entrepreneurs have created their businesses with their own resources (Mason, 1998, Winborg, 1997). The people interviewed confirmed that there are more stringent financial restrictions in the knowledge-based sector than in the conventional sector (see Table 4.8). Many reasons can explain these differences, including a more innovative nature and a greater proportion of ‘intangible assets’ that characterize these projects, the lack of a business curriculum for activities based on high knowledge, the lack of traditional financial institutions

Table 4.8 Sources of finance by sector (%)

Internal Personal savings Relatives and friends Credit cards External Business angels Venture capital Bank loans Overdraft Public bank loans Grants Other Client Suppliers Factoring Delay in tax payment Delay in service payment Delay in wage payment Purchase of second-hand machinery



83.7 80.6 15.3 17.3 33.7 12.8 4.1 14.3 15.3 1.0 1.0 49.5 24.5 23.0 4.1 8.2 2.6 4.6 16.8

89.0 84.7 25.9 7.6 35.0 5.3 1.8 24.3 11.4 2.3 0.9 63.2 15.6 41.4 4.3 7.8 2.7 1.6 37.1


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in the evaluation of these projects, the lack of a more developed network of suppliers in the country – they could provide working capital – and the smallest opportunity to use second-hand equipment. In contrast, a small group of entrepreneurs are able to have access to a capital of risk, especially thanks to the ‘business angels’ and, in a smaller proportion, to investment funds. Anyway, these sources tend to diminish clearly. The financial restrictions and the differences with respect to the conventional sector tends to be more noticeable during the first years of operation, when they finance its growth. The proportion of firms in the conventional sector that have access to banking loans is double compared with the knowledge-based sector, and a similar pattern emerges in the case of the credit of suppliers. With reference to the reasons for not using financing by third parties, half of those interviewed said that the type of provision is inadequate for their needs, one in three saying that he/she has not needed additional funds, and a similar proportion prefers to avoid external financing in order to maintain control of their business or simply because they do not trust financial institutions. Together with the limitations in the financing supply, there are also some obstacles on the side of the demand. The entrepreneurs from Brazil are the most critical in the financial aspect, while those from Chile are the least critical. For 72 percent of those interviewed, the lack of financing has some implications for the companies. Because of the lack of financing, a great number of firms have to begin in a scale (even if this is not desired) that is not the most appropriate to be competitive (54 percent); others need to get credit from suppliers and/or clients (45 percent), delay the creation of new business (26 percent) or select a lower technological level than that desired (37.3 percent). Summarizing, firms in knowledge sectors face greater financial restrictions compared with those in the conventional sector, and these restrictions lead to more difficult conditions for the setting in motion of the activity. Overcoming these restrictions is fundamental for the development of firms. It is important that the policy makers also consider, together with the limitations on the supply side, the problems that arise on the demand side.

3.3 Early development phase In the initial years entrepreneurs have to demonstrate that their projects and dreams are feasible. They must overcome barriers to enter the market and survive, find clients, handle a scarce cash flow, hire


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and organize human resources, find adequate suppliers, among other things. These challenges have particularities in the sector based on high knowledge. Firms and markets Knowledge-based companies establish their commercial proposals mainly taking advantage of opportunities associated with the differentiation of current products and with innovation (around half in both cases). The importance of the innovative proposals differentiates these companies from those in the traditional sector (49 percent, against 18 percent respectively), which are focused more typically in advantages of quality, services and/or price. The innovation is directed especially at the development of specific solutions for the domestic market (half of the companies interviewed) while the innovations at international level are second in importance (21 percent). Fewer than one in five firms report having based their proposals on advantages of price (against 43 percent in the conventional sector). The main clients of the new companies are other companies (76 percent), above all large firms from the services sector and, on a smaller

Table 4.9 Client companies’ profile by sector (%)

Services Large enterprises SME Both Manufacturing Large enterprises SME Both Wholesale trade Large enterprises SME Both Retail trade Large enterprises SME Both



68.1 38.7 19.0 10.4 53.4 30.7 12.9 9.8 35.6 19.6 11.7 4.3 28.8 9.8 15.3 3.7

23.7 7.6 9.5 6.6 51.9 19.0 17.1 14.9 36.1 9.8 15.8 10.4 25.9 4.7 13.9 7.3


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scale, from the manufacturing sector (see Table 4.9). The expansion of the services sector and the entrance of new, big international actors in the Argentine market, associated with the process of privatization and deregulation, have generated opportunities for the companies interviewed.5 This profile of the demand is considerably different in the traditional sector, where the main clients are from wholesale commerce and medium and especially small companies. It is noticeable that almost all the knowledge-based companies began their activity in a period of growing demand for such services/products and, generally, they face less competition from the founders of companies in the conventional sector. The proportion of firms that faced intense competition during that period is considerably lower compared with that in the conventional sector (41 percent, against 52 percent). The majority is competing with other SMEs (52 percent), others with large firms (31 percent), while a smaller number competes with both (13 percent). This profile of supply and demand gives some ideas as to why the new companies in the sector of high knowledge manage to export little. While a third of these companies exported in 2000, the exports were more than 5 percent of the sales in less than one-fifth of the companies. Their rise seems to be linked with the internal demand of large firms in expansion during the 1990s, to which these companies sold goods and services adapted specifically to their needs. An exporting strategy should explore the possibility of taking advantage of the established relationship with these big clients to reach the international markets where these clients operate. Managing the new company The first years are critical for a company, given that in these years there is the major risk of bankruptcy. Therefore, it is fundamental to understand the main challenges faced by new firms. Entrepreneurs indicate the following basic problems: finding new clients, managing cash flow, finding qualified personnel, directing the business, obtaining market information and finding adequate suppliers (see Table 4.10). Finding clients is a key problem for the knowledge-based companies for two reasons. The companies – and also the analysed countries – lack the experience to work in markets where technical capacity and trust are important factors, but also the weakness in the managerial capacities of the new companies constitute a problem especially in Argentina, Peru, El Salvador and Chile. Other common problems for the businessmen interviewed are the control of cash flow, the obtaining of market information and the management of the business. On the other hand,

Hugo Kantis and Pablo Angelelli Table 4.10

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Main problems in the first years by sector (%)

Find new client Manage cash flow Find workers Find suppliers Find equipment Adapt products Operation management General management Large clients relation management Find market information Quality control Hire managers



73.1 71.5 71.0 44.0 37.8 42.5 37.3 49.7 36.3 45.1 31.6 33.7

62.4 69.4 70.5 53.8 61.7 45.0 46.6 44.5 36.9 46.2 48.0 28.3


Table 4.11 Sources of support by sector (%)

Internal sources External support Public institution Chamber of commerce Consultancy firm Suppliers and clients Colleagues Friends and family Universities and R&D institutions



49.7 50.3 4.7 5.7 15.0 34.7 18.1 13.5 12.4

36.0 67.0 13.0 19.5 12.1 38.3 14.4 26.2 10.7


the three problems less mentioned are finding managers, buying equipment and certifying the standards of quality. This last case should be analysed taking into consideration that companies do not normally seek the certification of quality; therefore this represents an indicator of an absence of problem. The support network plays a smaller role in the knowledge sector compared with the traditional manufacturing sector (see Table 4.11).

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Although the commercial network is the main typical source of aid, this is relevant only for a third of the new companies. The support of the social and institutional networks is still lower. Brazil differs from other countries in terms of a bigger presence and interaction of network with clients/suppliers and particularly with institutions of science and technology (universities, research institutions). Brazil also enjoys a more compact system of production and of a more active system of innovation.

4. Conclusions and policy implications In this chapter we have identified the characteristic profile of companies and entrepreneurs of the knowledge-based sector, considering particularly its capacity for generating highly qualified jobs and innovative business projects of greater growth potential. This contribution is crucial for a region that needs to diversify and to enrich its industrial structure. In spite of this, the entrepreneurs working in these sectors have created their companies and faced challenges in the private context in which they operate. There are structural weaknesses that affect the firm creation process of knowledge-based companies. The identification of those weaknesses indicates some implications of policies for the region. It is important to show the relative weakness of the typical environments of learning in shaping vocations and business abilities: universities and companies, where the entrepreneurs worked previously, do not play a relevant role as ‘organizing incubators’. Besides, there is a small number of positively inspiring models, owing to a low density and visibility of companies and businessmen in hi-tech sectors. These results show the existence of structural difference among the present conditions (e.g. education, culture and systems of production) and the necessary conditions for an intense creation process of this kind of firm. Much can be said with reference to the networks that contribute to the creation and development of firms. In almost all of the region, but especially in Argentina and Chile, these networks are weak. Our research shows the relative weakness of production and institutional networks and a greater tendency towards contacts with professional colleagues. This is due to the low level of specificity and stability of the contacts that have facilitated the identification of business opportunities, the low access to resources (especially physical and financial, but also information), as well as the limited support that businessmen receive in overcoming the challenges faced in the first years of business.


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In addition, if we consider, on the one hand, the networks as structures/systems (sociocentric networks) and on the other hand, the individual tendency of the entrepreneurs to form networks (egocentric networks) (Johannisson et al., 1994), this research seems to indicate that these weaknesses originate mainly in the structural environment.6 This is due to the underdevelopment of the social capital in more fragmented companies and to the presence of fragile and fragmented systems of production and innovation in comparison with the most advanced countries where the networks represent a key factor of success in the creation and development of entrepreneurs and companies in new sectors (Saxenian, 1994, Kantis et al., 2002). These flaws in the ‘organizing incubators’ and in the networks help to explain, to some extend, the other weaknesses that have been reported, including the difficulties in the access to commercial information, the planning of projects and the development of commercial and financial management of companies. The financial restrictions are more severe in the knowledge-based sector, due to the presence of structural difficulties in having access to banking loans, the absence of a venture capital market in the region (formal and informal), and the low possibility of obtaining other resources from local suppliers of goods and second-hand equipment. In recent years, many programs and policies have been put in place to support the creation of knowledge-based firms in Latin America, which reveals a growing conscience of the problem. Nevertheless, the majority of the countries have implemented measures partly focused on training or technical support for entrepreneurs, traditional incubators or, in some cases, venture capital funds. But, as argued previously, there is a structural weakness in Latin American countries. Therefore, more integrated-systematic policies are required. The policies should include initiatives in different areas, such as the promotion of the business culture (e.g. climate/incentives) and the development of competences in institutions of knowledge (students, graduates, teachers and researchers in universities and I&D institutions); the implementation of spaces for the construction of teams and the development of networks (e.g. with other businessmen to learn from each other; with institutions of support to companies that provide technical assistance, with business angels for specialized capital and seed capital); the promotion of business opportunities; the introduction of reforms in the regulatory framework to promote venture capital and other financial products; the implementation of incubators and the technical aid for new business and businessmen. The local development could also find support

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in the business. Two examples of this type of policy are the initiative EXIST implemented by the Department of Education in Germany to promote knowledge-based companies, and the Program Softex in Brazil, directed at the creation of new companies in the software sector. Both have established economic incentives to maintain strategies designed and presented by regional alliances (including universities, other institutions of culture and business organizations) in a contest including the whole country.7 This combination of business, innovation and policies of local development represent an interesting route for the economic development of the region that these countries should seek to explore.

References Alcorta, L. and Peres, W. (1998), ‘Innovation systems and technological specialization in Latin America and the Caribbean’, Research Policy, 26: 857–81. Audretsch, D. and Thurik, R. (2001), ‘Linking Entrepreneurship to Growth’, paper prepared for Directorate for Science, Technology and Industry, OECD. Buame, S. (1992), ‘Stimulation of Entrepreneurship: An Integrative Approach’, paper presented at the European Small Business Seminar. Colombo, M. and Delmastro, M. (2001), ‘Technology-Based Entrepreneurs: Does Internet Make a Difference?’, Small Business Economics, Vol. 16(3): 177–90. Fayolle, A. and Ulijn, J. (2001), ‘Comparing entrepreneurial and innovation cultures: The European perspective of French, German and Dutch engineers, some empirical evidence about their technology versus market orientation’, paper presented at the Conference ‘The Future of Innovation Studies’, Technical University of Eindhoven. Gartner W. (1988), ‘Who Is An Entrepreneur? Is the Wrong Question’, American Journal of Small Business, Vol. 12: 11–32. Gibb, A. and Ritchie, J. (1982), ‘Understanding the Process of Starting Small Business’, European Small Business Journal, Vol. 1: 26–46. Johannisson, B., Alexanderson, O., Nowicki, K. and Senneseth, K. (l994), ‘Beyond Anarchy and Organization – Entrepreneurs in Contextual Network’, Entrepreneurship and Regional Development, Vol. 6(4): 329–56. Johannisson, B. (1998), ‘Personal Networks in Emerging Knowledge-Based Firms: Spatial and Functional Patterns’, Entrepreneurship & Regional Development, Vol. 10(4): 297–312. Kantis, H., Ishida, M. and Komori, M. (2002); Entrepreneurship in Emerging Economies: The Creation and Development of New Firms in Latin America and East Asia, Inter-American Development Bank, Department of Sustainable Change, Micro, Small and Medium-Sized Business Division, Washington. Kantis, H., Angelelli, P. and Moori, V. (2004), Entrepreneurial Development: Latin America and The International Context, Inter-American Development Bank and Fundes. Litvak, I. and Maule, C. (1976), ‘Comparative Technical Entrepreneurship: Some Perspectives’, Journal of International Business Studies, Vol. 7(1): 31–8.


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Mason, C. (1998). ‘El Financiamiento y las Pequeñas y Medianas Empresas’, in Kantis, H. (ed.), Desarrollo y Gestión de PyMEs: Aportes Para Un Debate Necesario, Universidad Nacional de General Sarmiento, Buenos Aires. Mortimore, M. (1995), América Latina frente a la globalización, no. 23, CEPAL/Naciones Unidas. División de Desarrollo Productivo y Empresarial, Santiago de Chile. Peres, W. and Stumpo, G. (2002), ‘Las pequeñas y medianas empresas industriales en America Latina y el Caribe’, CEPAL, Editorial El Siglo XXI, Mexico. Saxenian, A. (1994), Regional Advantage: Culture and Competition in Silicon Valley and Route 128, Cambridge, MA: Harvard University Press. Veciana, J. (2002); Comments on the results of the comparative study on Entrepreneurship between East Asia and Latin America, in Kantis, H., Ishida, M. and Komori, M., op. cit. Winborg, J. (1997), Finance in Small Business: a Widened Approach to Small Business Manager’s Handling of Finance, Hogskolan, Halmstad. World Bank (2002), World Development Indicators, Washington D.C.


Part 3 Productivity Increases


5 Business Support Services: A Conceptual Framework and Some Interesting Practices Nicola Bellini

1. Introduction In contemporary economies a large number of public and semi-public bodies are providing small and medium-sized companies (SMEs) with support services aimed at sustaining their competitiveness and growth strategies. Examples of business support services are: the Manufacturing Extension Partnership (MEP) in the US, Business Link – Small Business Service in England, Syntens in the Netherlands, ALMI in Sweden, the ‘real service’ centers in Italy, etc. The European Union itself has identified the creation of ‘top class business services’ as one of the main priorities in its policy for small and medium-sized enterprises. Also the economic literature has discussed this phenomenon for at least two decades now, with different approaches and sometimes opposed conclusions about its relevance. Nonetheless, a general consensus has emerged that such policies should be part of the toolbox of ‘structural industrial policies’ in those economies where the presence of SMEs is especially strong (see Parrilli’s introduction in this volume). In this chapter1 we intend to discuss some of the most relevant features of business support services, the ‘state of the art’ and the relationship with regional economic policies. Furthermore we will devote some specific attention to the nature and role of providers and to the issues concerning the evaluation of service activities.

2. Beyond definitions: business support services as ‘real services’ Eventually we have got an ‘official’ (and agreeable) definition of business support services, from a quite authoritative source, i.e. the European 95

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Commission. According to a recent Commission paper (CEC, 2001), business support services are: those services, originating in a public policy initiative, that aim to assist enterprises or entrepreneurs to successfully develop their business activity and to respond effectively to the challenges of their business, social and physical environment. In many respects, this is a useful definition, possibly too inclusive, but clear enough in establishing the conceptual link between policies and some business service activities. From this starting point a good deal of conceptual exploration is possible. Business support services transfer to user firms new ‘sticky’ knowledge resources and competences related to their core business functions. The exposure to the relationship with the service provider triggers learning processes within user companies, thereby modifying in a structural, non-transitory way their routines, their organization of production and their relationship with the market. Business support services:

• induce learning, i.e. a learning process is activated within the customer company. Services may either bring to light the unconscious, ‘hidden needs’ of the companies or – more often – give shape to needs that are perceived, but only roughly articulated; • have positive ‘externalities of consumption’, in the sense that, as a consequence of imitation mechanisms and network relations, higher standards are introduced both within individual companies and in industries and regions. Therefore, real services are supposed to contribute to the speed and quality of economic development. We call these enabling services to companies ‘real’. The expression ‘real services’ is clearly derived from the Italian ‘servizi reali’.2 It is the impact on the user and not the nature of the service supplied that defines real services. As a matter of fact, it is impossible to provide a definitive list of ‘real services’. Services are ‘real’ only in consideration of their impact on the user company and this in turns depends on the context where providers operate: they are both country- (or region-) specific and sectorspecific. Therefore, business support services are not to be confused with ‘advanced’ services. Real services may be and often are innovative, but this does not preclude, in specific situations, the activation of the virtuous circles of development and innovation triggered by services of a much more traditional nature. The only basic requirement remains that a learning process is activated within the customer company.

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This point is especially relevant when we shift our attention to less developed countries. Indeed most of the available literature refers to countries and regions where a certain level of economic development has been reached: this means that services impact on an already present industrial structure and play a role in its adjustment processes to new or changing competitive conditions. Such is the case of the ‘industrial districts’ (see Bellandi, 2005). A different discourse is clearly needed in the case of developing economies, where services should accompany the growth of an infant industrial structure. As there is a growing awareness of the central role of support services in development strategies based on clusters and networks (UNIDO, 2003), the transfer of experiences matured in developed regions to developing areas is possible and useful. Yet it must be dealt with cautiously and certain features of support services in industrialized areas (such as the emphasis on new technologies and knowledge) must obviously be reinterpreted (Gibb and Haas, 1999; Gibb and Adhikary, 2000; Caniëls and Romijn, 2005; Pietrobelli and Rabellotti, 2002 and Chapter 11 in this volume). In our opinion, the most important issues concern: the correct approach to the demand for services of SME; the need to stimulate a culture of innovation as well as cooperative behavior; the need to ensure continuity; to target users and partners, and to focus on human resources (Bellini and Condorelli, 2004; Committee of Donor Agencies, 1997).

3. The state of the art of support service policies It is impossible to give a quantitative estimate of the importance of business support services in contemporary economic policies. Calculating public expenditures in this area is an exercise that is made difficult by several factors: in most cases, it is impossible to distinguish expenditures for services and expenditures for other support activities; in other cases, expenditures occur at several levels of government, involve budgets of public and public–private agencies and even of private actors and associations. The information available on the state of the art of business support services worldwide is, to say the least, unsystematic. In particular we know little about the absolute quantities of services provided to companies. As matter of fact, we talk about a phenomenon, whose absolute size is unknown. In most cases we must refer to lists of members of networks or participants to national programs. As soon as one tries to comprehend the whole range of actors (public, semi-public, quasi-governmental, public–private etc.) information becomes even less

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systematic and reliable. According to a recent paper of the European Commission, ‘nonetheless, it is clear that large sums of public money are dedicated to support provision’ (CEC, 2001). In this section we restrict ourselves to summarizing a few facts that are supported by sufficient evidence. Firstly, business support services constitute a widespread phenomenon present in virtually every industrialized country (with relevant and well established examples in Europe, the US and Japan) and that is expanding to newly-industrialized and developing countries. The emphasis of the European Union on this issue is also evidence of the importance of business support services. Since 1994, the European Commission has emphasized the need for ‘creating top-class business support services’ as a contribution to increased competitiveness of SMEs within the scenario of the knowledge economy. Within the Multiannual Programme for Enterprise and Entrepreneurship and in particular for Small and Medium-sized Enterprises (2001–2005) a Best Procedure project on Business Support Services realized a wide review of the good practice in order to identify the steps necessary to achieve the ‘top class business support’ envisaged by the European Charter for Small Enterprises. Secondly, business support services have been a growing phenomenon, at least during the last 20 years. A significant amount of resources have been engaged in support activities; nevertheless, the total flow of financial resources does not allow this kind of intervention to show the same kind of clear and quantifiable impact on the economy of more traditional macro- and micro-economic policies. Thirdly, there are important differences between countries and also between regions within the same country. This differentiation stems both from explicit divergences in institutional design and strategic approach and from different starting points and pre-conditions (public–private relations; role and power of regional and local governments etc.), which makes meaningful international comparison often difficult. Finally, a second generation of initiatives is clearly coming up. The ‘new’ support service initiatives are the result of the reappraisal of earlier initiatives. In several cases, this has led to thorough restructuring of agencies and programs. The most significant of these cases in recent years has been the reorganization of the Business Links in the United Kingdom. However, new initiatives are also characterized by an increased professionalism of the management and staff of support service centers. Parallel to this, we witness to the definition of professional standards in some countries (AFNOR, 1997; DTI, 1998b) and the beginning of a standardization process at European level,3 to more frequent and consistent evaluation exercises and to a growing circulation of information on good practices,

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thanks to improved information sources (especially the service providers’ websites), the availability of databases4 and the activity of international networks.5

4. The conceptual framework: business support services in regional economic policies The political discourse on business support services has deep and robust roots in economic research. The conceptual toolbox that economists have built up defines the strategic framework for policies. 4.1 Business support services matter Within regional and local systems, the phenomenon of business support services is relevant for two reasons:

• business support services can help in identifying and building new linkages and cooperative interactions within the territory;

• business support services may contribute to identifying and building linkages with actors outside the territory. Internal linkages may concern more or less traditional issues (innovation, export promotion etc.), but there is often room for innovative linkages. Good examples are the evaluation and assessment services, like those supplied by the Steinbeis Foundation in Germany. By evaluating and assessing the technical creditworthiness of a company or of a project, the service provider allows the linkage between, on the one hand, companies and, on the other, banks and governments for the provision of equity and investment capital. External linkages allow the establishment of global connections for SMEs and the local/regional economy. Business support services often ‘import’ exogenous competences in the local system, thus having an impact on the local industry by adding opportunities, knowledge, relations among others; or, having developed specialized and innovative expertise, they ‘export’ it to other areas and sectors. They impact on local industry by increasing the range of actual and potential business networks. Moreover they are relevant for industrial policy makers at supra-local levels. A specific illustration of how a service center may become a node of local and global network is provided by CATAS, a laboratory for testing furniture and wood-based products that has evolved in a research center

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European specialized knowledge network Local industrial district

Other furniture districts

CATAS

Local customers

Non-local customers

Figure 5.1 CATAS as a network node Source: Grandinetti, 1998.

and a supplier of consultancy services to this industrial sector. Figure 5.1 shows that CATAS links with:

• the companies of the local industrial district in the North of Italy (the ‘chair district’ in the Region Friuli-Venezia Giulia);

• the companies outside the local district that operate in the same industrial sector and buy CATAS services. In this way CATAS helps the establishment and maintenance of production networks between local and non-local producers; • other (old and new) industrial districts: CATAS operates in the Italian region of Lombardy (with a subsidiary) and in Latin America, where the joint-venture CATAS Chile has been established to provide similar services to local producers. Here again CATAS creates opportunities for business relations, mostly as an ‘outward innovator’; • the international networks of specialized knowledge: CATAS is an active member of the European Association of Research Institutes for Furniture – EURIFI. This means that CATAS can import the most updated knowledge worldwide, monitor the evolution of technologies and markets (also thanks to the participation of standardization processes at European level) and promote methodologies and routines that are compatible with the local know-how, therefore defending the local competitive advantages.

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The business support services endowment contributes to the collective assets of a region or locality and to its ‘institutional thickness’ (Amin and Thrift, 1994): there is a positive relationship between the nature and strength of local/regional innovation systems and the knowledgeintensive service endowment. On the other hand, a vicious circle may emerge in the relationship between economic development and business support service endowment of a region or locality. This is related to the tendency of professional and business services to spatial clustering (Keeble and Nachum, 2001). Less developed production systems generate a limited and less qualified demand for services. Consequently, local service supply is likely to be limited and less qualified and this, in turn, hinders the development of the local production system (Pellegrini, 1997). 4.2 Provision of business support services suffers from market failures Market failures occur both on the supply and on the demand side. The consequence is that an adequate level of supply and of adoption by manufacturing companies is not assured. On the one hand, the private sector providers are predominantly orientated to large firms. In fact, private actors are often impaired by the impossibility to standardize services. If this is not possible, small companies often exit the strategic horizon of private service providers: they are (or are perceived as) difficult, risky and scarcely profitable customers, compared with larger corporations. Large firms are also the most important source of demand for new specialized business service firms. Furthermore, the information needed by small and medium-sized firms often is of a generic character – thus, it has ‘public good’ characteristics. As a consequence, the private sector fails to produce the type of information needed by SMEs. On the other hand, SMEs need external support more than large firms, but they are less able to make effective use of it, less able to search for specialist providers (and tied into the local network of generalist and less qualified providers), less able to specify their needs and, in too many cases, also less open to external advice (because of individualistic and self-centered attitudes). The gap may be difficult to bridge: demand may not search a supply that may not be searching for demand either.6 4.3 The best response to market failures takes place at the local and regional level Business support services are obvious candidates for localized delivery, because of the importance of close and frequent interactions for longterm relations to develop and because of the necessity to impact first on

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the local ‘strong ties’ of SMEs. Furthermore, using an interactive view of the process of innovation diffusion, which is based on technology as tacit and firm-specific knowledge, it follows that: The service relationship in technology transfer is closely dependent on the concrete context of the local innovation system within which it develops. The nature of this local innovation system (i.e. the habits, routines, institutions and rules specific to a given milieu) must shape the development of technology transfer services. (Cohendet, 1996: 272)

5. The providers of business support services 5.1 Private and public Who provides business support services? ‘In conceptual and actual practice, manufacturing modernisation programs do provide a form of interstitial filling between private- and public-sector activities’ (Feller, 1997: 189). Indeed, a plurality of actors can be found in that interstice, supplying a variety of organizational solutions in response both to the specific policy choices and to the characteristics of the socio-economic context. The list of potential providers of business support services includes:

• governmental bodies or independent public agencies; • public–private partnerships and agencies: this hybrid type is of special relevance for their ability to combine the advantages of legitimacy and neutrality of public bodies with – at least in theory – business-like efficiency and management styles and sometimes industry guidance;7 • consortia and specialized agencies sponsored by industrial associations; • private companies, acting according to government guidelines or within government projects or subsidization schemes. Differences in the performance of providers depend on several factors. Some differences are related to the institutional nature of organisations.8 When services imply disclosure of sensitive information or honest brokerage between potentially conflicting interest, public or collective actors may be perceived as offering better guarantees of objectivity, neutrality and confidentiality. Legitimacy and skills in building consensus may favor governmental agencies or associations. Certain actors, like universities, may perform better in case of need for specialized skills, but they may lack experience in servicing companies

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and may show excessive organizational rigidities (Bellini and Piccaluga, 2000). A solution consists in the establishment of specialized agencies that can extract from the academia the wealth of knowledge, without sharing its organizational problems. The potential of universities and research centers to provide, directly or indirectly business support services is very important, as is shown by several cases worldwide.9 Furthermore, business associations and chambers of commerce may be constrained in their actions, because of the priority on increasing or maintaining membership. This may result in the inability to select customers among members and in the impossibility of serving non-members (Bennett, 1998a and 1998b). Although the public nature of the provider may often be an essential feature, implying not only significant constraints but also important opportunities, it must be fully and consistently accepted that also private providers can be instrumental to the realization of effective business support service policies: the contents and the effective delivery of services is more relevant than the nature of the providers. The main advantages of private actors in supplying business support service policies are: a greater effectiveness in the user’s capability building; mobilization of specialized knowledge; possibly lower costs; more effective targeting, as a result of better knowledge of the market and less dependence on political constraints; and decentralized operation (Bessant and Rush, 1995). To sum up, Table 5.1 shows that different actors have different strengths and weaknesses with regard to the:

• quality and quantity of competence and relations; • efficiency and flexibility in service provision; • legitimization and neutrality, with regard to users. Question marks indicate that strengths or weaknesses depend on the specific situations, e.g. public-private partnerships and industrial associations are not necessarily efficient or inefficient. They may be efficient in one case and inefficient in another one. A support service policy that resorts to private actors instead of (or in addition to) public agencies or public–private partnerships, is faced with two main sets of problems:

• the identification of service providers that ‘fit into’ the policy objectives and quality standards;

• the potential or actual competition between public or subsidized providers and the private sector.

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Table 5.1 Strengths and weaknesses of business support services providers

Government agencies Universities and research institutes Public–private partnerships Industrial associations Service companies

Competence/ relations

Efficiency/ flexibility

Legitimation/ neutrality

? +

− −

+ +

+ ? ?

? ? +

+ + −

The first problem may be solved by establishing a procedure for accreditation of the service providers, on the basis of some pre-defined criteria. This is the approach adopted by the Business Link system and later by the Small Business Service in the UK. The accreditation process is likely to be quite complex. The scrutiny of proposals needs to consider many elements and be possibly iterative, in order to specify and agree on the different aspects of service production and delivery. An alternative to complex systems of accreditation is provided by the establishment of registers based on self-references and minimal filtering. No certification is provided about the enlisted providers. This approach is followed also internationally, e.g. by the ‘Euro-Mediterranean Park of business support services for small and medium sized companies’, a large Internet database of business support services and providers, inspired by the Spanish agency IMPIVA and implemented within the European program INTERREG. Sometimes the co-existence of public, subsidized and private actors creates difficult problems. A key and sensitive issue concerns the possible market distortion, that – as shown in some cases (e.g. Bellini and De Laurentis, 2000) – may be caused by public and subsidized providers and that may damage the operations and the development of the private suppliers. Distortions consist in the subtraction of market shares, but above all in the spreading among small entrepreneurs of incorrect views about the role, impact and pricing of external services. Elsewhere the impact of support service policies on the development of the private sector seems to have been less problematic and even positive. Clear rules are set up to avoid undue competition, e.g. according to Business Link guidelines, ‘for services other than basic information and counselling, all clients must be offered a choice of service providers who offer the same or similar service to meet their needs. In the case of the consultancy service this is normally a choice from a minimum of three

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consultants. […] The choice offered must, wherever possible, include one provider not connected with the Business Link or partner’ (DTI Business Link Directorate, 1998a: 11). A positive element has been the explicit policy choice in favor of partnerships with private actors, e.g. in the US, the Technology Reinvestment Program, that had a major impact on the structure and character of the MEP, imposed the co-financing of the projects by local or private funds and included an explicit requirement that proposals for funding addressed a criterion entitled ‘Coordination and Elimination of Duplication’. This criterion required that projects link with related service providers in the service region, be consistent with existing state strategies, and not duplicate existing resources or services (Shapira, 2001).10 In the FAQs page of the website of MAMTC (Mid-America Manufacturing Technology Center), the following statement can be read: ‘MAMTC was established to expand the market for private consultants, rather than to compete with them. A significant number of our projects include these consultants on the team. In these cases, MAMTC serves as a “sales force” for them, and also handles project management and billing’. In the US, according to one survey, besides providing services that are not supplied by private consultants, manufacturing extension centers play a relevant role in informing SMEs about private consultants and in facilitating access to them. It is therefore argued that local partnerships do not compete directly with private consultants; they provide assistance that enhances the relationships with private consultants and that they encourage the kind of openness to change that is conducive to a greater and more profitable use of outside assistance (Oldsman, 1997). In the UK, an evaluation survey of the Business Links (PACEC, 1998) reported that the business service provision by the private sector had been quite positively affected: the volume of services provided had increased and new services had been introduced. A selective effect seemed to be in place. In fact, the provider groups benefiting most from the stimulation of service demand were specialist consultants, together with banks and accountants, mostly as a result of signposting and referral activities by the Business Links. Simultaneously, the lower segments of the service markets (small independent advisers and consultants offering relatively poorer quality services) appeared to be negatively affected. 5.2 Producers vs. brokers Not all support service providers are producing the services they provide. Very often the agencies or companies that deal directly with users are only brokers of services that are produced by someone else. A service

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broker may add to the service acquired a greater or lesser amount of value or may simply take care of promotion and distribution. Brokers may be extremely important for the objectives of a business support service policy. On the one hand, brokers may manage crucial flows of information between (potential) demand and supply of business support services: e.g. ‘to address the high cost of some private consultants, one center has negotiated reduced rate structures which take into account the fact that the center bears the marketing costs and that center referrals often generate opportunities for follow-on work’ (Shapira, 2001: 987). On the other hand, brokers may help to make demand emerge from unspecified needs of potential users; brokers may actively collect demand and promote cooperation in buying behavior (multi-client projects). Furthermore, as the brokerage approach allows for supplying geographically dispersed users and at the same time takes into account that knowledge intensive services tend to remain geographically concentrated (on an international scale), it seems to be especially adequate for the development of support service activities in less developed and industrializing countries and regions (Bellini and Condorelli, 2004). Brokerage instead of direct production is an option that is increasingly implemented, because it adds to the opportunities for ‘territorialization’, i.e. a more diffused presence in the territory and greater proximity to SMEs. In so doing, it is a way to balance the trend toward the internationalization and geographic concentration of knowledge-intensive services. Furthermore brokerage helps to exploit the opportunities of cooperation and of risk- and expertise-sharing between support agencies (Cromie and Birley, 1994). In fact, small companies, which often operate in niche markets, may face very specific (technical and market) problems. Agencies run the risk of not being able to give appropriate responses, unless they are able to rely on a plurality of sources of information and expertise. In fact, brokerage may be at the core of the ‘real service’ activity. In many cases the innovative impact derives mainly or totally from the building of new problem-solving linkages between distant subjects (organizationto-organization, but often person-to-person). A fundamental experience in business support services has been the establishment of Personal Business Adviser services (PBAs) within the Business Links in England. PBAs provide the most explicit and complete design of a brokerage function and are the central feature and resource of the system of assistance to SMEs (DTI, 1998a; Lean et al., 1999; Bennet and Robson, 1999). PBAs are generalists and their task is to facilitate SME access to high-quality business support services. They work with customers in order to clarify and review their objectives, to prioritize their needs, to identify, package and

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coordinate the delivery of specialist services, to monitor service quality and impact on the client company.

6. Evaluation 6.1 Outcomes Ideally policy makers like to see evidence of a causal relationship between service policies and changes in the economy, at firm level, but possibly also in the economy as a whole. In order to find these causal relations, we need to investigate in more detail the ‘outcome’ of business support services. Depending on the scale on which one chooses to focus (i.e. the unit of analysis) a different outcome can be identified. Each outcome requires an appropriate method of measurement and evaluation. The four types of outcomes are summarized in Table 5.2. Operational outcomes are those patterns of behavior within the company that have been directly affected by the service provision. In other words, they are the immediate result of the service and they can be observed in the changes occurred in the user’s practices, to which we must add the effects of learning. Business outcomes are the variations in company competitiveness that are related to the use of support services. ‘Gross business outcomes’ may be evaluated by looking at changes occurring in basic key indicators (such as sales, cost savings, net assets, employment, client investments, Table 5.2 The evaluation framework Unit of analysis

Outcome

Functions within user companies

Operational outcomes (= service outputs plus learning) ↓ Business outcomes (= gross additional changes in business performance) ↓ Industry outcomes (= aggregate business outcomes minus deadweight plus company linkages) ↓ Socio-economic outcomes (= aggregate industry outcomes minus displacement plus multipliers)

User companies

User companies + their networks + competitors and imitators

Local economy

Source: Bellini, 2003.

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profits, exports, etc.) and in other performance indicators, both generic (labour productivity, capital productivity, and so on) and service- or sector-specific (market share, staff turnover, new product introduction time, and so on). More qualitative evaluations concern the effects of the service on the company’s relational space. Industry outcomes are the aggregate of business outcomes, relative to one industrial sector. They should be evaluated after discounting ‘deadweight’ effects, i.e. those outcomes that would have been achieved independently of the support activities. Furthermore, business outcomes must be detected not only in the user companies, but, because of spillover effects, in a larger group of linked actors. This group includes, besides user companies, companies belonging to their networks (e.g. when innovative practices in computer-aided design are ‘imposed’ on subcontractors) and imitators. Industry outcomes can also be measured by looking at company (or plant) survival rates. These indicators are especially important when referred to newly-started companies and can be compared with the survival rates in control groups. Among industry outcomes we should also include the impact of support services on the creation of inter-firm networks. Attempts so far show mixed results. This is also due to the fact that informal networks are sometimes more successful than the networks that are formally established as a result of the policy. Lastly, socio-economic outcomes are variations in the economic and social aggregates and are the most sensitive indicators in the eyes of policy makers. The unit of analysis is larger than the previous ones, i.e. the local (or regional or national) economy as a whole. Indicators include standard measures of economic performance (domestic product, exports etc.). Politically-sensitive indicators are the numbers of jobs created or retained (and the payroll from additional jobs) or the territorial distribution of services (e.g. the percentage of administrative divisions served). Other indicators may focus on the investments in human capital (e.g. the number of trained employees). Socio-economic effects are the combined result of the aggregate effect of business outcomes, increased by ‘multiplier’ effects, but diminished by ‘displacement’ effects. In other words, final evaluation must take into account that ‘some effects/outcomes benefiting support users are sometimes gained at the expense of their competitor businesses’ (PACEC, 1998: 7). Macro economic models of local or regional economies can be used, first, to translate firm impacts into industry impacts, after which they can be turned into estimates of the total economic impact (Ehlen, 2001). At this point policy makers may require also ‘value for money’ measurements and especially ‘cost-per-job’ and ‘taxpayer-payback’ estimates.

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All these measurements are in fact subject to difficulties in implementation and to more basic methodological challenges that make evaluation of business support services quite a hard task. The main difficulties stem from: the limited availability of control groups; the ‘mobility’ of policy objectives; the extreme heterogeneity of cases; the relevance of long-term, intangible and implicit benefits; the relevance of rival explanations; the limited diffusion and quantitative significance of interventions, etc. (Bellini, 2003). 6.2 Interpreting the market response Two ‘market’ indicators are then used in an attempt to summarize the performance of business support services: at the macro level, the ‘market share’; at the micro level, the ‘user satisfaction’. The market share of business support services can be adopted as an indicator of service penetration in the area’s productive apparatus. In practice, we use the percentage of companies (or of SMEs) that have bought the service. In fact such figures lend themselves to political interpretations. The larger the number of companies using the service, the larger is the number of subjects that are involved in the implicit exchange: in other words the market share matches the share of those benefiting from the policy, appreciating it and presumably ready to reward policymakers in terms of political consensus. Figures of market shares for business support services are so far quite disappointing. This seems to reflect a structural problem, not easily modifiable by policies. Some national case studies (especially referring to Australia, Ireland, Japan, Portugal, as reported in OECD, 1995) indicate participation rates with an order of magnitude of about 20–30 percent of all SMEs. In the case of Business Links, 1998 DTI user statistics show 112 000 business users per quarter, representing 5 percent of firms with 1–9 employees, 19 percent of 10–49 employee firms, 43 percent of 50–199 employee firms, and 9 percent overall. Recent estimates indicate increased difficulties of governmental bodies to meet market penetration targets (Bennett and Robson, 2003). A recent survey estimated the average participation level at 20 percent of all micro, small and sole proprietors’ businesses in Europe, with the highest rate in the Netherlands (34 percent) (Sheikh et al., 2002: 22). In the US: Much of the generic needs assessment of small- and medium-sized manufacturing firms that has served to build political support for manufacturing modernization programs relates to the symptoms of

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poor competitive behavior, not to an understanding of internal firm decision-making processes. In effect, centers work only with that relatively small percentage of firms defined as willing and able to accept assistance. As noted by the Manufacturing Technology Centers Third Year Review Panel, ‘the Manufacturing Technology Centers must cope with the fact that in the order of 70 percent of small- and mediumsized manufacturing companies are reported to be unable, unwilling, or unprepared to adopt the technologies and practices that would enhance their competitiveness. Of the remaining 30 percent, approximately two-thirds are willing but unable to adopt new technology; and one-third are both willing and able to do whatever it takes to enhance their competitiveness using advanced technology’ (Feller at al., 1996: 311). Market shares of business support services seem to be highly sensitive to a variety of factors. Shares are normally higher as a result: of the (de facto) compulsory character of the service; of a wider range of service supply (that may include standardized or scarcely innovative services); of the generosity of subsidies. Also sectoral and geographical variables may matter. For instance, contact patterns may be more intensive in peripheral regions, where support agencies may be the only partner available, than in urban areas, where private services are more developed. To sum up, also the comparability of market share data seems quite low. Rather than implying that business support services are of marginal importance, low market-share figures seem to be a sign of the limited relevance of the indicator. It is not the only one. It is interesting to notice, for example, that there is no evidence of a relationship between participation rates and satisfaction. A survey of Europe’s business support services shows very clearly that the countries with the highest satisfaction rates are not necessarily countries with high participation rates, with the only exception of Ireland. Countries with participation rates higher than the European average, like the Netherlands, Denmark, the UK, Finland or France show satisfaction rates at the European average level or lower. Portugal, Spain and Belgium show high satisfaction rates with participation rates at an average European level or lower (Sheikh et al., 2002: 41). As a consequence, in business support services marketsensitive suppliers may be driven into low value-added markets. As is reported in the Michigan case: ‘Top management has been torn between the Evaluation Team’s calls for focusing on high impact projects […] and the field staff’s inclination to deliver the services that firms ask for and are easiest to sell’ (Luria and Wiarda, 1996: 245).

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The market share analysis can be replaced, at least partially, by the analysis of the customer base. Within this approach the customer must be valued not only with regard to its present ‘transactional’ value, but also and mainly with regard to its long-term attractiveness, i.e. its ‘relationship value’. A good example is provided by a study commissioned by CATAS, the Italian service center for furniture and wood-based products (www.catas.it; CATAS, 1999). The customer base is analysed on the basis of their usage of services and distinguishes between the traditional core service of CATAS (technical tests) and the other services (engineering, research, training, etc.). Five types of customers are identified:

• superficial customers use the test service only and occasionally. They

•

• • •

are small and medium-sized companies with little propensity to export and to innovate and are unlikely to evolve in their using behavior, at least in the short term; occasional customers use all kinds of services, although rarely. Possibly this happens only in specific situations and for specific needs. Although these companies may have a good propensity to innovate and to export (and therefore need to certify the quality of their productions), they do not (yet?) perceive the service center as an appropriate partner; traditional customers use test services regularly and have tried other services. The relationship with these companies has a potential to evolve towards a partnership; functional customers use test services on a regular basis, but seem uninterested in widening the area of cooperation with the service provider; partners are those customers whose behavior has evolved towards a wide-ranging cooperation with the center.

The actual weight of the different types of customers is indicated by Figure 5.2. By analysing the provider’s portfolio of customers, we aim at ‘giving a name’ to the users. This gives evaluators some crucial information. Firstly, this analysis allows to distinguish ‘good’ customers from ‘bad’ customers: as we repeatedly stressed, not all customers guarantee to contribute the same quality to service production and therefore providers should feel a need to ‘give priority to a limited portfolio of established businesses with the potential and aspiration to grow, establishing and maintaining a long-term relationship with them’ (DTI Business Link Directorate, 1998a: 6).

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16% 27%

Superficial (rarely tests; no others) Occasional (rarely tests; rarely other services) 19%

Traditional (freq. tests; rarely others) Functional (freq.tests; no others)

6%

Partner (freq. tests; freq. other services)

32%

Figure 5.2 The customer portfolio of CATAS Source: CATAS, 1999.

The ‘community of customers’ determines the nature and level of the service, in terms of both image and substance. This is even more important, as it was also mentioned before, because of the inherent risk of adverse selection. Evaluators should be able to verify the overlap between the customer base and the hard core or the elite of one area’s productive apparatus. In the case of Pont-Tech (Pontedera), the center’s estimate of its customer base indicates that present customers (first half of 2001) represent 25 percent of the potential target market (mechanical subcontractors of the one large company in the area). But client companies represent 45 percent of the total procurement of the large company present in the area (most of the local SMEs are its suppliers) and an even higher share of the purchases with higher technology and quality characteristics. The center’s staff, however, was also able to mention (by name) a few other companies that are ‘not yet’ customers of the center. On the contrary, in the case of technology transfer centers operating in the Lombardy region, Cusmano et al. (2000) show that the group of innovative companies (identified through objective criteria, such as patents and the access to regional innovation programs) and the customer base of the centers in fact do not coincide. Secondly, the analysis of the client base makes it possible to identify and to weigh new customers and loyal customers. Loyal customers not only ‘cost less’, but guarantee a longer-term commitment to the relationship and are likely to participate more in service production.

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7. Conclusions This chapter has provided a short overview of some of the key issues concerning business support services, as they emerge from international literature and practice. It is worth emphasizing once again the strategic relevance of at least three of these issues. Firstly, business support services should not be evaluated in abstract terms, based on generic expectations about technological ‘paradigms’ or on simplified ‘benchmarking’ with success cases, but with specific references to the situation where they must operate. Although knowledge intensity is likely to be a central and common feature everywhere, support services in less developed and industrialized areas need specific (even if less ‘advanced’) delivery. Secondly, a flexible approach is needed with regard to the issue of the provider. On the one hand, setting up an agency formally dedicated to support provision does not imply necessarily that an effective support service policy is in place. On the other hand, some redundancy of actors may be useful in order to meet a diversified and dynamic demand. Successful support service supply should be based on both public/semipublic and private providers and must be delivered by brokers, when actual production is not technically or economically possible. Thirdly, a selective relationship with users is essential for the success of a support service policy. Providers and policy makers must be aware of the risk of fuelling adverse selection that results in inferior services and weaker impact.

References AFNOR – Association Française de Normalisation (1997), ‘Accompagnement global à la gestion del petite entreprise. Service des centres de gestion agréés et habilités. Spécification des services. Norme française homologuée’, NF X 50–880, Paris: AFNOR, December. Amin, A., and Thrift, N. (1994), ‘Living in the Global’, in Amin, A., and Thrift, N. (eds), Globalization, Institutions, and Regional Development in Europe, Oxford: Oxford University Press. Bellandi, M. (2005), ‘Los distritos industriales’, in Parrilli, M.D., Bianchi, P. and Sugden, R., Alta tecnologia, productividad y redes: un enfoque sistemico para el desarrollo de las PYMEs, Colegio de Tlaxcala, Mexico City. Bellini, N. (2000), ‘Real Services: A Re-appraisal’, European Planning Studies, Vol. 8(6), 711–28. Bellini, N. (2003), Business Support Services. Marketing and the Practice of Regional Innovation Policies, Cork: Oak Tree Press. Bellini, N., and Condorelli F. (2004), ‘The role of business support services in development cooperation policies with MENA countries’, paper presented at the Fifth

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Mediterranean Social and Political Research Meeting, Florence – Montecatini Terme, March. Bellini, N., and De Laurentis, C. (2000), L’offerta di servizi innovativi alle imprese, Florence: Unioncamere Toscana. Bellini, N., and Piccaluga, A. (2000), ‘The role of the university in constituencybuilding for industrial and territorial innovation: reflections on an Italian experience’, in López-Martínez, R., and Piccaluga, A. (2000), Knowledge Flows in National Systems of Innovation. A Comparative Analysis of Sociotechnical Constituencies in Europe and Latin America, Cheltenham, Edward Elgar. Bennett, R. (1998a), ‘Business associations and their potential contribution to the competitiveness of SMEs’, Entrepreneurship & Regional Development, Vol. 10, 243–60. Bennett, R. (1998b), ‘Business associations and their potential to contribute to economic development: reexploring an interface between the state and market’, Environment and Planning A, Vol. 30, 1367–87. Bennett R., and Robson, P. (1999), ‘Business Link: Use, Satisfaction and Comparison with Business Shop and Business Connect’, Policy Studies, Vol. 20(2), 107–31. Bennett, R., and Robson, P. (2003), ‘Changing Use of External Business Advice and Government Supports by SMEs in the 1990s’, Regional Studies, Vol. 37(8), November, 795–812. Bessant, J., and Rush, H. (1995), ‘Building bridges for innovation: the role of consultants in technology transfer’, Research Policy, Vol. 24, 97–114. Bianchi, P., and Bellini N. (1991), ‘Public Policies for Local Networks of Innovators’, Research Policy, Vol. 20, 487–97. Brusco, S. (1992), ‘Small firms and the provision of real services’, in Pyke, F., Sengenberger, W. (eds), Industrial districts and local economic regeneration, Geneva: ILO. Caniëls M., and Romijn H. (2005), ‘What Works, and Why, in Business Service provision for SMEs: Insights from evolutionary theory’, working paper of the Eindhoven Center for Innovation Studies n. 05.03. CATAS (1999), ‘CATAS: centro servizi reali alle imprese nel distretto della sedia’, San Giovanni al Natisone: CATAS. CEC – Commission of the European Communities (2001), ‘Creating top-class business support services’, Commission Staff Working paper, SEC(2001) 1937, Brussels, November. CEN – Comité Européen de Normalisation (2001), ‘Description for the types of business advice and support services provided to small enterprises in Europe’, CEN Workshop Agreement, Brussels. Cohendet, P. (1996) ‘Transfer of technology to Small and Medium Enterprises (SMEs): Conceptual changes and lessons from the two banks of the Rhine’, in Teubal, M., Foray, D., Justman, M., Zuscovitch, E. (eds), Technological Infrastructure Policy. An International Perspective, Kluwer, Dordrecht. Committee of Donor Agencies for Small Enterprise Development (1997), ‘Business Development Services for SMEs: Preliminary Guidelines for Donor-Funded Interventions’, Washington. Cromie S., and Birley, S. (1994), ‘Relationship among small business support agencies’, Entrepreneurship & Regional Development, Vol. 6, 301–14.

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Cusmano, L., Lissoni, F., and Sironi, M. (2000), ‘Selezione avversa e trasferimento tecnologico: un’analisi del centri di servizio alle imprese della Regione Lombardia’, Economia e politica industriale, Vol. 105, 19–57. DTI Business Link Directorate (1998a), ‘Personal Business Adviser Service. Policy Guidelines’, URN 98/695, Sheffield, November (revised). DTI Business Link Directorate (1998b), ‘National Standards of Professional Competence for Business Links’, URN 98/817–822 (six documents), Sheffield, July. Ehlen, M. (2001), ‘The Economic Impact of Manufacturing Extension Centers’, Economic Development Quarterly, Vol. 15(1), 36–44. Feller, I. (1997), ‘Manufacturing technology centers as components of regional technology infrastructures’, Regional Science and Urban Economics, Vol. 27, 181–97. Feller I., Glasmeier A., and Mark M. (1996), ‘Issues and perspectives on evaluating manufacturing modernization programs’, Research Policy, Vol. 25, 309–19. FSMED – Foundation for Small and Medium Enterprise Development, University of Durham (2002), ‘Business Support Services and Market Failure’, Brussels: European Commission. Gibb, A., and Adhikary, D. (2000), ‘Strategies for local and regional NGO development: combining sustainable outcomes with sustainable organizations’, Entrepreneurship & Regional Development, Vol. 12, 137–61. Gibb, A., and Haas, Z. (1999), ‘Developing local support services for small business development in Central and Eastern Europe. The donor challenge’, Entrepreneurship & Regional Development, Vol. 8, 197–216. Glasmeier, A. (1999), ‘Territory-based Regional Development Policy and Planning in a Learning Economy: The Case of ‘Real Service Centers’ in Industrial Districts’, European Urban and Regional Studies, Vol. 6(1), 73–84. Grandinetti, R. (1998), ‘Evoluzione del distretto industriale e delle sue formule imprenditoriali. Il caso del distretto friulano della sedia’, Economia & Management, Vol. 4, July, 79–98. Keeble, D., and Nachum, L. (2001), ‘Why do business service firms cluster? Small consultancies, clustering and decentralisation in London and Southern England’, Working Paper 194, Cambridge: ESRC Centre for Business Research, University of Cambridge. Lean, J., Down, S., and Sadler-Smith, E. (1999), ‘An examination of the developing role of personal Business Advisors within Business Link’, Environment & Planning C: Government and Policy, Vol. 17, 609–619. Luria D., and Wiarda, E. (1996), ‘Performance benchmarking and measuring program impacts on customers: lessons from the Midwest Manufacturing Technology Center’, Research Policy, Vol. 25, 233–46. OECD (1995), Boosting Business Advisory Services, Paris. Oldsman E. (1997), ‘Manufacturing extension centers and private consultants: collaboration or competition?’, Technovation, Vol. 17(5), 237–43. PACEC – Public and Corporate Economic Consultants (1998), ‘Business Links – Value for money evaluation’, Final report, Cambridge, October. Pellegrini, G. (1997), ‘Domanda di servizi e struttura del sistema produttivo del mezzogiorno’, Rivista economica del Mezzogiorno, Vol. 2, 417–49. Pietrobelli, C., and Rabellotti R. (2002), ‘Business development centres in Italy. An empirical analysis of three regional experiences: Emilia Romagna, Lombardia and Veneto’, Santiago: CEPAL.

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6 Entrepreneurship, Small Firms and Self-employment1 David Audretsch, Maria Callejon and Mari Jose Aranguren

1. Introduction At the end of the 1970s an important change took place in the economic structure of developed countries: a considerable increase in the number of small and medium enterprises occurred as well as a decrease of large firms. Since then, a wide literature has analysed this phenomenon. Some of these studies focus on the causes of this phenomenon whereas others centre on its consequences on economic growth and public welfare. The empirical literature highlights the dynamism of small firms in terms of both employment generation and innovation (see also the Introduction to this volume). For this reason the number of small enterprises, in relative terms, is considered a good indicator of entrepreneurship.2 The higher dynamism of small enterprises is presented in the literature as one of the main causes for their increase in the economic structure of their countries. Creation, growth and survival of new firms are fundamental processes that define the increasing competitiveness and their capacity to generate employment. However, empirical evidence highlights the situation that although small firm creation ratios are higher than those related to large firms, the sector of small and medium enterprises (SMEs) represent more vulnerable firms that tend to survive for shorter periods. An important gap in the literature on SMEs and enterprise dynamism refers to the lack of studies that take into account the heterogeneity of small firms (again, see the Introduction to this volume). Characterization and studies that try to detect differences in small firms conduct and performance are very important in analysing the impact of these economic units on growth and welfare. 117

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Although entrepreneurship is considered a factor in innovation and growth (Audretsch and Leilbach, 2003), it is not easy to find empirical ways to distinguish the entrepreneurs from other traditional business or from self-employed people. This makes it harder to measure the impact of entrepreneurial activities on growth. Empirical work has followed various approaches, including reports where self-employment is equated to ‘entrepreneurship’ (Gallup Europe, 2000) as well as academic approaches that take a more restricted view (Audretsch, Carre and Thurik, 2001). This chapter suggests the convenience of defining better the concept of ‘entrepreneurship’ in order to identify an observable variable that may be useful as an indicator of the level of entrepreneurship, given that only some businesses and start-ups represent genuine cases of entrepreneurial activities. This chapter follows this sequence: first, it looks at the changes that occurred in the economic structure and in the role of small firms within most Western countries during the twentieth century; secondly, it discusses some relevant models on the nature and consequences of entrepreneurial behavior; the third part examines some theoretical and empirical issues concerning the impact of entrepreneurship on growth and welfare; fourth, it comments on the pertinence of the measures of entrepreneurship used in empirical studies; finally, we present some evidence based on Spanish data suggesting that solo self-employment might be omitted in measures of entrepreneurial activities. The conclusions include suggestions on policy issues.

2. Changes within industry The role of SMEs in society has changed drastically over the last half century. During the post-Second World War era, the importance of small businesses seemed to fade away. While alarm was expressed that small businesses needed to be preserved and protected for social and political reasons, few stressed their relevance for economic efficiency. This position has reversed in recent years. It was startling when scholars began to document that what seemed an inevitable demise of SMEs, actually began to reverse in the 1970s. Loveman and Sengenberger (1991), and Acs and Audretsch (1993) carried out systematic international studies examining the re-emergence of SMEs and entrepreneurship in North America and Europe. Two major findings emerged from these studies – first, the relative role of SMEs varies systematically across countries, and secondly, in the mid 1970s in most European countries and in North America, SMEs began increasing their

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relative importance. In the US the average real GDP per firm increased by nearly two-thirds between 1947 and 1989, from $150,000 to $245,000, reflecting a trend towards the formation of larger size enterprises. However, within the subsequent seven years the real GDP per firm had fallen by about 14 percent to $210,000, reflecting a sharp reversal of the trend and the re-emergence of SMEs (Brock and Evans, 1989). Similarly, in 1976 SMEs accounted for one-fifth of manufacturing sales in the US, but by 1986 the small-firm sales share had risen to over one-quarter (Acs and Audretsch, 1990). The reversal of the trend leading from larger size enterprises towards the re-emergence of SMEs was not limited to North America. In fact, a similar trend was found also in Europe. For example, in the Netherlands business ownership rate fell during the post-war period and reached a trough of 0.085 in 1982. But this downward trend was subsequently reversed, rising to a business ownership rate of 0.10 by 1998 (Audretsch et al., 2002a). Similarly, the small-firm employment share in manufacturing in the Netherlands increased from 68.3 percent in 1978 to 71.8 percent in 1986; in the United Kingdom from 30.1 percent in 1979 to 39.9 percent by 1986; in (West) Germany from 54.8 percent in 1970 to 57.9 percent by 1987; in Portugal from 68.3 percent in 1982 to 71.8 percent in 1986; in the north of Italy from 44.3 percent in 1981 to 55.2 percent by 1987, and in the south of Italy from 61.4 percent in 1981 to 68.4 percent by 1987 (Acs and Audretsch, 1993). An EIM study documents how the relative importance of SMEs in Europe (19 countries), measured in terms of employment shares has continued to increase between 1988 and 2001 (EIM, 2002). With respect to the United States, Birch (1989) observed that the creation of new firms increased from around 90 000 in 1950 to 700 000 at the end of the 1980s. The same author signaled that in the late 1970s two-thirds of all net new jobs were created by very small companies with 20 or fewer employees. According to the approaches of dynamic industrial economics and evolutionary theory, the enhanced role of small firms is a consequence of structural change, and in particular of the shift in the predominant industrial regime that has been wisely described by Piore and Sabel (1984) as the ‘second industrial divide’. Audretsch and Thurik (2000 and 2001) have pointed out how, since the late 1970s, the United States have experienced changes in the industrial structure and the technological regime that implied a shift in industrial dominance from the big conglomerates and mass production technologies to the small innovative specialized firms.

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Audretsch and Thurik (2000) provide further factors of this structural shift – which is especially evident in United States. There has been an increase in labor supply together with some reduction in wages. This shift is complemented with better education; changes in consumer preferences for wider varieties of goods and services; deregulation that eases entry of new firms. In addition, Audretsch and Thurik (2001) maintain that the shift towards a knowledge-based economy is the driving force behind the move from large-sized to smaller-sized businesses, which represent a considerable part of new innovative activities. According to this hypothesis it may be said that the current economic period corresponds to Schumpeter’s Mark I regime of ‘creative destruction’ that is followed by a period equivalent to Schumpeter’s Mark II regime of ‘creative accumulation’. From the governance point of view Audretsch and Thurik maintain that there is a corresponding shift from the ‘managed economy’ to the ‘entrepreneurial economy’ (Audretsch and Thurik, 2001). Since the late 1990s, the trend towards a greater share of small firms within markets seems to have slowed down (Kwoka, 2000). Simultaneously the last few years have witnessed a significant process of concentration in many economic activities. The concentration process affects not only hi-tech industries and activities with network externalities, but also more traditional activities including retail services and hospitality, that are also the favorite activities of many micro entrants. Within John Sutton’s theory (1998), the present source of scale economies is not the automation of the production process – like in post-Second World War – but the existence of important sunk costs (e.g. in terms of R&D, advertising and global marketing) as well as the presence of learning economies associated to innovation that constitute dynamic economies of scale. In prospect, an interesting aspect might be the relationship of the entrepreneurial regime that emerged in the 1970s and 1980s with the more recent concentration trends that, given its characteristics, do not seem to imply a return to what Audretsch has titled the ‘managed economy’ of the old big firms. Apparently, present concentration rates do not correlate closely with higher market power as in previous periods. As Jovanovich (2001) has signaled the new economy is one in which technologies and products become obsolete at a much faster rate than a few decades ago, imitation lags have shrunk, technologies are adopted faster, and small firms and new firms are capable of quick responses and innovative activities. Jovanovich suggests that we are entering the era of the ‘young firms’; for this reason, it is not to be taken for granted that present concentration trends in some industries or segments of industries


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will bring a second move towards a Schumpeter’s Mark II regime or, equivalently, a ‘managed economy’.

3. The nature of entrepreneurship The notion of entrepreneurship, typically identified as the business activities of those agents that seek to introduce new ideas, products or services in the market, has long been recognized as a fundamental vector of economic growth and social development. The most prevalent and compelling views of entrepreneurship focus on the perception of new economic opportunities and the subsequent introduction of new ideas in the market. Entrepreneurship is about change; entrepreneurs are agents of change insofar as entrepreneurship is about processes of change. This corresponds to the definition of entrepreneurship proposed by the OECD: ‘Entrepreneurs are agents of change and growth in a market economy and they can act to accelerate the generation, dissemination and application of innovative ideas. Entrepreneurs do not only seek out and identify potentially profitable economic opportunities but are also willing to take risks to see if their hunches are right’ (OECD, 1998: 11). Since this change adds value to economic welfare it is generally regarded as a desirable behavior for the wealth of the nations. The concept and phenomenon of entrepreneurship have been approached outside and in parallel to the field of industrial organization but from different – although related – perspectives. Audretsch (1995) maintains that the theory on the behavior of new firms should take the individual as the unit of analysis. In classical dynamic approaches the entrepreneur is identified as the agent that (i) experiments and discovers (Hayek); or (ii) innovates (Schumpeter). Always the entrepreneur is an agent that fosters economic development. Hayek (1948) did not produce an explicit theory of the role and nature of entrepreneurship but his conception of the process of economic development relies on agents that scan all new market opportunities under the incentive of making a profit. Each agent browses only an infinitesimal part of the economic reality, but all alternatives are tested collectively. Implicitly Hayek presents entrepreneurship as a type of behavior that many individuals spontaneously adopt under free political and social institutions. In some way Hayek transfers the idea of biological Darwinian evolution to the economy in a process that involves the entrepreneurial activity. In a society ruled within parameters of individual freedom and where the allocation of resources is performed fundamentally through a competitive market, no business opportunity

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will pass unnoticed by one or another individual seeking to make a profit. Although Hayek acknowledges that individual rationality is imperfect and limited, and most undertakings will not be accepted by the market and fail, those business initiatives that are socially valuable and are able to generate enough demand will succeed. In that way free individual initiative coupled with overall coordination by the market will ensure that all imaginable innovation possibilities will be tested and only those ‘best fit’ business initiatives will be able to survive in the process of competition and contribute to produce the highest economic progress and rate of growth. In other words, the outcome of the selection process is that resources are optimally allocated in a dynamic context. This is a good way to illustrate the process of dynamic competition. Hayek does not intend to explain the entrepreneurship itself but its effects on the general performance of the economy under a policy regime of individual freedom. Entrepreneurs fit in as the elemental unit of economic growth. Recently Carlsson and Eliasson (2001) have proposed a model that they call ‘experimental selection’ that includes similar considerations. One aspect of Hayek’s model that may have interesting implications and links to modern selection theories like Jovanovic’s (1982) is that in his outline all initiatives are tested. Hayek’s model presents also the attractive feature that it can account for the high turbulence of firm demography, whereas models that suppose some kind of entrepreneurial rationality have more difficulties to match this empirical evidence. If the decision to enter a market is fully based on rationality the rate of gross entry would probably be lower and vary much more across industries and over the product cycle. In Schumpeter’s approach the entrepreneur is an innovator. The entrepreneur is the element that provides the creative response of the economic system whereas conventional business people present adaptive responses. The list of innovative activities (new goods, new methods of production, new markets, new sources of supply, new forms of organization of an industry like the creation of a cartel or, inversely, the breaking up of a monopoly) does not include only strict technological innovations. Responding to the specific purpose of this chapter, the relevant aspect is that Schumpeter distinguishes between two different technological regimes of innovation; he also identifies a different nature of the entrepreneur in each of the two regimes. In Schumpeter’s Mark I regime (1912) innovation is afforded by many small firms that use the ‘public basin’ of existing knowledge (Soete and Weel, 1999). This is the space where the entrepreneurs operate. In Schumpeter’s Mark II regime (1942)


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innovative activities are conducted by incumbent large firms which usually are monopolists of innovation and are able to appropriate most economic rents. In this second scenario it is more difficult to see a role for individual entrepreneurs, although the entrepreneurial drive remains very critical. If the theory of entrepreneurship is of special interest it is because we can distinguish two approaches that depend upon the adoption of a broad or a restrictive concept of entrepreneurship. According to the broad, inclusive concept, an entrepreneur is someone that takes decisions about the co-ordination of production activities and the allocation of resources. However, the academic tradition generally takes the more restrictive option that considers the entrepreneur as an innovator or a front runner, as in Schumpeter’s or Baumol’s contributions. In this second sense, entrepreneurship and management are not conceived as the same thing, neither in terms of motivations nor for their effects. Baumol (1968) expresses this widely shared conception by specifying that the ‘management function’ consists of taking the firm to its production possibility frontier, whereas the ‘entrepreneurial function’ focuses on locating new ideas and on putting them into effect, that is, to stretch the frontier further out. The adoption of the first (broad) or the second (narrow) interpretation of entrepreneurship involves deep analytical consequences. While innovative entrepreneurship is generally considered to impact positively on the level of competitiveness and on the growth rate, management activities are supposed to imply also positive but less intense effects.

4. Creative destruction, entrepreneurship, growth and welfare Although entrepreneurship has been considered almost universally as the vehicle for innovation, the beginning of a specific research line on its mechanisms is recent. The program of research developed by Acs and Audretsch (1987, 1988, 1990, 1993, 2001 and 2003) is rooted in the dynamic approach that provides evidence that innovative entrepreneurship in small firms is at the base of economic growth. Recent studies have also related the rates of SME ownership to growth (Audretsch and Thurik, 2001; Thurik and Wennekers, 1999; OECD, 1998). Audretsch et al. (2002b) have argued that the better growth performance of United States over the European Union in recent years has to do with the strong entrepreneurial vitality in the United States.

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The theories that link entrepreneurship with economic growth implicitly or explicitly assume that entrepreneurs are the agents of innovation and that technological innovation affects positively total factor productivity. In conformity with this model, Callejón and Segarra (1999) found that the rates of entry and the rates of turbulence affects positively total factor productivity in Spain; however, in this case these authors prefer explaining the positive correlation between entry of new firms and innovation/productivity on the basis of capital returns. Given that new small firms and the rate of firm turnover are considered indicators for industrial dynamics, the attention of a significant part of scholars has turned to the analysis of new firms. The scenario of the entrepreneurial economy implies that new firms are the driving force of innovation and of creation of skilled jobs. There are some empirical studies that confirm this theory, for instance, the report Enterprises in Europe produced by the European Commission (2001) confirms that in the period 1987–97 the European regions that experienced the highest growth rates were also those with the highest proportion of small firms. The exception are those regions with a high proportion of small firms that have a specialization in manufacturing industries; regions in this situation presented low growth rates. If innovative entrepreneurship can be associated to economic growth, a different problem arises, i.e. to identify the extent to which ‘creative destruction’ – or the turbulence associated with high rates of entry and exit – leads to faster growth and welfare improvement. The idea of a dominant ‘creative destruction’ driven by innovation in the current period is also explicitly shared by the Reynolds et al. (2001) GEM Report Series where the developed conceptual model assumes that business churning positively affects growth. However, the birth of very small firms has since long been negatively related in many models to the opportunities of finding a paid dependent employment, and to the unwanted ‘push’ of rising unemployment (Bögenhold, 2000). It is generally accepted that an important share of the ‘self-employed’ is not driven by motives of market innovation, and should not be considered ‘entrepreneurial’ in its Schumpeterian innovative sense. There is wide consensus in the distinction between the entrepreneur as introducer of innovations and other agents running a business. It can be expressed as the difference between an entrepreneur and a ‘shopkeeper’ (Audretsch et al., 2001), or as the distance between the group of ‘income substitutors’ and ‘entrepreneurial business’ in the terminology of David Birch. Baumol (1968), distinguishes between entrepreneurs and managers, like Penrose (1959). Other researchers, including Bögenhold


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(2000), Dhalquist and Davidsson (2000), have analysed from different approaches the motives that lead some people to start a business. Reynolds et al. (2001) have chosen to distinguish between ‘opportunity entrepreneurship’ and ‘necessity entrepreneurship’. And the case is that if not all new firms, not all self-employed enter into the category of entrepreneurs; an interesting question, from the point of view of the industrial dynamics analysis is to find ways of sorting out the types of agents that take the decision to create a firm and the importance of their respective contribution to economic growth. Audretsch et al. (2002) highlight the importance of institutional arrangements for the development of entrepreneurial activities. According to this analysis, the European Union, with its lasting unemployment difficulties, risks incurring a penalty in terms of economic growth rate if industrial restructuring continues to be impeded by institutional and regulatory barriers. For this reason, policy should shift from ‘regulating’ and ‘prohibiting’ to ‘enabling’ individual initiatives. The authors argue that policy should follow the lines of deregulation, privatization and labor market flexibility. ‘The central role of government policy in the entrepreneurial economy is enabling in nature. The focus is to foster the production and commercialization of knowledge. Rather than focusing on limiting the freedom of firms to contracts through antitrust, regulation and public ownership, government policy in the entrepreneurial economy targets education, increasing the skills and human capital of workers, and facilitating the mobility of workers and their ability to start new firms’ (Audretsch and Thurik, 2001).

5. Measures of entrepreneurial activity Empirical tests of the link between entrepreneurship and growth have been made less consistent (Reynolds et al., 2001) by the difficulties of finding a good definition for entrepreneurship that allows appropriate observable variables to be identified. Although scholars generally agree that new businesses are an important, if not the main agent of entrepreneurship, it seems also clear that not all new businesses are entrepreneurs able to make an impact on growth and innovation. One of the limitations involving both research and policy derives from the heterogeneity of entrepreneurship. An important research challenge is to decompose at least some of the different types of behavior and incentives that characterize entrepreneurship, which may help distinguish it from other businesses forms.

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Operationalizing entrepreneurship for empirical measurement is a difficult task (Storey, 1991). The degree of difficulty involved increases exponentially when cross-country comparisons are involved. Studies focusing on a single country, either in a cross-sectional or time-series context, have deployed a variety of proxy measures, spanning self-employment rates, business ownership rates, new firm start-ups, as well as other measures of industry demography, such as turbulence (turnover), or the extent of simultaneous births and exits and net entry. An ideal measure would incorporate each of these different measures reflecting a different aspect of entrepreneurship. However, systematic measurement conducive to cross-country comparisons is limited. The different contexts and organizational forms involving entrepreneurship account for the paucity of measures used to reflect entrepreneurial activity. Measures of self-employment reflect the change that is occurring at least for the individual starting a new business. That very little of this change is projected onto the larger industry, nation or global market has long resulted in the criticism of self-employment as a measure of entrepreneurial activity. That is, what is new and different for the individual may not be so different for the industry and the global market. As Aldrich (2000) has shown, even for a developed country such as the United States, only a very small fraction of new startups are really innovative. Still, measures of self-employment are widely used to reflect the degree of entrepreneurial activity, largely because they are measured in most countries, and measured in comprehensive comparisons across countries and over time (Blau, 1987). Audretsch et al. (2002a) and Carre et al. (2001) use the measure of business ownership rates (the number of business owners divided by the total labor force) to reflect the degree of entrepreneurial activity. There are a number of important qualifications that should be emphasized when using and interpreting this measure. First, it lumps together all types of a very heterogeneous activity across a broad spectrum of sectors and contexts into a specific measure. Second, it is not weighed for magnitude or impact. Third, this variable measures the stock of businesses and not the start-up of new ones. However, this measure has two significant advantages. The first is that, while not being a direct measure of entrepreneurship, it is a useful proxy for entrepreneurial activity (Storey, 1991). Second, it is measured and can be compared across countries and over time. Other measures of entrepreneurship focus more on change that corresponds to innovative activity for an industry. Such measures include indicators of R&D activity, the numbers of patented inventions, and


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new product innovations introduced into the market (Audretsch, 1995). These measures have the advantage of including only firms that actually generate change at the industry level, i.e. beyond the firm itself. However, such measures must always be qualified by their failure to incorporate significant types of innovative activity and change (Griliches, 1990). Similarly, other measures of entrepreneurial activity focus solely on the criterion of growth. Firms exhibiting exceptionally high growth over a prolonged duration are classified as ‘gazelles’. For example, Birch (1999) measures the number of ‘gazelles’ to reflect entrepreneurship. Such measures of entrepreneurship must also be qualified for their narrow focus on both the single unit of observation (the firm) – and the single measure of change (growth). Lundstrom and Stevenson (2001) followed the precedent of the Global Entrepreneurship Monitor (GEM) study (Reynolds et al., 2000) by defining and measuring entrepreneurship as based on the ‘mainly people (operating) in the pre-start-up, start-up and early phases of business’ (Lundstrom and Stevenson, 2001: 19). An obvious limitation of this approach is that it restricts entrepreneurial activity to the process of the firm start-up. While an important manifestation of change and innovation is undoubtedly reflected in the process of starting a new business, at the same time there is a considerable amount of change and innovation contributed by incumbent enterprises of all sizes, or what is sometimes referred to as ‘intrapreneurship’. Lundstrom and Stevenson justify their emphasis on pre-start-up and start-up as well as the incipient and early stages of business ownership because: These are the targets of measures on entrepreneurship promotion policy and we propose that these policy measures are taken to stimulate individuals to behave more entrepreneurially, which in our view can be done by influencing motivations, opportunities and skills. Therefore, our aim is to see what types of policy actions are taken towards individuals in the pre- and early stages of idea and business development. (Lundstrom and Stevenson, 2001: 19) In sum, one of the main imperfections of the most often employed measures of entrepreneurship is that they cannot discriminate between Schumpeterian entrepreneurship or self-employment and other routine business initiatives. To progress in the empirical test of the theory and policy on entrepreneurship it is convenient to try to identify and measure the relevant variables. This chapter attempts a modest contribution by

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signaling some groups of firms that may be more safely excluded from the concept of entrepreneurship.

6. Empirical analysis In this section of the chapter we use a database from Spain to compare the pattern of new business creation among business with 0 employees and firms with positive employment. This comparison enables us to test the hypothesis that the behavior of businesses driven by selfemployed without any employees is different from other small firms that hire employees. Entrants with 0 employees form the vast majority of the self-employed. We argue that entrants with 0 employees react to incentives that are different from those affecting entrants with employees, and that the proportion of entrepreneurs is apparently much lower among self-employed with 0 employees than among the rest of the firms. Our first hypothesis is that the commitment to pay employees can be interpreted as a signal that the new firms have higher expectations of growing and lasting than when firms start with no employees. The second hypothesis is that, although the composition of solo-employment is very heterogeneous, for a substantial part it is associated to weaker endowment in terms of capital and human resources. These represent businesses founded out of desperation, where the founder is unable to find an acceptable, paid and dependent job. In the European Union firms without employees account for more than 50 per cent of the stock of active firms; they represent 10 per cent of employment and almost 4 per cent of turnover. The share of this business is even higher in Spain, where they account for around 56 per cent of the firms, 19 per cent of employment and 8 per cent of turnover. The share of 0 employee enterprises is higher in all service sectors than in manufacturing and energy (in terms of number of enterprises, employment and turnover). This high proportion means that all analyses involving industrial demography, or using the standard measures of entrepreneurship that include 0-employee-businesses are highly influenced by the characteristics of this large group, especially if the unit of analysis is ‘number of firms’. This bias is likely to be less important if the analysis is made with reference to ‘number of workers’ or ‘turnover’. It is possible to compare the behavior of 0-employee-enterprises with firms consisting of 1 and 2 employees and 3 or more employees in Spain between 1994 and 2000. The database used is DIRCE or ‘Directorio Central de Empresas’, obtained from the Spanish ‘Instituto Nacional


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de Estadística’. This is a relatively new longitudinal database starting in 1994. The only variable contained within this database is the ‘number of employees’, whereas the individual information is not publicly available. It is only possible to obtain data for nine size classes, including the 0 employee class. For the purpose of this work we have opted for a graphic analysis which allows a better and more direct assessment of this case. 6.1 Firm demography by size Figures 6.1 and 6.2 present the entry and exit behavior and the survival rates of self-employed firms to small businesses over the period 1994–2000. Although the demographic dynamism of 0-employmententerprises is higher than the rest, their life expectancy is lower than in enterprises with employees. As we observe in Figure 6.2, less than half of 0-employee-enterprises created in 1994 survived in 2000 (43 per cent), while this percentage increases to 48 per cent for enterprises created with 1 or 2 employees and to 55 per cent for firms with three or more workers. Alternatively, if we consider the size distribution of the surviving firms in 2000, it appears that a good number of those that were born with 0 employees have jumped to the class of firms with employees. In terms of the size in 2000, survivors with 0 employees represent only 33 per cent of the entrants in the 0-employee-class, whereas survivors with 1–2 employees and with 3 or more employees represent 72 per cent and 92 per cent of the entrants in classes 1–2 and 3 or more respectively. 6.2 Entrepreneur or self-employed Figure 6.3 gives a quite transparent picture of the inverse relationships between firms with and without workers. While net entry rates correlate positively among firms with only 1 or two workers and firms with 3 or more, the net entry rate of business with 0 employees presents an inverse correlation with the other two groups. It is interesting to observe that the difference is not between very small firms and the rest, the difference can be observed even between firms with 0 employees and firms with only one or two employees. A first interpretation of this fact is that both types of firms respond to different incentives and that a significant part of the 0-employee-businesses enter into and exit from self-employment depending on the job market situation dominated by firms that hire workers. It can be also observed that the evolution in the numbers of startups and exiting firms differs between the two groups of firms – the self-employed and small firms – and present an inverse relationship (Figures 6.4 and 6.5). One important qualification is that in the period

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1

0.11

0.9 0.8

0.10

0.19

0.23

0.20

0.7

0.25

0.6 0.5 0.4

0.69

0.3

0.68 0.56

0.2 0.1 0 Entries

Stock 0 empl.

Exits

1⫺2 empl.

3⫹ empl.

Figure 6.1 Demographic rates 1994–2000. Breakdown by size class Source: Directorio Central de Empresas, 2004.

0 empl.

1⫺2 empl.

0.43 0.33 0.48 0.72 0.55

3⫹ empl.

0.92 Initial size

Final size

Figure 6.2 Rate of surviving firms according to size class (firms created in 1994 and surviving in 2000) Source: Directorio Central de Empresas, 2004.

1994–2000 the business cycle was in an expansionary phase, thus, it is not possible to observe the impact of the whole business cycle on the relative behavior of self-employed and small businesses. 6.3 Correlation test The correlation tests performed with a panel of 40 industries (manufacturing and services) and eight years from 1994 to 2001 confirms the information given in the graphic analysis. The technique used is a panel


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0.08 0.06 0.04 0.02 0.00 ⫺0.02 ⫺0.04 ⫺0.06 1994

1995

1996

1997

0 empl.

1998

1 or 2

1999

2000

3⫹

Figure 6.3 Net entry rates Source: Directorio Central de Empresas, 2004.

150 140 130 120 110 100 90 80 70 60 1994

1995

1996

1997

0 empl.

1998 1 or 2

1999

2000

3⫹

Figure 6.4 Evolution: number new firms Source: Directorio Central de Empresas, 2004.

regression with fixed effects that controls for the specific effects of each industry on net entries. The objective is to compare the signs and significance (not the value) of the coefficients of the regressions. Table 6.1 demonstrates that net entry rates vary in opposite direction in firms with 0 and firms with only 1 or 2 employees. Table 6.2 shows the same divergent behavior between firms with 0 and firms with 3 or more employees. Table 6.3 shows that net entry rates vary in the same direction, with the

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120 110 100 90 80 70 60 50 40 1994

1995

1996

1997

0 empl.

1998 1 or 2

1999

2000

3⫹

Figure 6.5 Evolution: number exiting firms Source: Directorio Central de Empresas, 2004. Table 6.1 Net entry (with 0 employees) Dependent variable

Net entry 0 employees

Constant

0.3094∗∗∗ (10.07)

Net entry with 1 or 2 employees

−0.2767*** (−3.72)

F test (p value)

p < 0.0002

Number of observations: 320 Notes: Statistically significant at: 1%(***). t-values in parenthesis.

same sign, between firms with only one or two employees and firms with more than three employees. A reasonable interpretation for the three correlations is that the decision to hire employees makes a strong difference in the type of firm. It is sensible to treat the group of solo-employment entrants as a different group that react in a contrary way to those economic stimuli that govern entry and exit in firms with employees. When net entry is higher in firms with employees because there are better opportunities for the survival of firms, self-employed businesses present lower net entry rates. This fact is compatible with the idea that most self-employed businesses are not in the category of entrepreneurs but simply trying to make a living. This conclusion is coherent with the European Commission (2002) study that


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Table 6.2 Net entry (with 0 employees) Dependent variable

Net entry 0 employees

Constant

0.0438∗∗∗ (11.21)

Net entry 3 or more employees

−0.8720∗∗∗ (−5.29) p < 0.0000

F test (p value) Number of observations: 320 Notes: Statistically significant at: 1% (***). t-values in parenthesis.

Table 6.3 Net entry (with 1–2 or more employees) Dependent variable

Net entry 1 or 2 employees

Constant

−0.1959∗∗∗ (−7.61)

Net entry 3 or more employees

1.3707∗∗∗ 12.64

F test (p value)

p < 0.0000

Number of observations: 320 Notes: Statistically significant at: 1%(***). t-values in parenthesis.

concludes that individual enterprise proprietorship tends to exit from the market when employment opportunities in the labor market improve.

7. Conclusions Recent studies have sought to link entrepreneurship to economic performance. This has generated a set of results shrouded in ambiguities. This chapter has sought to identify at least one reason for the ambiguous findings in the entrepreneurship literature – the heterogeneity inherent in the most prevalent measures of entrepreneurial activity. Studies linking entrepreneurship to economic performance typically include in a single measure firms across a fairly wide spectrum. Using data from Spain, the results of this chapter indicate that the behavior of the self-employed businesses is distinctly different, and in some cases orthogonal to the behavior of small businesses that have at least some employees. This suggests that entrepreneurship is very much a heterogeneous phenomenon. It may be that the only way to unravel the links between entrepreurship and economic performance is by undertaking analyses at a considerably

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less aggregated level. This of course, will make cross-national comparisons even more difficult. But the challenge for future research is to find meaningful units of analysis in the quest for identifying the economic contributions of entrepreneurship. The problem of finding ways to distinguish between the different types of new firms is a relevant aspect. If the contribution to growth and welfare depends upon the predominant nature of each particular firm – innovative, imitative, basic survival, meeting local demand for goods and services, among others – this means that the importance of market failures depends also on the type of firms, and this has direct implications for policy analysis and design. In this sense, it is desirably to organize programs that promote entrepreneurship according to its key role in economic development, and to its contribution to economic welfare through employment generation. Until the early 1990s, the main objective of policies for enterprise creation was the setting up of specific incentives and mechanisms; current measures combine support incentives and services (e.g. information, formation). Besides, public support is centered on generating a socioeconomic environment that is favorable to innovation and change. For instance, the European Commission, in its study Business Demography in Europe (2002) concludes that, except in specific cases, public financial support does not play an important role in firm creation, whereas informal capital markets and support services do. Since new enterprises form a heterogeneous group, it is consequent for policies to take this into account. It is important to reinforce the management, innovation and internationalization capacity of enterprises. Success depends on the quantity and quality of firms’ internal resources (human resources and physical and financial resources) as well as on the external resources that the economic environment proportionates (e.g. cooperation networks, technology access, market access, efficient suppliers and advanced services). As small enterprises present dissimilar internal resources in as much as they also have different capacities to benefit from the resources of their environment, it becomes very important to set up policies that take into account this heterogeneity.

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7 Competitiveness Based on Low Production Costs or on High Specialization and Productivity: The Case of SMEs in Costa Rica Justo Aguilar and Maikol Elizondo

1. Introduction The global economic recession that took place in the early 1980s affected Costa Rica’s growth conditions due to the disproportionate increment in the fossil fuels bill and the fragility of the exports level. The presence of socio-political conflicts in Guatemala, El Salvador and Nicaragua complicated the regional economy even more and all of this was reflected in low real Gross Domestic Product (GDP) growth rates and in the persistence of problems in external payments. In 1985, Costa Rica’s government negotiated a structural adjustment program with the World Bank and this supported the establishment of an export promotion strategy instead of the imports substitution strategy that had been implemented beforehand. Under the new system, the current tariff protection was dismantled and the economy was deregulated in a scheme of competition promotion, and at the same time exports were promoted to markets different from those that were part of the Central American region. The new strategy assumed international commerce and competition as the forces behind productive factor reallocation to the sectors that were ready to participate in the global economy. The government immediately set in motion an industrial reconversion program and an incentive system to redirect the sales of the manufacturing firms to the new markets. In this context, the small and medium enterprises (SMEs) were a crucial element in the country’s export 138

Justo Aguilar and Maikol Elizondo 139

development, in particular during its initial phase, since 1986 (Aguilar et al., 1998). In the earlier period the policy framework promoted an exports scheme based on big enterprises and transnational companies, mainly within industrial and agricultural sectors. SMEs constituted a source of employment for the less dynamic and less specialized sector of the economy, which represented a segment of subsistence producers. Twenty years after the economic reform process was initiated, the country shows a very different productive structure, with an important component of services and the production of high technology pieces, including sectors like production of microprocessors, medicines, and accessories for health attention. SMEs are today fundamental in the country’s development scheme and represent a source of opportunities for development in terms of innovation, knowledge generation and entrepreneurial capacity. The international literature addressing the subject of SMEs (see Ulate, 2001) allows visualizing them as fundamental in two different ways: the first makes reference to them as units that generate employment; and the second defines the role of the SMEs as entities that promote innovation and efficiency in the productive systems. The hypothesis stated in this article is that SMEs constitute an important source of employment in Costa Rica insofar as they operate at an intermediate level between a competition based on low production costs and schemes of competition where specialization and productivity improvements are the most important elements. To contrast this work hypothesis, the results of previous studies of the Institute for Research in Economic Sciences (IICE) of the University of Costa Rica are considered. Registries of the Costa Rican Institute for Social Insurance1 (CCSS) are also utilized with the purpose of determining the number of establishments that report entrepreneurial activities, as well as the Technological Strategies and Entrepreneurial Performance Survey of the same Institute. For the analysis of the information a non-parametric procedure called Homogeneity Analysis (HOMALS) is used. This chapter is organized in six sections: the first presents the context, hypotheses, definitions and justifications of the subject; subsequently, in sections two and three the theory supporting the study is presented as well as the analysis methodology; sections four and five show the results of the investigation; finally section six presents a discussion of the main results and the political measures that follow these results.

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2. Theory and antecedents: innovation and its relation with value generation 2.1 Traditional SMEs vs non-traditional SMEs Traditionally in Latin America SMEs have been seen as a source of employment, while in developed countries the prevailing vision considers them not only as employment-generating units, but also as units of change that may have a deep impact in overall economic efficiency. A typology of SMEs that supports this affirmation was formulated by the University of Ferrara (Consorzio Ferrara Ricerche, 1998). Within it, Japanese SMEs are classified as ‘global subcontractors’ because of their participation in international production and for their direct investments outside of Japan. Italian SMEs are inserted in successful ‘industrial districts’ because they are concentrated in one sector and in one specific geographical area; although their relations are local, these enterprises put together collective actions with the purpose of augmenting the efficiency of the whole group. On the other hand, most of these districts are export-oriented. An intermediate segment of successful SMEs exists in economies of recent industrialization; these are defined ‘traditional subcontractors’ in the case of Korea, and ‘medium-sized niche enterprises’ in the case of Singapore. Finally, there are SMEs of a lower level, associated with developing countries. These are urban family businesses and rural family businesses. The first are family-owned businesses that use relatives as workers; most of them operate within the informal sector. Their competitiveness is based on low labor costs rather than on high specialization and productivity. This is why their ability to extend commercial relations outside the national market is very limited. The second are enterprises that play a very important role in the generation of employment and in assuring the subsistence of these families; for this reason, these firms adopt very simple production systems that are (family) labor-intensive; this strategy helps them complement incomes gained within agricultural activities. This definition is consistent with the type of enterprises that typically operate in Latin America; according to the analysis provided by Kantis and Angelelli (see Chapter 4 in this volume), Latin America is known for being in the bottom positions of technological achievement ranking. This variety of typologies and definitions provide a good analytical framework to respond to the question related to the advantage of Costa Rican SMEs; are these based on low labor costs or on competitiveness gained through high specialization and productivity?


2.2 The size of businesses and their technology The quality of products, marketing and distribution channels, price strategies, managerial capacity and organizational structure can be mentioned as some of the most important factors that help improve the performance of businesses. However, it is considered that technology plays an essential role, on a global level, for the development of businesses, and on a more particular level, for each of the above-mentioned factors. The strategy of developing new products and techniques faster than competitors provides an advantage that, if exploited properly, can help firms to reach local and international markets. In relation to the question of which group of enterprises (whether large-sized or small-sized) is better equipped to conquer export markets, Gentzoglanis (1994) suggests that the size of the firm is fundamental. This is a vision followed by authors who adopt a mainstream economic approach. An enterprise can achieve production costs savings by augmenting its size (i.e. scale economies); thus, if small, the size of an enterprise can negatively affect the performance because it restricts the possibility of generating scale economies and of using strategies of pricebased competition. In this sense, the focus of Schumpeter (1935) is consistent, given that he supports the idea that only large enterprises are able to generate new technologies. This hypothesis helps us to infer that small-sized firms need pass through a growth process associated with their production scale and to enter international markets in order to acquire new techniques and technologies. In contrast, there are recent arguments in favor of the larger relative flexibility of small-sized enterprises in adapting/imitating technologies, in generating products for specific customers (Abraão, 2001), and in taking advantage of new ways of conducting businesses in growing market niches. Alternatively, big enterprises are presented as less flexible in their response capacity to sudden changes in business tendencies (Yong, 2003). In other words, the technological conditions make the growth patterns of small enterprises change considerably, given that there is a technological background utilized by these firms, and that being relatively smaller allows them to be part of a faster adaptation and adjustment process. According to Porter (1996), this is one of the main advantages of the SME sector. This is precisely the case of enterprises in high technology industries (see Schweitzer and DiTommaso, Chapter 3 in this volume). In this sector (e.g. biotech industry), the proportion of large firms may be much smaller than in other sectors where innovation development results are less accelerated.

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This framework also considers that, investing in R&D activities, be these formal, informal (technological adaptation) or outsourced from specialized expertise, results in more technically sophisticated products that in many cases are also price competitive. Innovation is then a fundamental element for a good performance of small firms. In this sense, Vernon’s arguments (1966) in favor of the larger potentials for innovation in small firms are highly valid today, given that smaller size facilitates the modification of the production process when dealing with a relatively minor technology substitution more than in the case of larger firms. This is why the hypothesis of the positive relation between smaller firm size and higher innovation rates may apply. Taking into account Chamberlain’s contributions on monopolistic competition, Hart (1985) presents the desire to obtain market power as the motivation for enterprises to differentiate their production system either through technological improvement directed to increase productivity or to differentiate products. Although entrepreneurial innovation is important, economists still debate about the factors that incite people to become entrepreneurs (see for, example, Audretsch et al. (Ch. 6) in this volume). It is recognized that entrepreneurial innovation occurs when new technologies and scientific developments generate economic opportunities captured by entrepreneurs; small, dynamic and rapidly growing businesses that emerge in the market become the primary engine for innovation (Freeman et al., 1982, cited by Gentzoglanis, 1994). At the same time, a fundamental element that promotes improvements in efficiency is international pressure caused by the reductions of trade protection for national firms (Lizano, 2003). For Alavi (1997), citated by Yoguel (1997), international competition is conceived as the ability of the entrepreneurs to design, produce and sell their products in a better manner than their competitors (in local and external markets). When national firms are exposed to international competition, the price system signals where the resources should be directed. The interaction of the price system, together with the national supply integrated with international supply, constitutes a mechanism that allows society to optimize the use of resources, thus improving the efficiency of the production system (Chun, 2004). Besides, according to Yong (2003), international neworking helps spread technology and promote outsourcing to local industries. These aspects are especially important because, as it will be presented in this study, Costa Rican SMEs are characterized as traditional enterprises that provide important sources of employment (Ulate, 2001;


Yong, 2003). Although they are traditional, they show a profile that is comparable to that of SMEs based in countries with higher development levels.

3. Analysis methodology and information This work is based on previous studies developed by the Institute for Research in Economic Sciences (IICE) of the University of Costa Rica (see for example Aguilar et al., 1998, Ulate, 2001, Aguilar et al. 2003 and Yong, 2003), the Technological Strategies and Entrepreneurial Performance Survey of the same institute, and registries of the Costa Rican Institute for Social Insurance (CCSS) with the purpose of determining the number of establishments that report entrepreneurial activities. For the analysis of the information a non-parametric procedure called Homogeneity Analysis (HOMALS) is utilized in order to detect behavior patterns related to the firms’ performance and internal characteristics. Concerning the information used in this study, two limitations are presented: first, the problem of the information registries of CCSS is that informal entrepreneurial activities are left out. Estimations by Trejos (1999) indicate that informal productive units represent a sector as important as the formal one, in the case of micro and small businesses. Second, in the service sector data include services provided by government agencies (Ulate, 2001), which also implies a distortion, even though it should not be important considering the fact that these dependencies generally employ over a hundred workers and productive units with that size are not considered in this study. 3.1 Statistical analysis A multidimensional optimal escalating analysis (HOMALS) is used as a statistical procedure to study the answers of IICE’s survey. HOMALS is a non-parametric statistical method implemented to quantify nominal variables, giving numeric values to qualitative data in a reduced dimension space (Bryan, 1994; Katz, 1999). The objective is to synthesize through a standardized qualitative measure (with mean equal to 0 and standard deviation equal to 1) the perception that the interviewed entrepreneurs have about their technology, the qualification of their personnel and the development of their firm. Specifically, using the HOMALS procedure we analyse the following variables:

• Quali-10 categ: How the entrepreneurs evaluate the qualifications of their personnel using a scale from 0 to 10.

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• Sist. Capacit: Presence or absence of formal training systems for the personnel of the SME.

• Tec. Today: How the entrepreneurs evaluate the quality of the technology they use at the moment of the interview using a scale from 0 to 10. • Tec. 2 Years: How the entrepreneurs evaluate the technology they will use in the following 2 years. The purpose of this kind of analysis is to obtain information about the non-lineal correlations between these variables, detecting homogeneous groups of variables and special behavior patterns. This procedure is conceptually very similar to the analysis of principal components, considering that it uses a minor group that synthesizes a series of variables as a mechanism to reduce the amount of information available. The difference is that it is applicable to non-quantitative measures. Furthermore, and given that the statistic method generates standardized values, it is possible to consider the values that summarize the information of the survey as indexes in each dimension. In this way, it is expected to summarize the information related to the qualification of the personnel in a first dimension of analysis that will be called ‘Qualification of the Personnel Index’. The second dimension of analysis will be called ‘Technological Development Index’ and includes the information associated to the opinion of the entrepreneurs about the technology used in their production processes at the day of the interview (Tec. Today) and the actual technology evaluated for the next 2 years (Tec. 2 Years), which allows, through the average of these two indexes, to construct a ‘Combined Qual-Tech Index’;2 this may help ranking the interviewed enterprises by magnitude. 3.2 The information The search for information from primary sources took place during the first semester of the year 2001.3 A questionnaire that separates exporting enterprises from non-exporting enterprises was used. In the selection of the size of the sample the opinion of the sector’s experts was considered, alongside the available economic and time resources; therefore the sample is not probabilistic. Nevertheless, the selection of the sample units was done randomly in each stratum (firms of the same size). In total 796 enterprises with less than 100 employees were interviewed (SMEs). The distribution of the interviewed firms by stratum and economic activity is presented in Tables 7.1 and 7.2. Data are proportional to distribution at the national level.

Justo Aguilar and Maikol Elizondo 145 Table 7.1 Number of interviewed enterprises (SME) Sector

Exporting firms

Non-exporting firms

Total sample

Manufacturing Agriculture Commerce Services

138 74 40 12

105 49 309 69

243 123 349 81

Total

264

532

796

Source: Technological Strategies and Entrepreneurial Performance Survey, IICE, 2001.

Table 7.2 Number of interviewed enterprises by size

Categories Microenterprises Small enterprises Medium enterprises Total

Number of employees

Exporting firms

Non-exporting firms

Total

1–5 6–30 31–99

30 124 110

319 172 41

349 296 151

264

532

796

Source: Technological Strategies and Entrepreneurial Performance Survey, IICE, 2001.

The questionnaire for non-exporting enterprises was organized in six independent modules: a first module of general information about the firm (address, telephone numbers, productive sector, etc.); a second module regarding the firm’s personnel (7 questions); a third module dedicated to the information related to production and sales (12 questions); a module for the productive process (9 questions); a fifth module concerning the specific markets that demand production (4 questions); another one dedicated to studying the expectations of firms for the following years (3 questions); and finally, a module for the subject of the financial environment (35 questions). The survey for the exporting enterprises was structured in the same way as the one directed to the non-exporting firms, but it has 13 additional questions in relation to the destiny market of exports.

4. Results: What are Costa Rican SMEs dedicated to? The data from social security about the economy’s formal sector shows that the tertiary sector (commerce and services) is the biggest, representing a 76 percent of the microenterprises, 56 percent and 46 percent of the small and medium enterprises respectively, being more important than the service sector for the segment of micro and medium enterprises. Those activities include education, data processing systems,

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professional consulting, small professional cells (activities that emerged at the end of the 1980s) and in general activities that are intensive in qualified human capital. The analysis focuses on the formal sector4 of the economy, for the data suggest that those who are dedicated to these activities do not necessarily try to solve an employment problem, but because of better professional (economic) perspectives when working in independent activities rather than in large firms. The relative importance of the manufacturing sector is higher when we refer to medium or small enterprises (19 percent and 17 percent respectively); however, it also constitutes an important economic sector for microenterprises (8 percent in total). This information suggests that the SMEs in the manufacturing sector prefer maintaining their activities on a scale that provides them with a relevant participation in the internal market insofar as it helps them to dedicate a good part of their production to international markets (Aguilar, 2003). Agriculture is a sector that increases its relative participation when going from small to mediumsized enterprises, growing from a 14 percent to 21 percent of the total for this category. If we go from the small to the medium-sized category, the concentration of manufacturing and agricultural firms is higher in comparison with the services sector, even though the latter is still predominant. These results confirm that the relative distribution of SMEs is different in each economic sector. In terms of employment, the data from CCSS reveals that a 59 percent of the total is located in the SMEs, and this sector generates more new jobs than large enterprises. This trend has modified the composition of employment in favor of the SMEs. This is demonstrated by SME contribution on total employment in 1997, which was approximately 46 percent. Montiel (2000) shows that in 2000, eight of every 10 new jobs were generated by SMEs. These results support the thesis that Costa Rican SMEs are still a very important source of employment, affirmation that is maintained in the study of Ulate (2001). Nevertheless, their orientation to professional services such as medical consulting, legal consulting, and other professional offices are evidence that SMEs are directed of participating in the market through competition schemes oriented to specialization and productivity. According to the estimations of Trejos (1999), during the period 1994– 98, informal micro and small enterprises generated 27 percent of the new jobs whereas formal micro and small enterprises created 21 percent. This suggests that at the same time SMEs were emerging in high value-added activities, there is a subsistence sector, which according to Trejos (1999) reaches 13 percent of total employment.

Justo Aguilar and Maikol Elizondo 147 Table 7.3 Discrimination measures and eigenvalues Variable Eigenvalues Sales Quali-10 categ Sist. Capacit. Tec. Today Tec. 2 Years

Dimension 1

Dimension 2

0.402 0.512 0.586 0.515 0.191 0.205

0.360 0.159 0.398 0.004 0.613 0.626

5. Costa Rican SMEs: Competition based on low labor costs or on high specialization and productivity? The methodology applied in this study allows defining two types of SMEs: a first group with a (transversal) tendency directed to improve the qualification of their personnel and to update their technology; and a second group of SMEs that neither invest in training for their human capital nor in improvements in productivity through technology updating. The eigenvalues indicate the amount of information summarized by the HOMALS procedure, being this approximately 40 percent. The information regarding the classification of the SMEs in function of the Qual-Tech Combined Index is presented in Table 7.4.

6. Discussion Using the non-parametric multidimensional optimal escalating procedure, the studied 796 SMEs have been classified in two categories: the first category is a group of SMEs (60 percent of the total which equals to 480 enterprises) with negative indexes in any of the considered areas, competing in the market with low production costs generated by small investments in technology and by hiring unskilled personnel. These constitute productive units that create employment in the national economy, but do not represent a source of productive efficiency. These characteristics are very clear in the first four deciles formed by enterprises with very low technology and training indexes compared with the average of the studied SMEs. The second category is formed by a group of SMEs (40 percent of the total) with positive indexes that are higher than the sample’s average, hiring personnel with a better professional profile and investing in technology. This group of enterprises is competing in the market by means of increasing specialization and productivity. These

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Table 7.4 SMEs organized by deciles according to the technology and qualifications combined index (QUAL-TEC) DECILES∗ 1

2

3

4

5

6

7

8

9

10

15 21 62 2

22 28 40 10

15 30 41 14

12 41 38 9

17 25 45 13

13 26 52 9

11 35 43 11

15 33 38 14

7 30 49 14

43 38 19

42 40 18

50 35 15

32 50 18

43 36 20

35 33 32

30 39 31

47 31 22

Productive Sector (%) Agriculture Manufacturing Commerce Services

6 29 63 2

Size of the SMEs (Employees) (%) 1 to 5 6 to 30 31 to 99

75 20 5

57 30 13

Technological Index Average Dispersionb

−0.601 −0.646 −0.565 −0.379 −0.280 −0.270 0.211 0.093 0.508 2.160 0.405 0.563 0.497 0.564 0.590 0.632 0.789 0.791 0.893 1.080

Qualification of the Personnel Index Average Dispersionb

−1.924 −0.980 −0.522 −0.306 0.002 0.584 0.653 0.489 0.587 0.609

0.340 0.253 0.800 1.084 0.790 0.643 0.784 0.826 0.840 0.816

Combined Qual-Tech Index Average Dispersionb

−1.262 −0.813 −0.544 −0.343 −0.142 0.034 0.232 0.449 0.796 1.140 0.172 0.098 0.063 0.062 0.047 0.062 0.044 0.089 0.119 0.311

Has training programs (%)a Yes No

1.330 3.8 98.670 96.2

2.5 97.5

13.8 86.2

20 80

27 73

22.5 77.5

47.5 52.5

66 34

48.7 51.3

7.5 2.92

8.027 2.83

Qualification of the Personnela Average Dispersionb

1.590 3.653 1.450 2.859

5.561 6.684 2.94 2.926

6.75 2.97

7.06 7.734 7.886 2.946 2.876 2.665

Qualification of Technology Today a Average Dispersionb

6.110 1.433

6.75 6.72 7.05 7.64 7.69 8.08 8.01 8.65 9.29 1.549 1.601 1.374 1.271 1.336 0.922 1.029 1.255 2.165

Qualification for the Technology in the next 2 yearsa Average 6.050 6.34 6.53 6.72 7.25 7.46 8.27 Dispersionb 1.272 1.383 1.765 1.484 1.469 1.342 1.33

8.05 8.56 9.33 1.568 1.611 2.122

Notes: ∗ From smallest to largest. a It refers to the questions specified previously. b Standard deviation has been used as a dispersion measure.

firms present good evaluation results for their technology at the time of the interview and for the use of technology they expected for the following 2 years (using the scale 0–10 they got over 8 points). In addition, the evaluation done by the managers in relation to the level of qualification of their personnel is found between 7 and 8 points on the scale 0–10.


Each of these groups and levels of qualification and technological development suggests that industrial policy in the SME sector should not be homogeneous; it should rather be oriented to achieve specific goals for each group of firms as it is proposed by Scheweitzer and DiTommaso (see Chapter 3 in this volume) in the case of small businesses operating in the high technology sector. Simultaneously, giving clear and differentiated incentives to groups of enterprises competing by means of increasing productivity, which is the case of technological businesses, helps to block the flow of human capital going outside the country (ibid.) and generates dynamism through the creation of more specialized entrepreneurial webs, given that these types of enterprises tend to strengthen together by forming clusters of firms (ibid.). The classification scheme and the classification that results from this study shows that Costa Rican SMEs are moving from a competition based on low labor costs to a form of competition based on increasing specialization and productivity. With the information obtained from the registries of the CCSS, it is possible to conclude that SMEs represent a more dynamic sector than that formed by large firms; they show a more significant growth and therefore, gain economic relevance in the productive structure of the economy. A hypothesis can be stated in this sense in relation to the formal segment of SMEs that show capacity to accumulate value and to be innovative and dynamic; a very different trend from what is going on with businesses in the informal sector. Table 7.4 also shows that the competitiveness profile based on low labor costs is mainly a microenterprise profile, which can be explained by the difficulties that small and medium enterprises have to deal with in terms of credit access, and logistic support programs as legal formalization and exporting. These difficulties are widely treated in the studies by Manoel de Madeiros (1994), Camacho (1994), Garcia and Paredes (2001), Meyer-Stamer and Waltring (2002) and López (1994), among others. This study does not provide evidence of the causality direction between growth in the productive units and their levels of technology and the qualification of their personnel. In other words, using the HOMALS method it is not clear if improvements in technology and qualifications are a consequence of growth in the size of productive units, or if these improvements in technology are the cause of the growth in the size of the enterprises. Theoretically, considering what has been presented by authors such as Abraão 2001, Meyer-Stamer and Waltring (2002) and Yong (2003), it is possible to support this latter hypothesis, and it can be concluded that adequate policy guidance may strengthen and improve the qualifications of the personnel and the technology adopted by SMEs.

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In this sense, the efforts of public policy should be oriented to support training programs, credit access and technological updating projects and initiatives for SMEs, given that their success depends on these internal characteristics.

References Abraão, L. (2001), ‘Chamberlain on Product Deferentiation, Market Structure and Competition: an Essay’, Working paper No. 105; Facultade de Economia, Unversidade do Porto, May. Aguilar, J., Cordero, J.A. and Trejos, S. (1998), ‘Estrategias Tecnológicas y Desempeño Exportador de la Pequeña y Mediana Empresa: el Caso de Costa Rica’, Instituto de Investigaciones Económicas de la Universidad de Costa Rica (IICE); Serie Divulgación Económica No. 32, 1998. Aguilar, J., Elizondo, M. and Zárate L. (2003), ‘Políticas públicas y desempeño de las pequeñas y medianas epresas manufactureras de Costa Rica’, Documento de Trabajo IICE-Instituto de Investigaciones en Ciencias Económicas, Mimeo. Bryan, F. (1994), Multivariate Statistical Methods, Chapman & Hall/CRC. Camacho, A. (1994), ‘La Experiencia en el Financiamiento de la Pequeña y Mediana Empresa en Costa Rica’, CEPAL, Serie Financiamiento del Desarrollo no. 17. CEPAL (1999), ‘La Pyme en Centroamérica y su Vinculación con el Sector Externo’,Comisión Económica para América Latina (cepal), lc/mex/l.404, Santiago. Chun, S. (2004), ‘Trade, Product Cycles and Inequality Within and Between Countries’, W.P. Department of Economics, Michigan State University, February. Consorzio Ferrara Ricerche (1998), The role of SME: Asian and European Experiences, AESMEC, University of Ferrara, Naples, May. Gentzoglanis, A. (1994), ‘Competitive Strategies, Innovation and Export Performance of SMEs’, University of Sherbrooke, Mimeo. García, G. and Paredes, V. (2001), ‘Programas de Apoyo a las Micro, Pequñas y Medianas Empresas en México, 1995–2000’, CEPAL, Serie de Desarrollo Productivo no. 115, December. Hart, O. (1985), ‘Monopolistic competition in the spirit of Chamberlain: a general model’, Review of Economic Studies, Vol. 52. Katz, M. (1999), Multivariable Analysis, Cambridge University Press. Lizano, E. (2003), ‘Costa Rica y el Proceso de Inserción en los Mercados Internacionales’, paper presented in the Seminar on the Free Trade Agreement between Central America and the US, Academia de Centramérica, Mayo. López, M. (1994), ‘El Financiamiento de la Pequeña y Mediana Empresa en América Latina’, Report, Programa de las Naciones Unidas para el Desarrollo (PNUD). Manoel de Medeiros, C. (1994), ‘Empresas de Menor Tamaño Relativo: Algunas Características del Sector Brasileño’, CEPAL, Serie Financiamiento del Desarrollo no. 15, Santiago. Meyer-Stamer, J. and Waltring, F. (2002), ‘Innovación Tecnológica y Perfeccionamiento de las Pequeñas y Medianas Empresas en la República Federal de

Justo Aguilar and Maikol Elizondo 151 Alemania: Incentivos y Financiamiento’,CEPAL, Serie Desarrollo Productivo no. 120, January, Santiago. Montiel, N. (2000), ‘Reformas económicas, mercado laboral y calidad de los empleos’, in A. Ulate (ed.), Empleo, crecimiento y equidad: el reto de las reformas de finales del siglo XX en Costa Rica, CEPAL-Editorial de la Universidad de Costa Rica, San Jose. Porter, M. (1996), Estrategia Competitiva: Técnicas para el Análisis de los Sectores Industriales y de la Competencia, México. Redding, S. (1996), ‘The Low-Skill, Low-Quality Trap: Strategic Complementarities between Human Capital and R&D’, Economic Journal, Vol. 106(435), March. Schumpeter, J. (1935), ‘The analysis of Economic Change’, Review of Economics Statistics, Vol 17(4), May. Trejos, J.D. (1999), ‘La microempresa de los noventa en Costa Rica’, Cuadernos de Trabajo no.2, PRONAMYPE. Proyecto Centroamericano PROMICRO-ILO, San José. Ulate, A. (2001), ‘El rol de las PYMES en Costa Rica: ¿generar empleo o acumular valor?’, Documento de Trabajo IICE-204, Instituto de Investigaciones en Ciencias Económicas. May. Vernon, R. (1966), ‘International Investment and International Trade in the Product Cycle’, Quarterly Journal of Economics, May. Yoguel, G. (1997), ‘Comercio internacional, competitividad y estrategias empresariales. El sendero evolutivo de la teoría’, Documento de trabajo no. 4, Universidad de General Sarmiento, B. Aires. Yong, M. (1998), ‘Estructura, desempeño, situación actual y perspectives de política para las pequeñas y medianas empresas industriales de Costa Rica’, Unidad Conjunta CEPAL/ONUDI. Proyecto BT-HOL 7093–1700. Yong, M. (2003), ‘Pequeñas y medianas empresas exportadoras de Costa Rica: hacia la superación de obstáculos en el camino de las oportunidades’, FUNDES, San Jose.


Part 4 Networking


8 Trust and Social Capital in Glo-cal Networks Lisa De Propris

1. Introduction The debate on clusters, industrial districts, regional innovation systems and innovative milieux has consolidated the belief that the competitiveness of firms and localities in many ways depends on the local accumulation of learning, competences and skills within a particular community, in a particular place, on a particular activity. The recognized advantages enjoyed by local production systems can be summed up as follows: (a) external economies associated with production specialization and the vertical integration of complementary production phases; (b) incremental innovation based on processes of learning and tacit knowledge; (c) inter-firm linkages facilitated by trust and social relations that develop in parallel with purely production transactions; and lastly, (d) the intricate web of economic and social relationships that are established in a social context having a recognized set of behavioural norms, customs and values that firms draw upon, generates social capital. Local accumulation is becoming, however, increasingly insufficient to maintain firms and localities on the frontier of knowledge and innovation; for this they need to combine local know-how and expertise with global inputs, information, and competences. The competitiveness of firms, localities and especially of what we can generally call local production systems, depends on their ability to have strong roots in the local embedded network of socio-economic linkages, and to engage with actors outside their locality and to create ‘glo-cal’ networks. When we speak of globalization, we often refer to the processes of internationalization of multinational enterprises which, depending on the opportunities provided, spread their productive activities across various 155

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localities worldwide. The globalization of small firms or local production systems, on the other hand, is nearly always solely associated with the expansion of their export markets. Local production systems are, in fact, rarely believed to be capable of expanding their competence and production network beyond the local boundaries, because small and medium sized firms’ limited competence (e.g. managerial or marketing) and financial means, in practice, restrict their investment possibilities. Besides, more interestingly given the aim of this contribution, another reason is related to the fact that their competitive advantages are perceived to be location-specific. In fact, production specialization, trust, the acquisition of knowledge, learning and social capital are all deemed to be rooted in the local system and are specific to the system itself. The importance of local production systems to engage in ‘glo-cal’ networks must not be underestimated, nor must it be dismissed on the basis that local advantages have in some cases enabled them to become leaders in market niches overseas. In fact, as is the case with multinational firms, the systemic growth of local production systems becomes an imperative whenever new product or geographical market possibilities are explored and, more importantly, when new complementary and substitutive competences are sought. Instead it would be desirable for local production systems to establish productive relations with actors outside their system and to create, for instance, multinational webs (Cowling and Sudgen, 1999) or multinational networks of production systems (De Propris et al., 2007). These can be seen as a mesh of local production systems that are cemented by production and economic relations that can involve groupings of industrial districts or clusters. The latter are prompted to connect by the necessity to exchange knowledge and information and to reach areas of specific competence. The internationalization and openness of local production systems coincide with the development of strong bridging relationships beyond agents’ comfort zone and familiar proximity. One possible risk is for this to undermine the foundations on which such systems are built, this being related to trust, embeddedness and social capital. The chapter explores the concepts of systemic trust and social capital in order to explain the sustainability of ‘untraded interdependency’ within the local network of socio-economic linkages. We would argue that such concepts are, however, inappropriate to describe the glue that links agents/firms when operating in a global or, in any case, in an a-local network of multifaceted, multi-scalar relationships. For this, we

Lisa De Propris 157

introduce the idea that other forms of trust and social capital need to be considered: network trust and network capital.

2. From calculative trust to systemic trust In the sociological discourse, and more recently in the discourse of economics, trust has been defined in many ways (Lane, 1998; Nooteboom, 2002), which we would streamline in two main categories depending on two distinct behavioural hypotheses: calculative trust and systemic trust. ‘Calculative trust’ (see Lane, 1998 for an alternative definition) presumes that the individual is primarily opportunistic and that he/she will be prompted to cooperate only by the prospect of personal interest. It draws on economic models for its theoretical formulation and is founded on three main concepts, i.e. rational choice theory, contract theory, and transaction cost theory. It also utilizes game theory as a theoretical tool. Conversely, systemic trust is rooted in the belief that the individual is driven by sentiments of reciprocity and altruism and that therefore he/she is prompted to relate to others by such sentiments as empathy (Nooteboom, 2002). Systemic trust draws on disciplines such as psychology and sociology that see individual behaviours and decision making as being prompted by factors that transcend rational calculation, but that depend instead on a complex set of contextual and environmental factors. In particular, calculative trust is indebted to Hobbes’ theories on human nature, and finds expression in Williamson’s assumption of opportunism and in the formulation of the prisoner’s dilemma. In fact, in this framework, social bonding and cooperation arise solely either in the presence of a third party, the leviathan, or as a result of individuals’ self interest. Calculative trust presents two key analytical components. Firstly, it is based on the assumption that individuals are by nature selfish and opportunistic; that their sole motive is self-interest and that they will attempt to maximize their advantages even at the cost of damaging other parties. Secondly, it is based on the belief that trust relationships occur in market conditions that are characterized by uncertainty and information asymmetry. This means that the set-up of trust relationships relies on mechanisms that minimize the risks for the weaker party, i.e. the trustor. Williamson (1996) argues that since opportunism and incomplete contracts (under the assumption of uncertainty and bounded rationality) make market transactions costly, organizations emerge to reduce such costs. More recently, Williamson (1996) accepted that the dichotomy between market and hierarchy had been bridged by the existence of

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hybrid forms of market, where nonetheless there is no room for trust or altruism in economic relations. This consolidated belief is reflected in the theory of contracts and in the development of game theory. Since Axelrod’s contribution (1884), trust has been known to play a key role in a context of uncertainty; the fact that two subjects might commit to a mutually profitable relationship – such as a cooperative relationship – even if presented with an alternative strategy that guarantees major payoffs, has been put down to trust. The selfish drive behind trust can be described in situations where players’ cooperative choices are formulated in a context like that described by the prisoner’s dilemma. Here the lack of trust and the selfishness of players are such that a suboptimal outcome is likely to emerge if the game is played once and for all. Conversely, the theory suggests that the repetition of a non-cooperative game can lead to a cooperative solution, albeit not a necessarily stable one.1 In other words, cooperation here is driven not by trust but by selfish interests. Also Good (1988) argues that a cooperative behaviour is not always necessarily prompted by a cooperative frame of mind, but it could be the result of a calculation where short-term cooperation is driven by the expected payoff resulting from being egoistic in the longer term. Calculative trust can be created, if incentives are good, only if payoffs are distributed in such a way as to maintain cooperation and guarantee sustained interaction. Paldam (2000) shows that, in the prisoner’s dilemma, even when payoff distribution is altered in such a way as to encourage a cooperative behaviour (by subsidizing cooperative behaviours so that cooperative strategies provide better payoffs than non-cooperative ones), selfish subjects ultimately opt for the non-cooperative strategy. In economic theory, therefore, trust is equal to cooperation. This simplification can be explained by the need for economics to handle phenomena that can be measured and theorized upon. However, in so doing, one loses sight of the difference between the two stages of the cooperative relationship: the expectation of trust and the realization of trust. These two stages are distinct and separate, and because of the circularity of trust and cooperation, they do not fit into a prescribed order. It will be discussed later that the study of trust from a multidisciplinary perspective brings this distinction into sharp focus, however, precisely because it shows that cooperation can occur when trust is absent but coercion is present, and that trust can occur before cooperation is established. We have already noted that ‘calculative trust’ supposes that an individual will choose whether to trust or not on the basis of a rational evaluation of his counterpart. However, this does not mean that trust is based on a simple probabilistic calculation, whereby trust is seen as the

Lisa De Propris 159

probability of one’s expectations with respect to the behaviour of another agent being realized. Indeed, if this were the case, then trust would increase with such a probability up to a point when the latter will be equal one. It is impossible, however, to be certain about somebody’s behaviour, because market relations are always fraught with uncertainty that entails a certain amount of risk. It is argued, therefore, that trust is essential to a relationship only when the uncertain behaviour of one of the partners is felt to put the realization of the desired outcome at stake (Pettit, 1995 in Nooteboom, 2002). Nooteboom (2002) and Dasgupta (1988) also believe that trust is inevitably fraught with uncertainty: Dasgupta goes so far as to say that if the trustor could monitor the trustee’s actions before deciding whether to trust or not, the word trust would lose its ‘potency’ (p.51). Calculative trust, which in fact occurs in market conditions, is based on the belief that individuals operate in a context of uncertainty but also concedes that before they engage in a trust relationship, they go through a preparatory process which involves collecting information and observable data about their trustee: past experiences are evaluated, reputation is considered, comments and information of all kinds are reflected upon. This body of information helps the trustor decide whether the trustee is worthy of trust or not. It is worth mentioning at this point, that in a trust relationship the trustor is in the weaker position since dependent on the trustee. The latter, on the other hand, is in a stronger position because of being more informed (see the theories on information asymmetry and moral hazard) and therefore better able to exercise a subtle form of control over his counterpart. This explains why calculative trust is heavily dependent on dynamics, such as collecting information, that help to keep information asymmetry and uncertainty under control. The relationship between trust and information is nonetheless as complex as to generate a paradox: trust cannot exist without information, but at the same time trust means nothing with complete information (Pagden, 1988). In other words, if you know everything you do not need to trust, but if you know nothing at all it would not be reasonable to trust (Rimmel, 1989:299 in Mutti, 1998). The information discrepancy between trustor and trustee need not necessarily be bridged by the facts that the former has gleaned about the latter, but by whatever facts the trustee deliberately decides to reveal about himself (Bacharach and Gambetta, 2001) and by the reputation he enjoys and duly signals to his trustor (Dasgupta, 1988). Because of uncertainty and information asymmetry, if trust is to occur then the trustor must also establish ‘tolerance levels’ and set clearly defined limits about the kind of risk he/she is prepared to take

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(Nooteboom, 2002). In fact, Nooteboom insists that when two individuals do not know each other, then a trust relationship will be established only if it involves a limited commitment and a limited degree of risk. Only if this relationship is successful, is it then repeated possibly with greater trust and, thereby, risks. He also adds that at the beginning of a trust relationship, the trustor would have to activate safety mechanisms through, for example, the drawing up of contracts or, more generally, through the establishment of sanction mechanisms that act as a safety net in case of default.2 Lewick and Bunker (1996) describe the ‘stagewise evolution of trust’ from calculative to knowledge-based to normative trust, whereby after the initial pay-off driven stage, trust between agents is based on the acquired knowledge of each other as the relationship is in progress (this trust is also referred to as process-based trust, because it is underpinned by the realization of the trust-based interaction (see Sydow, 1998). Calculative trust can be seen as underpinning relationships extracted from a time–space context. The sustainability of these relationships is derived from agents’ incentive to maintain cooperation even in the presence of an incentive to breach such trust and maximize payoffs once and face retaliation afterwards. So time and the repetition of the interaction generate a sort of ‘relationship memory’ such that agents realize the benefit of cooperation. There are two fundamental problems related to calculative trust. The first involves the very foundations on which the concept of trust itself rests. If a trust relationship appears to depend heavily on power and control mechanisms for its realization, then we could argue that here we are not dealing with trust but with something else altogether. Some scholars have, in fact, argued that trust ought to make some modes of formal control, such as contracts, redundant. To be more specific, trust should be able to act as a substitute for contracts rather than the latter acting as the condition for trust to be realized. Das and Teng (2001) argue that a dependence relationship that relies heavily on control could in fact inhibit goodwill and competence trust in business relations. Bachmann (2001) insists that the fundamental difference between trust and control is that the former anticipates positive behaviour, whereas the latter expects a negative behaviour, thus activating ex ante power mechanisms. Lastly, Sako (1992 and 1998) argues that trust is pertinent to situations when extremely complex relations inhibit the stipulation of complete contracts, so much so that goodwill trust becomes, in such a case, far more important than what she terms contractual trust.3 Indeed, goodwill trust reflects the expectation of a certain behaviour where

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and when incomplete contracts leave agents discretion to act. Lyon and Mehta (1997) maintain that goodwill trust play a key role in formal contracts precisely because these are by nature always incomplete (including situations where a formal agreement has not been made). They also argue that too detailed contracts might actually undermine agents’ goodwill and generate an incentive for the trustee to behave in an opportunistic way. A further problem with calculative trust emerges from experimental economics. Studies have shown that people do not always appeal to reason when it comes to maximizing their payoffs but that, conversely, they have social preferences and that, more generally, they tend to let themselves be guided in their choices by social rules, conventions and acts of reciprocity. Several applications of the ‘the trust game’ model (Berg et al., 1995) have shown that the level of both trust and trustworthiness depend heavily on individual factors (such as gender, race and personality), on social factors (such as education and social extraction) and contextual factors (depending on the rules of the game) (Glaeser et al., 2000; Burks et al., 2003). In other words, the experimental verification of the predictions of the prisoner’s dilemma (either one shot or repeated) has shown that the dynamics of agents’ decision-making are far too complex to be captured by rationality only. To this purely economic understanding of trust, an alternative can be drawn from models framed within the psychological and sociological disciplines; we shall call this ‘systemic trust’.4 The literature presents several definitions of trust. Firstly, the notion of generalized trust (or generalized morality as theorised by Parsons, 1951) is contrasted with specific trust. Then, there are such definitions as process-based trust, institutional trust, normative trust, social trust, emotional and obligational trust (Luhmann, 1979; Lane, 1998; Nooteboom, 2002). Lastly, there are also the three definitions of contractual, intentional and competence trust as conceived by Sako (1992). We introduce here the concept of systemic trust as associated with emotional and cognitive trust; it is rooted in attitudes such as empathy, reciprocity and morality; it assumes that the norm is to trust and be trustworthy, at least until such attitude is betrayed. While the origins of the cooperative behaviour associated with calculative trust can be found in self-interest on an individual level, and in authoritative coercion on an aggregate level (Nooteboom, 2002), the origins of the cooperative behaviour associated with systemic trust are to be sought in friendship and kinship on an individual level and in a sense of shared values and cultural norms on an aggregate level.

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Trust relationship can be motivated by reasons that transcend the purely economic factors, but draw instead upon social interaction and kinship; as well as can develop from customs and habits that have long been consolidated. Therefore, as such, trust relationships constitute the norm rather than the exception. Systemic trust is seen as being specific to situations where economic actors find themselves engaged in economic relations of a quasi-market nature (De Propris, 2001). These relations are deeply rooted in a complex and integrated social community. This is cemented by a set of shared behavioural norms, and civic and moral values, as well as by a sense of shared history and culture. This concept of trust echoes the local habit of mutual cooperation that, according to Dei Ottati (1994), characterizes relations between firms located in the Italian industrial districts. Historical, moral and cultural homogeneity inevitably creates an environment where individuals constantly witness accepted and familiar behaviours that reflect their own, so much so that this generates expectations in relation to mechanisms of prospective interaction. We refer here, in particular, to those expectations that generate cooperation on the basis of trust and reciprocity, in situations when, even though participants know very little about each other, they manage to establish trust relationships because ‘each trusts the other simply on the grounds that everyone else trusts’ (Luhmann, 1979: p.75). Within this conceptual framework, trust in economic relationships is not the result of individual calculations or of hierarchical constructions; nor does trust spring from an enforced sense of morality. It is, instead, born out of a deeply rooted sense of bonding and local embeddedness. In other words, while calculative trust was understood to be specific to dyadic and biunique relationships extracted from any social, cultural, and historical context,5 systemic trust considers relationships between agents where socio-economic personal factors are intertwined. This idea is also embraced by Fukuyama (1995), for whom trust is a set of ‘expectations that arises within a community of regular, honest, and cooperative behaviour, based on commonly shared norms, on the part of other members of that community’ (p.26). Implicit in Fukuyama’s definition is the idea that trust is born in contexts which provide individuals with the time, the space and the opportunity to get to know each other and that trust is therefore culturally determined. Calculative trust can explain on the spot cooperation, but cannot be the basis for ‘untraded interdependences’ in systems such as clusters, industrial districts or milieux, because it does not kick off a virtuous circle of trust. The sustainability of self-interest-driven cooperation depends

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on the repetition of the interaction and the balance between payoffs and punishment. Not only this, but along the process, agents also learn about each other and this reduces the uncertainty associated with the transaction. Over time, dyadic cooperation becomes the outcome not only of self-interest, but also of some form of knowledge-trust (Lewick and Bunker, 1996). On the contrary, systemic trust underpins trust-based relationships and cooperation that are embedded in a socio-culturalinstitutional context that provides an informal mechanism to create and maintain trust. For this reason, systemic trust can be the basis for ‘untraded interdependences’ in local systems.

3. Social capital The study of trust in economic relationships inevitably leads us to question the role of an aggregate of trust relationships on economic and social networks, i.e. social capital. Of the numerous definitions of social capital in the current literature, two seem to prevail in terms of significance and importance: relational capital and social capital. Glaeser et al. (2002: 438) define individual social capital as ‘a person’s social characteristics (. . .) which enable him to reap market and non-market returns from interactions with others.’ This definition is often referred to as individuals’ relational capital, since it comprises individuals’ set of relationships and networks. On the other hand, Putnam (1993: 167) defines social capital as ‘the features of social organization, such as trust, norms, and networks that can improve the efficiency of society by facilitating coordinated action’. Individuals’ social capital, namely relational capital, is framed within the economic discipline, as it is individualistic and payoff-driven. In particular, this economic approach draws on Bourdieu (1997) and Coleman (1988) and later on economists and geographers who apply optimum investment models to the study of social capital. From these studies, social capital emerges as a variant of human capital and, as such, is presented as a factor that contributes towards maximizing economic capital or towards maximizing individuals’ profits. Bourdieu (1997) defines social capital as a reward benefiting those who have participated in groups or social networks. As is the case with human capital, individuals can invest in social capital in the present by engaging in social interaction and accumulating social links, with the prospect of reaping profits in the future. This means that social capital can be accumulated, transmitted and reproduced.

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According to Coleman (1988), like other forms of capital (such as physical capital) social capital is ‘productive’ (p.S98), but unlike physical capital, it is intangible because it is incorporated in the relationship between individuals – not in the individuals themselves – and it is defined by the function it performs for the individuals. In other words, social capital is defined by the function it performs more than anything else. Coleman identifies three forms of social capital: obligations and expectations, information channels, and social norms. As already mentioned, for Coleman, the emission of an obligation is crucial to a trust relationship because this anticipates an act of reciprocity; thus the sum of obligations emitted by a subject constitutes his social capital and the density of this emission reflects the investment made. The second form of social capital is made up of the flux of information that runs through social relations; in the third form, social capital is likened to a set of social norms dictating the rules of behaviour within a given community. The economic approach to social capital has been followed by such scholars as Glaeser et al. (2002) and Annen (2003) who claim that, firstly, social capital is understood as a form of investment that allows subjects to invest in it in the present with the prospect of reaping profits in the future; secondly, individuals are understood as being the makers of their own social capital; thirdly, collective social capital is seen as an aggregation of individual social capitals. This view has attracted serious criticism. Arrow (2000) advances a scathing criticism against the economic approach and argues that social capital cannot be considered as a form of capital like all the others mainly because it is reversible, and above all because it cannot be seen as a ‘deliberate sacrifice in the present for future benefits’ (p.4). In fact, he suggests that individuals bond for reasons that are not necessarily economic and that social interaction is often considered as being worthwhile for its own sake rather than being a channel to pursue a payoff. In other words, Arrow argues that ‘the reward for the social interactions is intrinsic – that is, the interaction is the reward’ (p.3). A further problem with the economic approach to social capital is related to the fact that is individual-centred, since it coincides with individuals’ relational capital. In contrast, it must be noted that individuals’ investment in social relationships, by definition, necessitates more than one person, which is why social capital cannot be considered as an individual’s asset, but it must be viewed at least as an interpersonal asset (van Stavern, 2003). In contrast to this economic understanding of social capital there is an alternative formulation that draws on socio-political models. Even

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though it was originally coined by Coleman about a year earlier, the expression ‘social capital’ only became current after Putnam (1993) where he analyses, in an Italian context: (a) the link between institutional performance (regional) and civic involvement, and (b) the connection between civic engagement and economic development. He comes to the conclusion that both institutional performance and economic development are positively correlated with civic-ness which plays a key role in defining the dynamic of social capital. In other words, ‘voluntary cooperation is easier in a community that has inherited a substantial stock of social capital, in the form of norms of reciprocity and networks civic engagement’ (p.167). Putnam suggests that social capital can be seen as an alternative solution to the collective action dilemma summarized in the prisoner’s dilemma. Social capital is the result of social interactions that occur when individuals engage in horizontal networks6 such as cooperatives, organizations and other associations of a social, political or economic nature. Social capital generates trust and is constantly fed by the virtuous circles that feed on trust and cooperation. In other words, social capital constitutes at the same time both cause and effect of trust relationships (Portes, 1998). In Putnam’s view, social capital is seen as a collective asset that cannot be generated deliberately by one single individual or through the cooperation of n individuals. On the contrary, it is the end product of a circular, cumulative process involving trust, reciprocity, cooperation and a sense of civic engagement, in which a common legacy of history and culture guarantees the perpetration of social interaction. Lastly, it is worth noting that, unlike physical capital which is a private asset, Putnam understands social capital as a public asset, which means that all participants can benefit from it, even if they are not actively or directly contributing to its maintenance. This can give rise to free-riding problems that can be addressed through social sanction mechanisms.7 Like Putnam, Fukuyama (1995) explores the connections between trust, social capital and economic development in Japan, the United States, Europe (Germany, Italy) and Asia (China). In his work, social capital is defined as a capability that characterizes a society, or a part of it, when dense trust relationships are present. According to Fukuyama, social capital is culturally determined by such mechanisms as religion, tradition, historical practice and convention and is the result of a spontaneous process of collective interaction (‘spontaneous sociality’) which leads individuals to assimilate and share moral values such as loyalty, trust and honesty. Social capital, therefore, cannot be generated by unilateral individual mechanisms. Fukuyama suggests that patterns

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of cooperative behaviour based on trust are born within the family, the core or prime nucleus of social capital; nonetheless, only those forms of trust that transcend family or kinship give shape to a form of sociality and social capital that is conducive to economic development. The socio-political approach to social capital considers it to be culturally determined in so far as it is generated by the interaction of individuals in a community. This argument almost automatically leads us to consider communities whose members are geographically contiguous. This explains why this form of social capital is often claimed to contribute to creating a climate where ‘untraded interdependences’ can be created and nourished.

4. Trust and social capital in glo-cal networks The theories on trust and social capital, as delineated in the preceding two sections, are instrumental to understanding why these have played such a central role in explaining the interactive processes concerning firms in local production systems. In fact, in conjunction with an analysis of the organization of production (e.g. production segmentation, specialization; and external and agglomeration economies), for the study of local production systems it has become crucial to understand which factors enable and facilitate the functioning and the fluidity of complex networks of inter-firm transactions. As well as to understand what causes each transaction to take place, re-occur, adapt and be reorganized smoothly and costlessly. A possible answer to these questions comes from the notion that trust can act as a ‘lubricant’ of inter-firm relationships, and that social capital is its amplified and aggregate expression as it mirrors the fabric of trust relationships that generates positive externalities within the system. The advantages of trust are well known: trust reduces uncertainty; it reduces the need to formulate complex contracts; it enhances the flux of qualitative and quantitative information that runs from firm to firm; it activates endogenous sanction mechanisms; and lastly, it allows firms to establish and maintain cooperative relations. We are here dealing with systemic rather than calculative trust precisely because we are appealing to a form of trust in a context where a critical mass of trust relationships gives rise to a set of trust norms that spread within the system to secure its own continuity and homogeneity.8 The origins and evolution of systemic trust are thus embedded within the system, in this case the local production system, and it can only be altered if economic actors in the system wish to.

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The importance of social capital in socio-economic relations is equally well known. Social capital is now known to be crucial to the competitiveness of local systems – in that it promotes the creation and spread of tacit knowledge; it contributes towards increasing information flows; and it generates trust relationships (Trigilia, 2001). In concordance with Putnam, social capital is viewed as the result of a spontaneous, cumulative process of repeated trust relationships where history and culture shape the dynamics of the evolutionary process itself. Moreover, social capital is not seen as the sum of firms’ dyadic relations but is, on the contrary, a public asset, a collective resource that generates positive externalities for all the firms in the local production system. Both systemic trust and social capital are, therefore, embedded in the local systems, where agents share the same socio-cultural-institutionalhistorical context, and constitute for the local system a localized and specific comparative advantage. The multifaceted literature on industrial districts (Becattini, 1990), clusters (Porter, 1998), innovative milieux (Camagni, 1991) and regional innovation systems (Cooke, 2002) has underlined the importance of trust and social capital to facilitate the ‘untraded interdependences’ that mirror production/economic relationships. The sharing of tacit knowledge, the informality of communications and exchanges, and the management of risk and uncertainty are facilitated and underpinned by the presence of systemic trust and social capital. In other words, it is often argued that the competitiveness of firms and localities can stem from the characteristics, structures and dynamics of production processes that are embedded within the local system where geographical proximity is able to generate both economic efficiencies (agglomeration, location and external economies), and a blend of social, cultural and institutional factors. The advantages of local embeddedness and co-location are increasingly undermined by the need for localities to maintain open channels with the outside world. These needs can take various forms: knowledge sourcing, access to cheaper factors of production, competence sharing or access to markets. Openness can both encourage new firms to come in providing fresh nourishment for the whole system (Bellandi, 2001), and allow incumbent firms to start up new relations or to place themselves within other production contexts. Local centripetal forces tend to be, therefore, more and more coupled with global and centrifugal ones, so that firms are increasingly engaging in both local and global networking at the very same time. Firms are, therefore, becoming parts of glo-cal networks.

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We would argue that the concepts of systemic trust and social capital described above are inappropriate to explain what can facilitate such glocal networking. To some extent, both of them could even act as barriers to the opening of a system to the outside. The local embeddedness of systemic trust could inhibit, for instance, the creation of relationships with ‘unknown’ agents operating in an ‘unknown’ context. The familiarity and comfort of agents that operate in a trust-based environment could deter them from taking the plunge and explore new opportunities and prospects. On the other hand, in extreme conditions, social capital can also become a club asset or even cause ‘social liability’,9 where members are defined and non-members excluded. In this case, social capital becomes an intangible and invisible border closing systems or groups to the outside. Portes (1998) points out that the very same factors that constitute the advantages of social capital (homogeneity, gratitude and reciprocity, respect for established rules and the recurrence of relations between subjects that know each other) can turn into exclusion criteria. The idea that closeness, exclusion and entrenched relationships can be detrimental to local systems and localities and explain their decline might not be novel; what is interesting, however, is the fact that paradoxically this decline might be caused by those very factors that have also triggered a number of advantages. This raises a number of issues. First of all, can we conceptualize a form of trust that underpins multi-scalar networks? What form will it take? How is it created and maintained? What forms of proximity will it refer to? How do agents reconcile rooted (systemic) and uprooted forms of trust? What aggregation of trust-based relationships will emerge? Can we conceptualize a form of social capital that belongs to an a-local network? We would suggest that the development of network trust10 could depend on: a) trustworthy ‘relational memory’; b) the presence of ‘bridging agents’; c) the openness, density and modes of information sharing; and d) the governance of the relationships (who decides and who depends on whom?). a) There is a dimension of trust that is often overlooked, that is its capacity to be transferable across relationships. In particular, there are two aspects of trust that the theory has somehow neglected. Firstly, if a firm is used to operate in a context where trust prevails, then it would expect to receive trust and reciprocity; in other words, for this firm trust relationships would constitute the norm rather than the exception. Secondly, a firm that is used to operating in a context imbued with trust is aware of the benefits and advantages it generates. These two components of trust which, despite their contextual links, are ingrained within each

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individual firm can be summed up as the propensity to trust and the awareness of the value of trust. We are suggesting that firms that work in a trust-based atmosphere, do not only have positive expectations with regards to the establishment of trust relations, but are also aware of its intrinsic worth and beneficial value. One can, in fact, reasonably assume that a firm’s accumulated trust experience constitutes its heritage, a kind of ‘trustworthy relational memory’, guiding it into taking a particular course of action when new or unexpected situations arise. In other words, it coincides with the relational experience of individuals at the local level, which provide a default attitude at the a-local level. b) Whether we agree with Sako’s (1992) definition of goodwill trust as being a transaction when parties refrain from ‘unfair advantage taking’ (p.452), or with Thomas’s (1978) concept of ‘basic trust’ as being a situation when trust and confidence is the norm and deception the exception, trust requires an initial leap of faith. This starts out as an initial step, which at time t = 0, calls for a small act of faith and goodwill, no matter how small and insignificant this might be. Clearly, not all firms commit to the same degree of bridging, this depends on a number of factors including the position they occupy along the supply chain; their current relations with firms outside their system and also their degree of commitment to openness. ‘Bridging firms’ are most likely to seek contacts outside their local system since they are those that feel more strongly the pressure of national and global competition (e.g. cost of raw material, access to technology, design and specialized competences) and that therefore feel the need to keep an ear to the ground. Not only does systemic trust provide these firms with a competitive edge, but it also gives them the chance to establish new trust relations prompted by positive expectations. Granovetter (1973) argues that the most important relationships in social networks are the weak ties that bridge concave systems of strong ties. In fact, while strong ties are capable of promoting and guaranteeing cohesion within a group of individuals, only weak ties allow for openness and integration across groups. Strong ties allow an individual to belong to a community, to share its norms, processes and information; whereas weak ties provide the individual with new opportunities, allowing him to access a pool of information and knowledge beyond and external to his own community.11 Therefore, trustworthy ‘relational memory’ and an attitude to risk are fundamentally important conditions for the local network to have hubs – bridging agents – that are capable of linking the local set of strong relationships with the weak links of the global network.

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c) the heterogeneity of the agents/firms of the glo-cal network requires intense relationship building that necessarily demands the willingness and capacity for good communication (Sydow, 1998). In fact, relationship building depends on the openness, density and modes of information sharing, especially in a context where there is cultural (e.g. language, heritage, and customs) and normative/institutional diversity. d) the sustainability of the relationships between heterogeneous partners and the derived trust depends also on the governance of the relationships, that is, on the degree of mutual dependence or one-way dependence, on who decided the terms of the relationships. We would argue that heterarchical, mutual dependent relationships are more likely to generate trust-based relationships than hierarchical and control-based ones. The reason for this is that agents are more willing to trust each other if they both have stakes in the relationships. And what about social capital? As for social capital, if on the one hand social capital is embedded in the local system, on the other, would it not be reasonable to assume that, once established, also network trust could embed itself in the network of local and global hubs and linkages? Granovetter’s original definition of embeddedness does not refer to local interactions only, rather he stresses ‘the role of concrete personal relations and structures (or networks) of such relations in generating trust and discouraging malfeasance. The widespread preference for transacting with individuals of known reputation implies that few are actually content to rely on either generalised morality or institutional arrangements to guard against trouble’ (1985, 490). To some extent, no matter how distant individual firms might be from each other, there is nothing that can keep them from establishing and cultivating over time, through iteration, their own form of social capital. We could refer to this as ‘network capital’, since it belongs to the network of agents and it is underpinned by the aggregation of firms’ network-based trust. We have tried to summarize the considerations above in the Figure 8.1, where network capital comprises a set hubs and linkages across local production systems in conjunction with ‘bridging agents’.

5. Conclusion The competitiveness of local production systems is related to tangible factors, such as the flexible organization of production, and to more intangible factors, among which, given the focus of this article, are trust and social capital. The latter are intangible because they are not measurable in monetary terms, but they are deeply rooted in the history, the

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Network capital

Systemic trust and SC Network trust

Systemic trust and SC

Figure 8.1

Systemic trust and SC

Network capital

culture and the interactive dynamics of a particular group in a locality. This is why trust and social capital are seen as being intrinsic to and rooted in local production systems. In particular, they are specific to each local system. However, if their systemic component is taken to extremes, it could mutate and become constraints that might lead the system to inertia and/or closure. Within a global market system, where access to knowledge and technology is crucial to maintain one’s place in the market, it would be unreasonable to assume that local production systems could generate and consume the know-how and technology they need endogenously. This, therefore, gives rise to the need to establish linkages with firms and other economic actors outside the local system. We have suggested we can call such multi-scalar networks, glo-cal networks. The conceptual challenge of this contribution has been to explore the concepts of trust and social capital in the absence of geographical proximity. We have tentatively introduced the concepts of network trust and network capital to explain both how we can enable local systems to link up with other local systems and what form of trust and social capital can underpin such linkages.

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Needless to say, this contribution opens up more questions and unresolved issues rather than provides answers. The arguments advanced are undoubtedly in need of further thought and elaboration, which will, hopefully, lead to a better understanding of the role of intangible assets (like trust and social capital) in a-local networks.

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Sako, M. (1992), Trust and Organisational Efficiency, Price, Quality and Trust, Cambridge, Cambridge University Press. Sako, M. (1998), ‘The information requirements of trust in supplier relations: evidence from Japan, Europe and the United States’, in Lazaric, N. and Lorenz, E. (eds), Trust and Economic Learning, Cheltenham, Edward Elgar. Sydow, J. (1998), ‘Understanding the constitution of interorganisational trust’, in Lane, C. and Bachman, R., Trust within and between organizations, Oxford, Oxford University Press. Thomas, D.O. (1978), ‘The Duty to Trust’, Proceedings to Aristotelian Society, 79: 89–101. Trigilia, C. (2001), ‘The Return of Economic Sociology in Europe’, European Journal of Social Theory, Vol. 4(4): 427–42. van Stavern, I. (2003), ‘Beyond Social Capital in Poverty Research’, Journal of Economic Issues, Vol. 37(2): 415–23. Williamson, O.E. (1996), The Mechanism of Governance, Oxford, Oxford University Press.

9 Local and Global Linkages of Small and Medium Enterprises in Local Production Systems in Brazil1 Wilson Suzigan, Renato Garcia and João Furtado

1. Introduction The object of this chapter is to analyse the forms taken in Brazil by interfirm linkages in local production systems. These are typically non-integrated production systems comprising large numbers of firms, many of which are small and medium enterprises (SMEs). They interact frequently and tend to develop a variety of linkages, as well as having agents who coordinate interfirm relations as a complement to market mechanisms. These forms of governance vary according to the type of local production system (LPS), which in turn is determined by production structure, territorial agglomeration, industrial organization, market insertion (domestic, international), institutional density (collective actors, private and public), and social fabric. In the words of Storper and Harrison (1991: 408) they allow us to ‘understand which actors have the power to affect the development of such systems’. Section 2 presents a brief review of the literature in which the concept of LPS linkages is discussed, emphasizing the ‘global supply chain’ and ‘local private and public coordination’ approaches. This is followed in sections 3 and 4 by a summary of two case studies in Brazil to illustrate and assess the pertinence of the two approaches. The footwear industry in Franca (São Paulo State) is a typical case of insertion in a global supply chain led by major international buyers, while the furniture industry in Votuporanga (in the same state) shows how power asymmetry in the LPS is offset by forms of local private and public coordination of networks of firms. The last section presents conclusions and suggestions for general public policy guidelines regarding LPS. 175

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2. Coordination of supply chains and insertion of local production systems A recurrent theme in research on local production systems (LPS) is the coordination of interfirm relations, given the concentrated presence of producers and the predominance of small and medium enterprises (SMEs) that configure a complex production structure comprising firms in various stages of the supply chain, with a division of labor among specialist producers. This translates into external economies that benefit all firms in the system and are essential to their competitiveness. Because of the high degree of vertical disintegration there must be frequent interaction among agents, making some form of coordination necessary. Among the questions raised by the discussion of this theme are: What are the factors that determine the capacity to act as lead firm in coordinating interfirm linkages? What elements induce different configurations of the balance of power within LPS and their non-local (global) linkages? How does the existence of pronounced asymmetry among firms in any given LPS affect the organization of production in the system and the relations among agents? Do the linkages between local producers and the agents responsible for marketing their products represent a stimulus to development of the system? And in what areas do firms succeed in developing or come up against obstacles erected by the way in which the supply chain is organised? This chapter endeavors to answer some of these questions using evidence from case studies. One of the most substantial contributions to the study of interfirm relations and governance in industrial production systems is the research by Storper and Harrison (1991), who approached the subject from the angle of the hierarchies formed within supply chains. The key concept here is the ‘production system’, defined by these authors as the coordination structure that arises out of the interactions that take place along the supply chain and comprises both vertical and horizontal linkages among firms. These linkages may be solely governed by market mechanisms or result from interactive relationships that are often strongly hierarchical. The authors take this concept as a starting-point for in-depth examination of the governance structures observed in interfirm relations, in terms of the degree of hierarchy, leadership and command (or alternatively collaboration and cooperation) exerted by firms in coordinating relations with other players in the same system. The issue of production system governance refers therefore to the power relations found in supply chains, and to understand it one must begin by asking whether relations within the supply chain (or production

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system) are governed by price mechanisms or, at the opposite extreme, result from strong hierarchies imposed by agents with the power to do so. There are also intermediate coordination structures in which both price mechanisms and hierarchies are replaced by more frequent interaction among the agents involved, resulting in a greater degree of collaboration and cooperation in interfirm relations. However, this does not mean there is no asymmetry at all among the firms. On the contrary, relations of this kind are typically characterized by strong hierarchies due to differences in bargaining power among the firms that participate in the system. Storper and Harrison (1991) incorporate into this context the local dimension of production activities and a set of LPS structures. The concentrated presence of firms (producers and their suppliers) in the same branch of industry or market segment entails intense interaction, which may or may not be controlled by a major corporation (the ‘lead firm’). In these LPS the frequency of interaction is very high owing to the division of labor among specialist producers, resulting in external economies for the firms that participate in the system.2 The authors next present a typology of production systems, with three complementary dimensions: (i) the characteristics of the production system (input–output system); (ii) the existence of agglomerations; and (iii) the governance structure for the network of firms. Based on these three attributes they create a matrix to classify systems with distinctive characteristics (Table 9.1).

Table 9.1 Typology of production systems Type

Main characteristics

Examples

All ring – no core

There are no clear leaders and no asymmetries among firms

Italian industrial districts (classical model)

Core-ring with coordinating firm

Some degree of hierarchy and asymmetries; lead firms influence (but do not decide) the behavior of the producers

Networks coordinated by firms (such as Benetton and Bosch)

Core-ring with lead firm

Asymmetries and hierarchy; the lead firm determines the strategy of the producers

Networks managed by big firms (such as GE, Westinghouse, Sony and Philips)

All core

Verticalized big firm

Williamsonian integrated firm

Source: Adapted from Storper and Harrison (1991).

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Although the typology is incomplete, as the authors themselves recognize, it is an important contribution to the analysis of interfirm relations. However, the authors appear to underestimate the importance of asymmetries among firms and of strongly hierarchical relations, which create a governance structure (corresponding to their two intermediate types) that seems to be the most frequently found in the LPS studied to date. It is therefore unlikely that governance structures exist in which such asymmetries simply disappear, making way for relations among equals, of the type they term ‘all ring – no core’. The recent evolution of capitalism has led, on the contrary, to a reinforcement of the economic power of certain firms, which impose hierarchical relations on other firms that belong to the supply chain. Markusen (1996) also attempts to advance in this direction by presenting a typology of local networks. Her starting-point is the assumption that an analysis of the Italian industrial districts is not sufficient to encompass the extensive and varied set of experiences in which an agglomeration of firms plays an important role. One such case is the ‘hub-and-spoke’ formation in which the LPS gravitates around a large firm that coordinates the supply chain. This type of system clearly involves hierarchical relations among firms in which the lead firm imposes its interests on the other firms in the network. In this case, what cooperation among agents there is tends to take place on the terms defined by the most important firms, since all interfirm relations are organized as a function of their demands, their contracts and their longterm commitments. Thus cooperation is restricted to efforts to improve production, lead times and ways of controlling suppliers (locally or elsewhere). Another point to which this author calls attention is the fact that most research on LPS is not concerned with how these systems mesh with the broader context, especially their linkages to global supply chains. This is vitally important, she argues, since the firms in such LPS are often competitive only in the domestic market and cannot compete globally. The proper approach to any attempt at addressing this issue is based on what Gereffi (1994) calls ‘global commodity chains’. This starts from an analysis of the organizational format of international supply chains to investigate the hierarchies and forms of governance found throughout the chain, with the assumption that the appropriation of value by the agents who participate in the chain is not symmetrical, given the existence of major hierarchies across the system. The types of global commodity chain analysed by Gereffi (1994) include what he terms ‘buyer-driven’ chains, found in the textile, clothing, footwear, furniture


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and food industries. The governance structure is determined by the firm’s capacity to own strategic assets whose tacit and specific nature prevents other firms in the chain from reproducing them. In this case, the coordinators or lead firms (large international buyers such as department stores and supermarkets) typically do not engage in production themselves. Their power derives from owning commercial assets such as trademarks, brands, marketing and distribution channels, etc. These lead firms play a central role in coordinating vast networks of contractors, who are usually located in developing countries and manufacture the finished goods according to specifications supplied by foreign buyers. The buyers are usually responsible for product development and marketing. As a result, the large buyers very strongly influence the dynamics of all other agents in the entire chain. In other words, buyers are capable of coordinating global supply chains by heavily influencing the strategies of suppliers and contractors. It remains to investigate the possibilities for development or upgrading of these firms; the research by Humphrey and Schmitz (2000) is a case in point. An important aspect to stress is the key role of spillovers in enhancing the competitiveness of producers in LPS, since geographic and cultural proximity encourages firms and local institutions to exchange knowledge, and this in turn fuels the innovation process. Examples can be found in Belussi and Gottardi (2000), Bianchi and Parrilli (2002), Parrilli (2004) and Lombardi (2003). In this sense, however, there is a clear contradiction in the nature of the control exercised by large buyers and their relations with suppliers. On one hand, the large buyers play a fundamental role in transmitting knowledge to contractors. The need for quality assurance and enforcement of product specifications leads producers to develop specific skills, often in collaboration with buyers. There are many cases of large buyers with structures to provide technological and organizational assistance adjoining their sales offices in producer countries and regions, whereby they help to foster a learning process through interaction with suppliers. On the other hand, development driven by interaction with major buyers rarely extends outside the production sphere. Thus producers develop relevant capabilities relating to production processes, in terms of product quality and conformity with specifications, even developing process innovations themselves. But they are unable to influence other assets, especially those that add value to commodities, such as product development or the establishment of their own commercial assets (e.g. brands or sales and distribution channels). It is ownership of these and other strategic assets that gives firms the ability to control a supply chain,

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since unlike manufacturing facilities they cannot easily be reproduced in different contexts. This inability to advance toward key assets means producers cannot achieve ‘higher corporate functions’ (Furtado, 1997) and restricts their operations to production. This reduces their opportunities to appropriate most of the value added along the supply chain, while at the same time making sure that control remains in the hands of the large international buyers. Thus part of the external economies created by the LPS is not appropriated by local firms. The ability to lead a network of firms enables the large international buyers to appropriate the value created during the production and distribution process. In contrast, forms of local private and public governance can play an important role in stimulating the competitiveness of firms located in production clusters. Local governments, for example, can contribute by setting up and funding institutions to support the development of local producers, such as vocational training centers, units to provide technological services, or governmental development agencies. Trade associations and non-governmental organisations can also act as catalysts of local development by taking action to foster competitiveness and interfirm collaboration. Even in cases where the local system is organized by a lead firm, as in the ‘hub-and-spoke’ systems noted by Markusen (1996), local governance is also of great importance. Although cooperative relations among agents are not very frequent, in her view the dynamism of the LPS depends mainly on the strategies of the lead firm, which is capable of coordinating relations among the various agents that make up the system. Other local firms tend to submit to the interests and actions of the lead firm, but they too will benefit from the lead firm’s development, albeit asymmetrically. The case studies discussed in the following sections illustrate the pertinence of these forms of local governance to LPS in Brazil. However, it is worth noting that in other cases the presence of lead firms that govern the local system may lead to its stagnation. If a lead firm, which is capable of coordinating the many other agents that make up the system, adopts conservative strategies, it may prevent the development of other firms in the same local system. Humphrey and Schmitz (2000) use the term ‘quasi-hierarchy’ in referring to this phenomenon. Thus it can be seen that the potential for development of local production systems depends largely on the forms of governance, public or private, in place in each system. The extraction of benefits from clustering, in addition to any incidental external economies, depends on


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whether the LPS has forms of governance that stimulate cooperative relations among agents, leading to the establishment of joint actions among them and enhancing the competitiveness of all producers in the system.

3. The footwear industry in Franca (SP): ‘quasi-hierarchy’ and participation in the global supply chain The Franca region of São Paulo State is the second-largest producer of footwear in Brazil, after the Vale do Sinos region in Rio Grande do Sul. In 2004, the number of people formally employed in Franca’s entire leather and footwear supply chain was almost 31 300, according to the Ministry of Labor. There were 1814 firms in the chain. Footwear production proper employed more than 24 200 workers, evidencing strong local specialization. Moreover, this specialization is reinforced by another feature of the local production system, which is the almost exclusive production of men’s leather shoes. The LPS comprises a large number of firms, most of them small and medium. Local producers benefit extensively from the external economies that result both from the presence of a vast contingent of skilled workers, who moreover have the specific skills required by the system, and from large and frequent spillovers of technology and knowledge. However, a large proportion of the production process, mainly the labor-intensive stages, takes place outside the factories through the subcontracting of stitching and manual sewing, and this creates a significant number of informal jobs. Moreover, cost cutting by outsourcing parts of the production process via abundant use of homework is a strategy extensively used by the local industry to enhance the competitiveness of the firms involved. This evidences the existence of spurious elements that sustain the competitiveness of local producers. Another feature of the Franca LPS is the presence of a large number of firms engaged in related and support activities, such as suppliers of raw material, plant and equipment, and components for footwear. This configures a virtually complete production structure as far as the manufacturing of footwear is concerned, with the LPS containing almost all links in the leather and footwear supply chain. All these features underscore the importance of agglomeration economies for the competitiveness of local producers, who benefit from the positive externalities generated by the local system. Despite the importance of incidental external economies, however, producers in

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Franca gain little from the considerable scope for establishing and maintaining joint activities. This is mainly due to the form of governance of the LPS, which is characterized by major asymmetries.

3.1 Organization asymmetries and ‘quasi-hierarchy’ in local system coordination The development of the Franca footwear industry took off in the late 1960s and early 1970s, when the Brazilian footwear industry incisively entered the international market. In actual fact, this resulted from collective action by Brazilian footwear producers, especially in the Vale dos Sinos region, who paid to bring over foreign designers and journalists to a trade fair in Brazil (FENAC, short for National Footwear Fair, held annually in Novo Hamburgo, Rio Grande do Sul). As a result of this initiative the large international buyers, who are always in search of countries with low wage costs to supply product, began placing massive orders with footwear producers in the Vale dos Sinos region, mainly for women’s shoes, a specialty of the local firms. At that time the Franca producers took advantage of their specialization, which complemented that of the Vale dos Sinos producers, and began offering men’s leather shoes to the large international buyers. This injected a welcome dose of dynamism into the local industry. By the 1980s the Franca footwear industry’s rapid development had led to the emergence of a very heterogeneous production structure in which a few large firms that operate in the domestic market and have their own brands as well as considerable bargaining power in dealings with buyers and the rest of the supply chain coexist with a vast contingent of micro, small and medium enterprises, most of which sell standardized products with low profit margins. Alongside these producers are a large number of service providers, mostly stitching subcontractors who work for shoe manufacturers on an informal basis. From the above description it can be seen that this is a heterogeneous and complex production structure. Furthermore, it generates steep hierarchies that result in an unequal capacity to appropriate the benefits derived from agglomeration. A large proportion of the small and medium enterprises in the LPS are unable to appropriate a significant share of the value added along the supply chain, even when they operate in the domestic market.3 Their strategies are often suffocated by the actions of large local firms and their suppliers. Even joint initiatives by SMEs have been inhibited and sometimes neutralized by the actions of large firms. An interesting initiative was undertaken some years ago by a group of 30 small firms known locally


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as the G30. The group attempted to set up a consortium to negotiate better terms on which to buy strategic inputs such as soles and adhesives. The considerable bargaining power of local suppliers of soles and adhesives gave small producers a competitive disadvantage in this area, since they were rarely able to buy such materials on the same terms as their larger competitors. However, this collective initiative by small firms was short-lived because the large local firm that supplied glue broke the consortium using the simple tactic of approaching the members of the G30 one by one to offer lower prices than had been negotiated with the consortium. The small footwear producers rapidly abandoned the consortium as a result and the initiative eventually failed. Cases like this show the difficulties faced by SMEs in trying to take collective action, given the opposition of players in the same local systems. The larger firms often block collective initiatives by SMEs in an attempt to enhance their competitiveness. Another interesting example occurred in the 1990s, when a joint strategy was coordinated by the local trade association (Sindifranca) to establish a local brand in the domestic market. A number of firms, with financial and other kinds of support from the trade association, decided to place advertisements for ‘Franca Footwear’ in national news media. The initiative lasted only a few months, however, because it was considered unhelpful by the large firms in the local system. It remains to investigate the reasons for which local firms do not persist with actions of this kind. The main reason is that large firms have no interest in the establishment of collective actions that benefit the production system as a whole, especially when the principal beneficiaries of such actions are SMEs. Large firms see SMEs as their competitors in the domestic marketplace, given that they are contesting the same share of domestic demand. From the standpoint of SMEs, meanwhile, past failures to establish joint action make producers more reluctant to attempt such initiatives again.4 The outcome is that SMEs do not enjoy the potential benefits of belonging to the production cluster. This reflects the perverse form of LPS coordination which effectively ignores the interests of small producers and promotes strategies of larger firms that are successful from the microeconomic standpoint but detrimental to local development. In addition, local producers, especially those of larger size, have to submit to the interests of the major international buyers. Access to the most important markets for their goods gives international buyers the ability to control the global supply chain for the footwear industry.

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3.2 Coordination of supply chain (governance) by major global buyers The global footwear supply chain is a typical case of a buyer-led chain, to use the terminology proposed by Gereffi (1994). The role of global buyer is performed by large retail chains in the US and Europe with access to the world market and thus the ability to control the supply chain overall. Brazilian producers, especially in the Vale dos Sinos and Franca regions, have participated in the global supply chain since the early 1970s, when they began supplying men’s and women’s leather shoes to the large buyers. For the Brazilian footwear industry as a whole, and particularly for producers in Franca, international participation was a huge boost and enabled them to make significant advances in production. Interaction with large global buyers – in practice with the representative offices set up in Brazil by export agents for the buyers – led to important enhancements in process technology, product quality, and lead times. In contrast with advances in the production sphere, however, producers in Franca who participate in the global supply chain have not been able to advance significantly in the marketing, product development and design spheres. The presence of export agents for major international buyers has inhibited or prevented more substantial progress in these areas. As for marketing and sales, the producers simply ship footwear to export agents, who take care of the entire product distribution process. Goods are rarely sold with the producer’s brand name or logo on display. Even the phrase ‘Made in Brazil’ is displayed inconspicuously. The producers have no product development and design activities of their own to speak of. Models are created, designed and often priced by the buyer, who simply hands the specifications over to the producer. Thus the product development department of a typical footwear maker in Franca comprises no more than a small team of ‘modelists’, who merely adapt the models ordered by large buyers to the production process to assure their manufacturability. The global buyers’ ability to control the supply chain is strengthened by the existence of alternative sources of product, as shown in Figure 9.1. This is evidenced by the vigorous growth of the Chinese footwear industry, which has supplied increasing volumes to major world markets since the early 1990s and has steadily eroded Brazil’s share of the US market.5 It can thus be seen that in the case of the Franca footwear producers who ship to international markets, the interests of local firms are subordinated to the forms of global governance determined by major global buyers. This clearly has damaging effects on the competitiveness


Consumer market (US and EUROPE)

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Global buyers

International buyers

Traders

Producers

Producers

Producers

Suppliers

Suppliers

Suppliers

Local system 1

Local system 2

Local system N

Figure 9.1 Global commodity chain in the international footwear market Source: Adapted from Gereffi (1994).

of the producers, as they are unable either to appropriate a significant proportion of the value added along the supply chain or to absorb part of the benefits that should accrue from belonging to an industrial cluster.6 In contrast with this situation, firms that ship to the domestic market and also export to other parts of South America, including Mercosur, engage in far more significant product development activities, albeit excessively geared to simple adaptation to the Brazilian market of models designed abroad. Moreover, on the home and South American fronts firms are able to control sales and distribution channels, and this gives them the capacity to control the supply chain formed in the domestic and regional markets (see Figure 9.2). In conclusion, the case of the Franca footwear industry clearly evidences the fundamental role played by forms of supply chain governance in conditioning the competitiveness of local firms. For firms inserted in the global supply chain, the form of governance determined by international commercial capital imposes major constraints on local product development and hence the competitiveness of local firms, in contrast with the greater creativity of firms that sell mainly to the domestic market or export through their own sales channels.

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Producers

Local system

Commercialization chains

Stores

Figure 9.2 Domestic commodity chain in the footwear industry Source: Own elaboration based on Gereffi (1994).

4. Collective action with local private and public coordination in the development of the Votuporanga furniture industry The furniture industry is typically diversified and heterogeneous, as well as being geographically dispersed. Firms of every size can be found in this industry, from large industrial concerns with mechanized and often automated production processes to small enterprises with semi-artisanal or fully artisanal production processes. Three raw materials form a basis for the three main segments defined by preponderant or sometimes exclusive use: wood, metal and plastic. Alongside these two sources of differentiation is specialization by segment (professional, especially office, and residential), specific destination (bedroom, living room, kitchen) and income (from branded products made of quality materials and differentiated by design, to low-price, standardized or copied products). The geographic dispersion of the furniture industry is also associated with its technical and industrial characteristics. Because scale economies are very limited while transportation costs are relatively high, the industry tends to develop on a regional basis and this process is often stimulated by government incentives. While it is dispersed in national terms, the furniture industry is typically concentrated in regional clusters, although these differ widely in terms of types of agglomeration and linkages. The Votuporanga furniture production cluster is an important and highly interesting case of this configuration. It comprises a large number of firms (over 500 in the region and 136 in the city of Votuporanga), which differ greatly in size, characteristics and specialization. The number of jobs created by the local furniture industry amounts to about


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14 000 in the region and 2300 in the municipality of Votuporanga. Its main market is regional in the broad sense, comprising the west of São Paulo State, the south of Mato Grosso and Minas Gerais, the north of Paraná, and large towns in other parts of São Paulo State. Most firms, including the smallest, have their own sales channels. Exports are sporadic, even to Mercosur, despite the intentions declared by many firms. On rare and exceptional occasions firms fulfill orders collectively. A case in point was an important order from Iraq. When large orders with short lead times come in, an agile and efficient collective production mechanism can be observed. An order for several thousand bedroom sets may be handled by dividing it up into segments (beds, wardrobes, chests of drawers, bedside tables) and distributing the items in each category to specialist firms, which then may subcontract other firms to produce parts and components. Although this mechanism for collective coordination of production is activated only sporadically to fulfill exceptionally large orders (only a few large producers can meet very large orders on their own in Brazil), other elements of coordination differ sharply from those seen in other LPS and evidence noteworthy density. The typical mechanisms of informal interfirm coordination have been present for many years. In the collective memory, and possibly with redoubled force on the symbolic plane, the founding moment in the process of building interfirm linkages was a fire that completely destroyed the production capacity of one firm and threatened to destroy its business as it faced the impossibility of fulfilling its contracts, which would have done irreparable damage to its reputation and future prospects. Several firms mobilized to help, providing space, lending machinery and supplying raw material. As a result, the stricken firm was able to resume manufacturing operations very quickly, albeit provisionally. Cases such as this are the product of specific circumstances, of course. They may be triggered by a fortuitous element, such as the respect in which the proprietor of this particular firm was held by many of his peers, but even so they help reinforce a collective stance that facilitates other cooperative linkages and multiplies opportunities to reap economic benefits from non-opportunistic behavior. However, the history of the Votuporanga furniture industry and its creation of cooperation and collective action mechanisms also display striking examples of deliberate construction. In this rich industrial story the first coordinated collective initiative was an attempt to create a regional brand with its own characteristic style (known locally by the English word ‘country’). It began in 1992–93 when SEBRAE/SP, with the support of the local manufacturers’ association (AIRVO – Associação

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Industrial da Região de Votuporanga), implemented a project called ‘Interior Paulista Design’ to modernize the Votuporanga furniture industry. The ‘country’ brand and product line turned out to be a failure but the collective action in question points to two important elements of this production cluster. The first is the arguably premature recognition – by the firms involved, the local business community, leaders of the association and local government – of the possibility or necessity of collective forms of intervention. The second element, equally important, is the entrepreneurs’ capacity for networking and mobilization, an element that lasted even after the failure of the ‘country furniture’ project. These two elements, both long-lasting, underpinned the most important step taken by the Votuporanga furniture industry to strengthen itself and embark on a new course of development: this was the 1993 hiring of a professional to act as coordinator, initially in a very informal manner, of a series of local collective actions and initiatives. This professional, whose job description was defined and redefined over a considerable period as his duties and capabilities increased, proved to be an element of reinforcement for several key characteristics of the local industry, especially its cooperative linkages and the positive externalities available for leverage, reinforcement and development. From then on several collective actions planned and executed by the coordinator reinforced the associativism of local firms and public and private institutions. They included the hiring of consultants who specialized in business management (costs, layout, production processes, marketing), the implementation of a total quality program in which specially trained technicians operated as ‘knowledge multipliers’, the creation of a higher education course in furniture manufacturing technology at the local university (FUVEC – Fundação Votuporanguense de Educação e Cultura), and a permanent strategy for training skilled labor that culminated in the 2001 opening of a vocational education and technology center (CEMAD – Centro Tecnológico de Formação Profissional da Madeira e do Mobiliário de Votuporanga), which as well as providing vocational education gave local firms access to modern technologies for business management, new materials research and testing, and furniture design labs. The apogee of this process – creation of CEMAD, headed by the de facto coordinator of the LPS with the help of a small team of highly dedicated professionals, the support of AIRVO and the furniture industry association (Sindimob), and partnerships with FUVEC and the municipal government – deserves additional comments. CEMAD is a center of excellence in Brazil and will certainly exert huge influence on the formation of a skilled workforce and the efforts of local firms to build


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technological capabilities, especially in design, a key knowledge area for competitiveness in the furniture industry. Besides participation by firms and local public and private institutions, the project raised funding from lines of credit and official financing from the federal government (CNPq, FINEP/PATME, and PROEP/Ministry of Education). The amount invested was about US$1.5 million but even before the first cycle of vocational education was completed this produced a highly important outcome for the development of the furniture industry in the city and region, and one whose effects may well spread to other regions:7 the awareness that the development of a local production system can be significantly boosted by strengthening formal and informal cooperation linkages, its key characteristic, so that problems are addressed and surmounted, an agenda for action on major issues is worked out, and new ways of putting that agenda into effect are agreed upon.

5. Conclusion and policy suggestions The cases discussed in this chapter bring out the importance of a number of points already highlighted in the literature and clarify or qualify others. First, they confirm the intuition expressed by Humphrey and Schmitz (2000: 21) that ‘most clusters are hybrid’. In other words, most clusters contain a range of productive segments and governance structures. Second, they also confirm that participation in buyer-led global commodity chains (Gereffi, 1994) prevents local producers from developing more than the capabilities required by buyers for manufacturing (e.g. the Franca case, especially its export segment). Third, in contrast with the lack of emphasis given in the literature to forms of local private and public governance, the Votuporanga case shows that these forms of governance are of paramount importance to the success of clusters not inserted into global supply chains. Firms in these clusters typically display a variety of forms of linkage with international markets: some may be large independent exporters with their own sales channels, while others may be SMEs that produce for export in consortia; they also include segments of firms (large, medium and small) with a strong presence in the domestic market. Hence the scope and opportunities for collective initiatives, often led by a coordinating agent, and for leadership by large firms that promote the development of specialist suppliers and local subcontractors. This gives rise to combinations of different local governance structures, from private governance structures (particularly in systems of micro, small and medium enterprises) with the participation of private institutions (trade associations, business clubs) and public institutions,

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to governance structures characteristic of clusters of the ‘hub-and-spoke’ type (Markusen, 1996), even when the LPS does not have that particular configuration. Thus in order for clusters or LPS to be the object of public policy they must first be analysed with a view to determining their productive structure, forms of market insertion and corresponding coordination structures. For clusters linked to buyer-led global commodity chains, it seems clear that there is little scope for any policy measures other than trivial improvements to infrastructure and support institutions, unless lead firms and local private and public collective actors are strongly involved with the clear aim of ‘repositioning the local system’ (Humphrey and Schmitz, 2000). The scope for public policy and the development potential appear to be greater in the case of clusters not linked to global supply chains. For these, it should be possible to do much with measures designed above all to stimulate collective initiatives, if possible with a coordinating agent; strengthen private and public local institutions; revamp physical infrastructure and the provision of specialist services (technical and technological assistance, vocational education, testing, market and product research, etc.); intensify knowledge flows; and strengthen the learning capacity of firms, especially SMEs (Bianchi and Parrilli, 2002; see also the Introduction in this volume). With these general considerations in mind, and with the reservations required by any generalization, we can now attempt to set out some principles for the formulation of an overall policy in this area. The underlying idea is directly or indirectly to stimulate entrepreneurial or collective initiatives of a specific nature, particularly those that inject technology into the local system as a driver of competitiveness. In a context that combines elements of competition and cooperation, it is above all the technological dimension that fosters provisional advantages whereby other firms are encouraged to pursue ways and means of imitating and surpassing their rivals. Thus strengthening the positions of the most technologically-oriented firms and environments should encourage other agents to adopt similar competitive strategies. Such public initiatives to stimulate innovation and technological capacity building could also help clusters achieve higher levels of efficiency by encouraging more advanced initiatives and multiplying them throughout the cluster via mechanisms of competition and cooperation. These general policy principles would be designed to stimulate: (1) the retaining of a coordinator to develop an agenda for actions and interactions by local firms and institutions, and to act as mediator in


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their relations with the outside world, especially government and banks; (2) the creation of new firms as spin-offs from local firms and research institutions; (3) the intensification of in-house R&D by firms so as to achieve the capacity to produce complete product development projects, including design, conception, development, prototyping, production line adaptation and marketing; (4) the creation or reinforcement of collective technology and training centers equipped to offer vocational courses in areas of relevance to the LPS, technological services, product testing, and other services; (5) the provision of specialist knowledgeintensive business services, such as market research, information on fashion trends, automation systems (especially for design, product modeling, manufacturing and sales), development of specific software applications, implementation of barcode technology, and others; (6) the introduction of business management and total quality programs, including supplier qualification and training, and of technical standards and certification; (7) the use of legal instruments to protect innovation, and (8) the creation of information systems that enable local firms and institutions to gain access to specific kinds of knowledge pertinent to local activities, in technology, software, markets, trends, legislation, financing, databases, events, and Brazilian and international publications. These principles could induce or reinforce processes of collective learning, create conditions favorable to technological networking and other forms of interfirm cooperation, and generate external economies for firms belonging to the local production system.

References Belussi, F. and Gottardi, G. (2000), Evolutionary Patterns of Local Industrial Systems: Towards a cognitive approach to the industrial district, Aldershot: Ashgate. Bianchi, P. and Parrilli, M.D. (2002), ‘Small and medium-sized enterprises: a comparative approach to Latin America and the European Union’, Dept. of Economics, Discussion Paper no. 26, Ferrara University. Breschi, S. and Malerba, F. (2001), ‘The Geography of Innovation and Economic Clustering: some introductory notes’, Industrial and Corporate Change, Vol. 10 (4): 817–33, December. Furtado, J. (1997), ‘La transformation des conditions d’insertion des économies à industrialisation tardive l’économie mondiale: un examen des facteurs généraux suivi de leur particularisation dans cinq secteurs industriels’, University of Paris XIII, PhD thesis. Gereffi, G. (1994), ‘The organization of buyer-driven global commodity chains: how U.S. retailers shape overseas production networks’, in Gereffi, G. and Korzeniewicz, M. (1994), Commodity chains and global capitalism, Westport: Praeger.

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Humphrey, J. and Schmitz, H. (2000), ‘Governance and upgrading: linking industrial cluster and global value chain research’, IDS Discussion Paper no. 120, Sussex University. Lazerson, M. and Lorenzoni, G. (1999), ‘The firms that feed industrial districts: a return to the Italian source’, Industrial and Corporate Change, Vol. 8(2), June. Lombardi, M. (2003), ‘The evolution of local production systems: the emergence of the “invisible mind” and the evolutionary pressures towards more visible “minds”’, Research Policy, Vol. 32(8): 1443–62. Markusen, A. (1996), ‘Sticky Places in Slippery Space: A Typology of Industrial Districts’, Economic Geography, Vol. 72(3), July: 293–313. Parrilli, M.D. (2004), ‘A stage and eclectic approach to industrial district development’, European Planning Studies, Vol. 12(8). Storper, M. and Harrison, B. (1991), ‘Flexibility, hierarchy and regional developments: the changing structure of industrial production systems and their forms of governance in the 1990s’, Research Policy, Vol. 20(5). Taplin, I. (1994), ‘Strategic reorientation of U.S. apparel firms’, in Gereffi, G. and Korzeniewicz, M., eds., Commodity chains and global capitalism, Westport: Praeger.

10 Industrial Cluster Trajectories and Opportunities for Endogenous Upgrading in Developing Countries1 Peter Knorringa

1. Introduction This chapter discusses various trajectories of industrial clusters in developing countries, in combination with an analysis of how different trajectories and different types of inclusion in broader value chains shape opportunities for endogenous upgrading. Therefore, this chapter focuses on the third strategic line – on clustering and networking – of the systemic approach to SME development of this volume. At first sight, the European industrial district success stories from especially the Third Italy in the 1980s and 1990s seem particularly relevant as an example for clusters in developing countries. These European industrial districts by and large share the following characteristics (Asheim, 1992; Schmitz and Musyck, 1994; Rabellotti, 1995). First, they tend to specialize in labor-intensive artisanal sectors, such as footwear or garments, in which less developed countries are often thought to enjoy a comparative advantage. Secondly, the Italianate industrial districts are built on local firms, mainly of small and medium size. Most clusters in developing countries also consist overwhelmingly of small and very small firms. Moreover, local and regional policy makers in developing countries are desperately looking for ways to stimulate a more endogenous industrialization process. Thirdly, the Italian industrial districts are situated in regions that were rooted in small-scale agriculture and which industrialized relatively late. This means that these success stories were part of an industrial ‘periphery’. Similarly, most clusters in developing countries are also located in the peripheral areas of their respective countries. In short, at first glance the Italianate industrial district 193

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experience appears to show that a successful industrialization process built on locally owned firms is possible after all, even in peripheral areas. However, a fundamentally different institutional setting, with widespread poverty, a labor surplus and more extreme differences in bargaining power between cluster actors, may well lead to very different outcomes in developing countries. Besides, apart from being different from the Italian setting, the diversity of institutional settings within the developing world is also mind-boggling. Nevertheless, even though each cluster may have a unique story to tell and direct transferability of experiences may be absurd, it is important not to become mentally imprisoned by history (Schmitz and Musyck, 1994). Therefore, without glossing over the fundamental differences in institutional settings, I feel it is useful to take the industrial district literature as a frame of reference for an analysis of industrial cluster trajectories in developing countries. Moreover, the extent of transferability of experiences appears to be much higher within a framework that focuses on trajectories rather than static models (Humphrey, 1995). While it is now commonplace in cluster studies from developing countries to refer to the Third Italy, only relatively few studies have so far tried to incorporate the idea of trajectories. A notable early exception is Swaminathan and Jeyaranjan (1994) who have tried to analyse the Tiruppur knitwear cluster through a trajectory from artisan to dependent subcontractor to Mark I and to Mark II stages, as coined by Brusco (1990). This chapter identifies various possible trajectories that clusters in developing countries may follow, and discusses their relative potential for endogenous upgrading. While clusters in developing countries as a rule do not initiate radical innovations, they appear to differ significantly in the extent to which they depend on outside actors for implementing incremental (process) innovations. In this chapter, the capability of constellations of local actors in specific clusters to implement and build on incremental innovations – leaving aside the origin of these innovations – denotes their potential for endogenous technological and organizational upgrading. For the more mature and export-oriented clusters operating in buyerdriven commodity chains, such endogenous upgrading capability is important because it makes them more attractive to the more demanding but also better paying global buyers in the more quality-driven market segments (Gereffi, 1999; Schmitz and Knorringa, 2000). Upgrading in value chain literature is usually broken down into:

• process upgrading (doing things better); • product upgrading (producing better goods);

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• functional upgrading (engaging in additional and higher value-added activities) (Humphrey and Schmitz, 2000). A key issue in the present literature is the extent to which asymmetrical relationships with buyers provide small and medium scale producers in developing countries with opportunities for learning and upgrading. Recent studies (among others Gereffi, 1999; Schmitz and Knorringa, 2000) argue that (global) buyers often play a significant role in process and product upgrading, especially for their more favoured suppliers. The controversial issue is whether firms are also able to achieve functional upgrading, and to determine the role buyers play in furthering, neglecting or obstructing functional upgrading by their suppliers. While Gereffi’s study on garments recognizes that there are many obstacles to functional upgrading, he emphasizes the dynamic learning curves that producers in value chains are exposed to: moving from mere assembly to monitoring the entire production process, to design and sale of their own branded merchandise. In contrast, Schmitz and Knorringa (2000) found that in the footwear industry global buyers tended to see attempts at functional upgrading as encroaching on their core competencies and actively discouraged such attempts by industrially clustered groups of small and medium scale suppliers. Therefore, to enhance opportunities for endogenous upgrading it is important for producers to be able to move from focusing exclusively on process and product upgrading to also (being able to) engage with functional upgrading. This chapter first looks briefly at the large group of survival clusters for which the industrial district model is not a suitable frame of reference. Section 3 positions a wide variety of case studies on three different stylized cluster trajectories, and discusses the extent to which examples of endogenous upgrading can be found. The next section aims to identify to what extent policy lessons from the Third Italy may be useful to local and regional policy makers in developing countries. The last section contains the conclusion.

2. The case against a meaningful comparison: survival clusters Probably the most common type of manufacturing cluster to be found in developing countries is the survival cluster (see, for example, Pedersen, 1997). Such clusters are based on horizontal specialization and not (or at least not primarily) on inter-firm division of labor within the value chain. However, relatively lower transaction costs may be achieved because of

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lower search costs for potential customers (consumers as well as traders) and the presence of a local specialized labor pool. Because such transaction costs are often extremely high, especially in the least developed areas of the developing world, they often provide clustered enterprises with a crucial competitive edge over isolated firms. In comparison to other clusters, perhaps the main feature of survival clusters is that they face very unstable conditions and are usually not the only, and sometimes not even the main, activity of participating actors. Heinen and Weijland (1980 ) raised the question whether such clusters should be interpreted as a sign of poverty or progress. Micro-level studies reveal that rising incomes have in some cases led to the collapse of such clusters, while in other cases they have led to a consolidation of the participants’ commitments towards cluster activities. However, without wanting to be deterministic, also consolidated survival clusters face daunting barriers to their development into more mature clusters with, for example, increasing inter-firm division of labor and the building up of upgrading capabilities. A parallel with the informal sector and small enterprise literature may be useful here. The common understanding in much of this literature appears to be that in enterprise development ‘little acorns do not as a rule grow into mighty oaks’ (Grosh and Somolekae, 1996), or in other words, ‘graduation’ from survival to micro- to small-scale is the exception rather than the rule (Farbman and Lessik, 1989). A similar caution in assessing the opportunities of survival clusters to grow into more mature clusters seems justified. Even though probably most of these survival clusters are found in rural areas, they also exist in metropolitan areas. The main difference is that most metropolitan clusters are built on survival-oriented selfemployment, where actors have fewer local roots and operate more in modern sectors (Alam, 1994; Benjamin, 1991).2 These sectoral specializations largely correspond with the well-known European clusters: Fashion-sensitive and labor-intensive sectors with significant market niches which add surplus value to quality-competitive artisanal products, such as footwear, other leather products, clothing, wooden furniture, jewelry, glassware, some metal products, and types of toys and handicrafts. The more promising clusters in developing countries, especially in Asia and Latin America, are usually located in medium-sized towns. In the literature, it appears as though Africa does not possess such promising artisanal clusters (for an overview of African case studies, see McCormick, 1999). However, this observation should not be taken at face value. First, researchers on clusters in Africa have tended to focus on the informal (jua kali) segment of a particular sub-sector. Second, and related

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to the first point, the operationalization of the cluster concept has been much stricter in terms of geography.3 Most cluster studies deal with, for example, an area on the outskirts of a bigger town where all vehicle repair shops/garages have been concentrated (see, for example, Kinyanjui, 1997). To put it bluntly, as soon as one comes across a few printing workshops next to those garages, the cluster ends. In contrast, the Agra footwear cluster, notwithstanding concentrations in specific neighborhoods, is spread out over a city of almost two million inhabitants, and encompasses both large, modern factories and informal home-based units (Knorringa, 1996, 1999). In the African context, such variety within a sub-sector in one big city may well exist, but it would not be discussed as one cluster. For example, the garment sub-sector in Nairobi appears to encompass large, modern factories (often export-oriented and owned by white entrepreneurs), as well as a hidden medium-sized segment of workshops predominantly run by Asian entrepreneurs, and an informal survival segment run by indigenous black artisans (McCormick, 1999). Notwithstanding such different approaches, it seems safe to say that most clusters in developing countries are survival clusters with limited potential for endogenous upgrading. The industrial-district model does not offer a particularly useful angle to approach the problematic of these survival clusters. What remains is that in terms of total employment and in terms of likely policy priorities for poverty alleviation, this large group of survival clusters may well be more important and more in need of support than the more mature clusters, which will be discussed in the remainder of this chapter.

3. The case for meaningful stylized trajectories This section presents the three stylized trajectories that emerge from the literature, and aims to show their usefulness when systematizing experiences from more mature urban clusters in developing countries. Any typology inevitably simplifies and may give the wrong impression that clusters are homogeneous when they enter a particular trajectory. Clearly this is not the case. Clusters possess unique characteristics shaped by their respective social, cultural, political, and economic environments. Notwithstanding this path-dependent uniqueness of clusters, many of the more mature clusters appear to evolve along three distinguishable trajectories. These three trajectories are derived from Markusen (1996), who came up with the labels as part of a typology of industrial districts and their description for industrial economies, and from Humphrey (1995: 159), who described possible cluster trajectories in developing

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countries without providing labels. Remarkably enough, the trajectories sketched by Humphrey can be seen as moving from a ‘basic’ agglomeration to one of the types of industrial districts that Markusen distinguishes. But, to start with, the first option is a stagnating cluster that does not evolve along any of the possible trajectories. Such clusters: ‘will continue to be agglomerations of firms enjoying the external economies of agglomeration but without the inter-firm linkages which are at the heart of the industrial district model’. (Humphrey, 1995: 159). To be able to enter one of these relatively more successful trajectories requires a shift from ‘static gains’ to ‘dynamic gains’ (Rabellotti, 1995), or from competitive advantages derived ‘just’ from external economies to include processes of consciously pursued joint action by cluster participants (Schmitz, 1995). In the first trajectory, a cluster evolves into the set of stylized facts that represent the Italianate industrial district. In Italy, it now appears as though at least some of its clusters are evolving into hub-and-spoke districts with a limited number of larger leading firms and many subcontractors (see, for example, Meyer-Stamer et al. 2004, Rabellotti, 2004). A second trajectory, more common in developing countries, concerns clusters that evolve from a ‘basic’ agglomeration into a hub-and-spoke district without an intermediate stage in which they have resembled the main features of the Italianate model. A third trajectory runs from a ‘basic’ agglomeration to a satellite district, in which most small and medium firms manufacture for leading firms located outside the cluster. There are indications that some satellite districts may subsequently evolve into hub-and-spoke districts. In the remainder of this section, I position a selection of case studies from developing and developed countries on one of these trajectories, and discuss their potential for endogenous upgrading. Given the scarcity of longitudinal case studies, this review necessarily relies mostly on comparing studies done in a single time period.

3.1 The first trajectory: towards an Italianate district The first trajectory – towards an Italianate type of industrial district – is the most difficult to find in developing countries. In fact, only two such cases were found in the literature: The surgical instruments cluster in Sialkot (Pakistan), and the ceramic tile cluster in Criciúma (Brazil). The former especially appears to have displayed a significant number of the Italianate features, at least in the beginning of the 1990s (Nadvi, 1996). As Humphrey wrote in his overview, the Sialkot cluster

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consisted of: ‘large numbers of small firms engaged in extensive interfirm exchanges of service, horizontally and vertically, active producer associations, supportive local and regional governments, and the cluster’s powerful position in the world market for basic surgical instruments’ (Humphrey, 1995: 159). However, a few years later this cluster appears to be on a trajectory towards a hub-and-spoke district. Nadvi (1999) reports on the consequences of the crisis for Sialkot’s manufacturers. In May 1994, the Food and Drug Administration of the United States, the most important export market for Sialkot, embargoed the import of Pakistani (i.e., Sialkot-made) surgical instruments for failing to meet international quality standards. By 1996, Sialkot appears to have come out of this crisis even stronger than it was before: sales are again above the 1993 level, and overall quality has improved. Moreover, after a slow start, by September 2000 170 out of 300 relatively larger producers were ISO 9000 certified (Nadvi, 2004). In order to establish or maintain contacts abroad, such certification has become more and more a necessary but not a sufficient condition. Therefore, doing direct business with quality conscious importers becomes the exclusive domain of those larger entrepreneurs with the proper certifications. Moreover, within the associations and institutions of the Sialkot cluster, a relatively small group of entrepreneurs appears to have become more dominant. Finally, trends around the turn of the millennium seem to indicate that the Sialkot cluster is becoming increasingly integrated with, and partly dependent on, the German surgical instrument cluster of Tuttlingen. This has led to further differentiation of value chains in combination with looser ties among enterprises as the spread of ISO standards makes it easier for firms to switch suppliers (Nadvi and Halder, 2005). In the case of the Criciúma cluster, local actors from firms and business associations deliberately try to build Italianate structures (Meyer-Stamer, 1997). The cluster consists of around ten medium- and three largesized manufacturers of floor and wall tiles (all nationally owned) and a substantial number of suppliers (some nationally owned, some subsidiaries of leading firms from Italy and Spain) (Meyer-Stamer et al. 2004). Unlike the case of Sassuolo, the worldwide leading tile cluster in Italy (Porter, 1990), there are no local equipment manufacturers in Criciúma. In the past there was fierce rivalry and little cooperation between firms. This changed after the industry entered into a deep crisis around 1990. Two presidents of local business associations succeeded in establishing cooperation; one of the important outcomes was the creation of a local technology center. Two further aspects are important to understand

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why cooperation started. First, there was the observation that firms in Italy and Spain were mostly located in industrial districts and did actually cooperate; this helped in overcoming business-cultural obstacles. Second, firms can cooperate in fields like technology because they do not establish a competitive advantage; heavy investment in new equipment and a strong effort to establish quality management concepts (like Kaizen and 5S) are no more than a precondition for survival in an increasingly sophisticated industry. Competitive advantages are established through innovative design, logistics, and marketing concepts, and firms are keen not to reveal their tricks in these fields. Finally, also in the case of the tile industry the importance of local cooperation seems to be declining, and giving way to more internationally coordinated value chains. A special feature of the tile industry is that the developing country cluster – Criciúma tile producers – has so far benefited from the fierce rivalry among Italian machinery and Spanish glaze producers, while being able to maintain its own presence in final markets. In a way these examples already put forward what may well be three of the more general reasons why the Italianate trajectory is scarcely to be found in developing countries. First, for small firms in developing countries it is even harder to be able to afford the investments in technology to keep up with rising quality standards. While Italianate industrial districts have been very successful in implementing incremental innovations, a big question is whether they can cope with more radical changes in technology requirements. Therefore, it seems fairly unrealistic to expect small firm clusters in developing countries to be able to conquer a part of the market niche now held by their more mechanized and computerized Italian counterparts who also possess much more experience with fashion-oriented high-road manufacturing. Nevertheless, the Italianate trajectory in principle has the highest potential for creating endogenous upgrading capabilities, precisely because of its main strength in implementing incremental process and product innovations. A second reason for the absence of an Italianate trajectory in developing countries has to do with social structure. To put it simply, I have not come across one developing-country case study that resembles the social boundary conditions for the Italianate trajectory. Clusters in developing countries are embedded in a fundamentally different setting from the Italian case studies (Amin, 1994). For example, social cohesion and the integrating role of local institutions – the pet themes in the industrial district literature – appear to be less prominent in clusters in developing countries. Instead, internal segmentation appears to reproduce and

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even strengthen inequalities. Because of extreme differences in bargaining power between actors in the cluster, possible benefits from collective efficiency are skewed in favor of leading actors and market agents (Smyth, 1992). Thirdly, a final reason not to be surprised to find so few clusters in developing countries on an Italianate trajectory is that such trajectories have become more rare also in Italy itself. In the European and Italian debate, the Italianate features are increasingly seen as a phase in a broader global industrial restructuring process. Without suggesting that the Italianate model would be inherently unsustainable, it may well be less suitable to the present situation in the world market for many of the relevant sub-sectors. Even in Italy, it now appears as though at least some of its clusters are evolving into hub-and-spoke districts with a limited number of larger leading firms and many subcontractors. This leads to a situation where producers in some of the icons of the Third Italy, like the Brenta footwear cluster, are using a strategy of ‘functional downgrading’ – withdrawing from branding, marketing and distribution – to become high-end suppliers to internationally famous brand names (Rabellotti 2004). 3.2 The second trajectory: towards a satellite district A second trajectory runs towards a satellite district, in which most small and medium firms manufacture for leading firms located outside the cluster. In many of the relevant sub-sectors, the labor intensive manufacturing process has been transferred – in steps – to manufacturers in developing countries. In many cases, the leading firms of such commodity chains in European countries have transformed themselves into trading houses, keeping a firm grip on design and marketing. Most observers consider the satellite trajectory to be least attractive, as it offers the least possibilities for building endogenous upgrading capabilities. Manufacturers who are attractive to leading international corporations for only one reason – cheap labor – are very vulnerable, as relative labor and transaction costs tend to keep changing between countries. Moreover, to be considered by global buyers for only a particular job is fatal, since jobs are constantly changing. In contrast, in resilient and interdependent inter-firm relations, leading firms are more inclined to deal with a changing situation together with known partners. A leading firm must feel confident enough to rely on the specialized capabilities of its suppliers. Especially in fashion-sensitive industries, it is, ‘too costly and time-consuming to perfect the design of new products and translate those designs into simply executed steps. Those formerly

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charged with the execution of plans – technicians, blue collar workers, outside suppliers – must now elaborate indicative instructions, transforming the final design in the very act of executing it’ (Lazerson, 1993: 215). Evidently, this is a far cry from the export processing zones’ type of assembly line work where predominantly young women without previous artisanal experience work long hours for low wages. However, being incorporated into a commodity chain controlled by a buyer outside the cluster is not all bad. Especially in the short run, important benefits may accrue to local workers. To start with, the women workers usually involved may be able to learn industrial manufacturing skills, earn their own income, and as a result possibly strengthen their bargaining position at home. At a macro level, these increased income opportunities for women may well contribute to a more equal income distribution. Secondly, for a certain period, it can achieve a substantial production volume for both the domestic and export markets, and thus diversify the industrial structure. Moreover, although the conditions of this type of employment are not very promising, they are in many ways already an improvement on alternative job opportunities. Entrepreneurs can also benefit from being part of such international commodity chains. Apart from earning large sums of money as intermediaries, they gain access to all sorts of relevant information on the international market in their specific sub-sector. In many cases local manufacturers may acquire endogenous upgrading capabilities in process and product upgrading. Moreover, in some cases entrepreneurs may even try to venture out on their own in a next phase by capturing the higher value-added stages in the commodity chain. This may start a process towards a hub-and-spoke trajectory, in which the leading actors in particular commodity chains are leading local entrepreneurs. The footwear industry in and around Madras offers a successful example where a few local industrialists are slowly capturing highervalue added stages in the commodity chain. Most of the currently renowned firms have entered the footwear industry from a leathertanning background. These firms are long-standing suppliers of mainly European footwear firms. While the Indian firms previously supplied finished leathers (1970s) and semi-finished leathers (1960s), now they also prepare uppers (1980s) and – increasingly – full shoes (1990s) for these leading actors. In turn, these foreign firms assist in setting up modern factories where non-unionised women work with modern imported machines. One of these local hub-firms was the only company from India that had its own stall in one of the upper-market exhibition halls at the main European shoe fair in Dusseldorf in March 1997.

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However, such examples are rare. On the whole, it seems that while most groups of exporters can be positioned on a satellite trajectory, this trajectory also provides the least likely environment for significant endogenous upgrading. 3.3 The third trajectory: towards a hub-and-spoke district The last trajectory to be discussed is a hub-and-spoke trajectory, which appears to be the most common trajectory for clusters in developing countries. According to Nadvi and Schmitz (1994: 12): ‘most LDC clusters tend to be distinguished by internal hierarchies’. The most typical example is the case of the Korean chaebol, where small firms orbit around large industrial complexes. In the Brazilian Sinos valley (a shoe cluster), small firms tend to operate rather separately from a few Fordist giants (Schmitz, 1995). In many of the south Asian clusters, one tends to find a combination of the above two trends. A few leading families, who own the largest, more modern factories in the cluster (which are by international standards usually semi-mechanized medium-scale units), dominate local industry through the local business associations and mould the cluster image as it is perceived by outsiders. Other smaller units either supply them as subcontractors or supply to other, usually less attractive, market channels. Examples include garments in Tirrupur (Cawthorne 1995 and Swaminathan and Jeyaranjan 1994) and Ahmedabad (Das, 1996a); flooring tiles in Gujarat (Das, 1996b); textile printing in Jetpur (Dupont, 1994); bicycles in Ludhiana (Kattuman, 1994); and footwear in Agra (Knorringa, 1996; 1999). Moreover, this characterization also applies to examples such as the Tegalwangi rattan furniture cluster in Indonesia (Smyth, 1992), and the footwear clusters in Peru’s Trujillo, and Mexico’s Leon and Guadelajara (Rabellotti, 1997). In most of these clusters, one finds at least three tiers of firms: At the lowest tier of the hierarchy are households and small workshops which have limited resources, produce for local consumption and seek to survive. The medium tier is occupied by firms who are better endowed (in capital and skills), are able to generate an investable surplus and produce, either directly or on (sub)contract, for the domestic and often export markets. The third tier includes firms which maintain high levels of quality, are technically innovative, capable of entering export markets, and have growth aspirations. (Nadvi and Schmitz, 1994: 12) Perhaps the main risk in a hub-and-spoke trajectory, in terms of acquiring capabilities for endogenous upgrading, is that often a few leading

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families try to monopolize benefits and become a source of conservatism instead of innovation, even though they have the financial capacity to invest in upgrading. Many of the south Asian case studies tend to indicate how such ‘fat cats’ are often a drag on innovative behavior or at least prevent cluster-wide diffusion of the acquisition of upgrading capabilities (Cawthorne, 1995; Das, 1996b; Knorringa, 1996). Clusters not only need to acquire capabilities to implement incremental innovations. Particularly clusters in developing countries also need to be able to deal with radical changes in their environment. A main threat-cum-challenge for the manufacturing of tradables in many developing countries is the onslaught of the New Competition (Best, 1990) in export markets, combined with a general trend of economic liberalization in developing countries. The case studies available on the impact of the New Competition and economic liberalization on the performance of clusters, tend to show that they are resilient and that they do upgrade but that, in response, the internal structure of clusters also changes.6 Some actors lose out, power becomes more concentrated, and the hub-and-spoke trajectory appears to become more pronounced. To summarize, the potential for endogenous upgrading is highest in the least-found Italianate trajectory, while it is lowest in the most frequently found satellite trajectory. The hub-and-spoke trajectory forms the intermediate case; it is increasingly found and does possess a selective potential for upgrading in process and product upgrading, but by and large not in functional upgrading.

4. Concluding remarks The clearest and hardest message emerging from the European industrial district literature is that: ‘none of the industrial districts are the result of planned action, of a local or regional industrial strategy. They all developed spontaneously’ (Schmitz and Musyck, 1994: 902). This chapter has attempted to show the usefulness of systematizing the wide-ranging experiences among more mature industrial clusters in developing countries along three trajectories. This attempt to systematize does not include the largest category of clusters in developing countries, i.e., survival clusters. The trajectory towards an Italianate district, which offers the greatest potential for endogenous upgrading, is very rare in developing countries. The reasons for this include the lack of technological innovative capabilities and resources in most clusters in developing countries, and

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the fundamentally different institutional setting in which social inequalities are often strengthened because of extreme differences in bargaining power between actors in the cluster. In contrast, the trajectory towards a satellite district, which appears to offer the least potential for endogenous upgrading, is the most commonly found among clusters in developing countries. Alternatively, a trajectory towards a hub-and-spoke district offers an intermediate situation; it provides more potential for endogenous upgrading then the satellite trajectory, and an increasing number of clusters in developing countries seem to portray hub-and-spoke features. In terms of policy options, one might argue that a trajectory towards a hub-and-spoke district is the most feasible and potentially most useful metaphor to keep in mind, with the following qualifications. Policy makers should aim at facilitating the capture of higher-value added stages in the value chain, support attempts to acquire innovative technological capabilities, and especially facilitate platforms to enable internal conflict solving. It should be a primary task of policy implementers to contribute to internal conflict resolving by not siding automatically with the leading entrepreneurs, but by trying to operate as a mediator in local power struggles by supporting the build-up of countervailing power. It is of crucial importance that local conflicts be addressed, and not neglected or hidden, because the Italian experience appears to indicate that periods of innovative growth tended to be preceded by successfully settling such struggles.

References Alam, G. (1994), ‘Industrial Districts and Technological Change: A Study of the Garment Industry in Delhi’, Technological Dynamism in Industrial Districts: An Alternative Approach to Industrialization in Developing Countries?, UNCTAD, New York and Geneva, pp. 257–66. Albino, V., Garavelli, A.C. and Pontrandolfo, P. (1996), ‘Local Factors and Global Strategies of The Leader Firm of an Industrial District’, Paper presented at EurOMA Conference on Manufacturing Strategy, London, June. Asheim, B.T. (1992), ‘Flexible Specialization, Industrial Districts and Small Firms: A Critical Appraisal’, in H. Ernste and V. Meier (eds), Regional Development and Contemporary Industrial Response. Extending Flexible Specialization, Belhaven Press, London, pp. 45–63. Benjamin, S.J. (1991), ‘Jobs, Land and Urban Development. The Economic Success of Small Manufacturers in East Delhi, India’, Lincoln Institute of Land Policy, Cambridge, Massachusetts. Best, M.H. (1990), The New Competition. Institutions of Industrial Restructuring, Polity Press, Cambridge.

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Brusco, S. (1990), ‘The Idea of the Industrial District: Its Genesis’, in F. Pyke, G. Becattini and W. Sengenberger (eds), Industrial Districts and Inter-Firm Co-operation in Italy, International Institute for Labor Studies, Geneva, pp. 10–19. Cawthorne, P.M. (1995), ‘Of Networks and Markets: The Rise and Rise of a South Indian Town, the Example of Tiruppur’s Cotton Knitwear Industry’, World Development, Vol. 23(1): 43–56. Das, K. (1996a), ‘Flexibly Together: Surviving and Growing in a Garment Cluster, Ahmedabad, India’, Journal of Entrepreneurship, Vol. 2. Das, K. (1996b), Collective Dynamism and Firm Strategy: The Flooring Tile Cluster in Gujarat, India, Gujarat Institute of Development Research, Working Paper, No. 76. Dei Ottati, G. (1996), ‘Trust, Interlinking Transactions and Credit in the Industrial District’, Cambridge Journal of Economics, Vol. 18(6): 529–46. Dupont, V. (1994), ‘Facets of Industrial Clustering and Flexibility in the TextilePrinting Industry of Jetpur (West India)’, Paper presented to a workshop on Flexible Specialization in Pondicherry, India, 25–26 March. Farbman, M. and Lessik A. (1989), ‘The Impact of Classification on Policy’, in A. Gosses et al. (eds), Small Enterprises, New Approaches, Proceedings of the Workshop Small Scale Enterprise Development, In Search of New Dutch Approaches, March, 6–7 Ministry of Foreign Affairs, Directorate General International Cooperation, The Hague, pp. 105–22. Gereffi, G. (1999), ‘International Trade and Industrial Upgrading in the Apparel Commodity Chain’, Journal of International Economics, Vol. 48(1): 37–70. Grosh, B. and Somolekae, G. (1996), ‘Mighty Oaks from Little Acorns: Can Microenterprise Serve as the Seedbed of Industrialization?’, World Development, Vol. 24(12): 1879–90. Heinen, E. and Weijland, H. (1980), ‘Rural Industry in Progress and Decline’, in van Gelder, P. and Bijlmer, J. (eds), About Fringes, Margins and Lucky Dips. The Informal Sector in Third World Countries, Free University Press, Amsterdam. Humphrey, J. (1995), ‘Industrial Reorganization in Developing Countries: From Models to Trajectories’, World Development, Vol. 23(1): 149–62. Humphrey, J. and Schmitz, H. (1996), ‘The Triple C Approach to Local Industrial Policy’, World Development, Vol. 24(12): 1859–77. Kattuman, P.A. (1994), ‘The Role of History in the Transition to an industrial District: The Case of the Indian Bicycle Industry’,Paper prepared for a workshop on Flexible Specialization in Pondicherry, India, 25–26 March. Kinyanjui, M.N. (1997), ‘Tapping Opportunities in Enterprise Clusters in Kenya: The Case of Enterprises in Ziwani and Kigandaini’,Paper presented at a workshop on Collective Efficiency at the Institute of Development Studies, Sussex, UK, April. Knorringa, P. (1996), Economics of Collaboration; Indian Shoemakers Between Market and Hierarchy, Sage Publications, New Delhi and London. Knorringa, P. (1999), ‘Agra: An Old Cluster Facing the New Competition’, World Development, Vol. 27(9): 1587–604. Lazerson, M. (1993), ‘Factory or Putting-out? Knitting Networks in Modena’, in G. Grabher (ed.), The Embedded Firm. On the Socioeconomics of Industrial Networks, Routledge, London, pp. 203–26. Lazerson, M. and Lorenzoni G. (1996), ‘A Return to the Italian Source: The Networks that Feed Industrial Districts’, Mimeo.

Peter Knorringa 207 Markusen, A. (1996), ‘Sticky Places in Slippery Space: A Typology of Industrial Districts’, Economic Geography: 293–313. McCormick, D. (1994), ‘Industrial District or Garment Ghetto? The Case of Nairobi’s Mini-Manufacturers’, Paper presented at an EADI workshop in Vienna, November 1994. McCormick, D. (1999), ‘African Enterprise Clusters and Industrialization: Theory and Reality’, World Development, Vol. 27(9): 1531–52. Meyer-Stamer, J. (1997), ‘Path Dependence in Regional Development: Persistence and Change in three Industrial Clusters in Santa Catarina, Brazil’, Paper presented at a workshop on Collective Efficiency at the Institute of Development Studies, Sussex, UK, April. Meyer-Stamer J., Maggi C. and Seibel S. (2004), ‘Upgrading in the Tile Industry of Italy, Spain and Brazil: Insights from cluster and value chain analysis’, in H. Schmitz (ed.), Local Enterprises in the Global Economy, Cheltenham, Edward Elgar, pp. 174–99. Nadvi, K. (1996), ‘Small Firm Industrial Districts in Pakistan’, Doctoral Thesis Institute of Development Studies, Sussex University. Nadvi, K. (1999), ‘Collective Efficiency and Collective Failure’, World Development, Vol. 27(9): 1605–26. Nadvi, K. (2004), ‘The effect of global standards on local producers; A Pakistani case study’, in H. Schmitz (ed.) Local Enterprises in the Global Economy, Cheltenham, Edward Elgar, pp. 297–325. Nadvi, K. and Halder, G. (2005), ‘Local Clusters in Global Value Chains: Exploring Dynamic Linkages between Germany and Pakistan’, Entrepreneurship & Regional Development, Vol. 17: 339–63. Nadvi, K. and Schmitz, H. (1994), ‘Industrial Clusters in Less Developed Countries: Review of Experiences and Research Agenda’, Institute of Development Studies, Discussion Paper, No. 339, Institute of Development Studies, Sussex. Pedersen, P.O. (1997), ‘Clusters of Enterprises Within Systems of Production and Distribution: Collective Efficiency and Transaction Costs’, in M.P. van Dijk and R. Rabellotti (eds), Enterprise Clusters and Networks in Developing Countries, Frank Cass, London, pp. 11–29. Penn, R. (1994), ‘Contemporary Relationships between Firms in a Classic Industrial Locality’, in J. Rubey and F. Wilkinson (eds), Employment Strategy and the Labor Market, Oxford University Press, Oxford. Porter, M.E. (1990), The Competitive Advantage of Nations, New York, Free Press. Rabellotti, R. (1995), ‘Is There an “Industrial District” Model? Footwear Districts in Italy and Mexico Compared’, World Development, Vol. 23(1): 29–41. Rabellotti, R. (1997), ‘Devaluation Bonanza or Something More? Increasing Collective Efficiency Behind the Recovery of the Mexican Footwear Clusters’, Paper presented at a workshop on Collective Efficiency at the Institute of Development Studies, Sussex, UK, April. Rabellotti, R. (2004), ‘How Globalization affects Italian Industrial Districts: The Case of Brenta’, in H. Schmitz (ed.), Local Enterprises in the Global Economy, Cheltenham, Edward Elgar, pp. 140–73. Schmitz, H. (1995), ‘Collective Efficiency: Growth Path for Small-Scale Industry’, Journal of Development Studies, Vol. 31(4): 529–66.

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Schmitz, H. and Musyck, B. (1994), ‘Industrial Districts in Europe: Policy Lessons for Developing Countries?’, World Development, Vol. 22(6): 889–910. Schmitz, H. and Knorringa, P. (2000), ‘Learning from Global Buyers’, Journal of Development Studies, Vol. 37(2): 177–205. Smyth, I. (1992), ‘Collective Efficiency and Selective Benefits: The Growth of the Rattan Industry of Tegalwangi (Indonesia)’, in J. Rasmussen, H. Schmitz and M.P. van Dijk (eds), ‘Flexible Specialization: A New View on Small Industry’, IDS Bulletin, Vol. 23(3): 51–6. Swaminathan, P. and Jeyaranjan, J. (1994), ‘The Knitwear Cluster in Tiruppur: An Indian Industrial District in the Making?’, Madras Institute of Development Studies, Working Paper, No. 126.

11 A Sectoral Approach to Policies for Clusters and Value Chains in Latin America1 Carlo Pietrobelli and Roberta Rabellotti

1. Introduction and theoretical hypotheses Does enterprise participation in global markets ensure sustainable income growth? Policies have been often designed in the belief that this was the case. Yet, competitiveness and participation in international markets may take very different forms, and benefit developing countries to a remarkably different extent. This chapter explores the role that sectoral policies may play to foster Latin American small- and medium-sized enterprises’ (SMEs) participation in global markets in a way that provides for sustainable growth. The latter may be defined as the ‘high road’ to competitiveness, contrasting with the ‘low road’, typical of small firms in developing countries that often compete by squeezing wages and profit margins rather than by improving productivity, wages and profits. A thoroughly different process is one of increasing and improving participation in the global economy, realizing sustained income growth. The difference between the high and the low road to competitiveness is often explained by the different capabilities of firms to ‘upgrade’ (Humphrey and Schmitz, 2002a; Kaplinsky and Readman, 2001; Porter, 1990). The literature on competitiveness defines upgrading as the ability to make better products, make them more efficiently, or move into more skilled activities. We explicitly relate this ability to innovation, and define ‘upgrading as innovating to increase value added’. This concept of upgrading may be effectively described for enterprises working within a value chain, where four types of upgrading are singled out (Humphrey and Schmitz, 2000): (i) Process upgrading is transforming inputs into outputs more efficiently by re-organizing the production system or introducing superior 209

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technology (e.g. footwear producers in the Sinos Valley, Schmitz, 1999b); (ii) Product upgrading is moving into more sophisticated product lines in terms of increased unit values (e.g. the apparel commodity chain in Asia upgrading from discount chains to department stores, Gereffi, 1999); (iii) Functional upgrading is acquiring new, superior functions in the chain, such as design or marketing or abandoning existing lowvalue added functions to focus on higher value added activities (e.g. Torreon’s blue jeans industry upgrading from maquila to ‘fullpackage’ manufacturing: Bair and Gereffi, 2001); (iv) Intersectoral upgrading is applying the competence acquired in a particular function to move into a new sector. For example, in Taiwan competence in producing TVs was used to make monitors and therefore move into the computer sector (Humphrey and Schmitz, 2002b, Guerrieri and Pietrobelli, 2004). Capitalizing on one of the most productive areas of the recent literature on SMEs, we restrict our field of research to small enterprises located in clusters. As a matter of fact, there is now a rich empirical evidence (Humphrey, 1995; Nadvi and Schmitz, 1999; Rabellotti, 1997) showing that small firms in clusters, both in developed and developing countries are able to overcome some of the major constraints they usually face: lack of specialized skills, and difficult access to technology, inputs, market, information, credit and external services. Nevertheless, the literature on clusters, mainly focused on the local sources of competitiveness coming from intra-cluster vertical and horizontal relationships generating ‘collective efficiency’ (Schmitz, 1995), has often neglected the increasing importance of external linkages. Due to recent changes in production systems, distribution channels and financial markets, and to the spread of information technologies, enterprises and clusters are increasingly integrated in value chains that often operate across many different countries. The literature on global value chains (GVCs) (Gereffi, 1999; Gereffi and Kaplinsky, 2001) calls attention to the opportunities for local producers to learn from the global leaders of the chains that may be buyers or producers. The internal governance of the value chain importantly affects the scope of local firms’ upgrading (Humphrey and Schmitz, 2000). This chapter exploits original evidence on Latin America, and suggests that both the local and global dimensions matter at once and firms

Carlo Pietrobelli and Roberta Rabellotti

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often participate in clusters as well as in value chains. Both forms of organization offer opportunities to foster competitiveness via learning and upgrading. However, they have also remarkable drawbacks, as, for example, upgrading may be limited in some forms of value chains, and clusters with little developed external economies and joint actions may have little influence on competitiveness. In addition, both strands of literature were conceived and developed to overcome the sectoral dimension in the analysis of industrial organization and dynamism. On the one hand, studies on clusters, focusing on agglomerations of firms specializing in different stages of the filière, moved beyond the traditional units of analysis of industrial economics: the firm and the sector. On the other hand, in the value chain literature, the main differentiation is between buyer-driven versus producer-driven chains (Gereffi, 1994), and sectors usually fit in either form. Nevertheless, the nature of the industrial sector plays a role and affects SMEs learning and upgrading strategies. To this aim, in order to account for the different learning, innovation and upgrading patterns of different sectors – as long acknowledged by several scholars (Pavitt, 1984, Bell and Pavitt, 1993) – we propose a categorization of the sectors prevailing in Latin America. This is: a) traditional manufacturing industries (e.g. textile, footwear, tile and furniture); b) natural resource-based industries (NR-based) (e.g. copper, marble, fruit, fish); c) complex product systems’ industries (COPS) (e.g. automobile, auto-parts, aeronautics and consumer electronics); and d) specialized suppliers (in this study essentially software). For each group we analyse the impact of collective efficiency and of the pattern of value chain governance on upgrading strategies (Giuliani et al., 2005). Our original contribution to the literature lies in taking into account all these dimensions at once. Thus, we investigate the hypothesis that enterprise upgrading is simultaneously affected by firm-specific efforts and actions, and by the environment in which firms operate. The latter is crucially shaped by three characteristics: (i) the collective efficiency of the cluster in which SMEs operate; (ii) the pattern of governance of the value chain in which SMEs participate, and (iii) the peculiar features that characterize learning and upgrading patterns in specific sectors. This allows us to focus on how policies may foster SMEs’ ‘high-road’ to competitiveness. The research on which this chapter is based explores this hypothesis with novel empirical evidence on a selection of SME clusters in Latin America (Pietrobelli and Rabellotti, 2004, 2007). On the basis of

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this empirical evidence, we explore the implications for the design and implementation of policies, which need to take into account the specific features of industrial sectors.

2. Results from empirical analysis In this chapter we present the results of the qualitative and quantitative exploration of the hypothesis that SMEs’ upgrading is affected by the degree of collective efficiency of the cluster in which SMEs operate, by the pattern of governance of the value chain in which SMEs participate, and by the peculiar features that characterize learning and innovation patterns in specific sectors. This three-dimensional analysis is based on the collection of original data from 12 new clusters in Latin America (Table 11.1), and on an extensive review of cluster studies available in the literature.2 The list of cases, while necessarily not complete, is the largest available – to our knowledge – on which comparative exercises have been carried out, and provides a good approximation to the reality of clusters and value chains in LA. The analysis consists of a systematic attempt to quantify on Likert scales, for each of the clusters investigated, the dimensions that are object of analysis: degree of collective efficiency and levels of upgrading. Cluster studies have also been categorized according to the type of value chain they are connected to. To quantify the degree of collective efficiency, we carefully assessed the main components of collective efficiency (CE) – external economies (EE) and joint action ( JA). Hence, a value ranging from absent (0) to high (3) was attributed to the following components: specialized labor market, local availability of inputs, easy access to information and markets for external economies, and backward and forward vertical linkages, horizontal bilateral and multilateral linkages for joint action.3 The same we did with reference to product, process, functional and intersectoral upgrading: a value ranging from absent (0) to high (3) was attributed to each of these types of upgrading. The values have been determined during either the original field-studies, or, in the cases reviewed from existing literature, from the context and specific wording of papers. Finally, we identified the number and mode of governance (market, network, quasi-hierarchy and hierarchy) of the value chains in which the clusters feed into.4 The original empirical evidence presented in this report enables several important conclusions that are summarized in the rest of this section.

Table 11.1 Basic characteristics of the Latin American clusters in this study Cluster

Country

Date of creation

Number of firms

Production 2002 (US$ mill)


Exports Exports Direct 2002 (US$ 1996 (US$ jobs mill) mill)

Indirect Jobs

1 Salmon – Austral Region (NR-based)

Chile

1978

65 + 150

1 005.0

500.0

970.0

480.0

29 000

12 500

2 Milk and dairy – Boaco, Chontales (NR-based)

Nicaragua mid 1990s

10.605

31.8

25.4

12.7

2.9

15 624

6544

3 Mangoes – PetrolinaJuazeiro (NR-based)

Brazil

1980s

330

37.0

8.0

51.0

22.0

17 400

11 600

4 Grapes – PetrolinaJuazeiro (NR-based)

Brazil

1980s

250

56.0

45.0

34.0

10.0

5 Melons – Rio Grande do Norte (NR-based)

Brazil

1980s

120

13.0

19.0

38.0

25.0

19 000

12 500

6 Apples – Santa Catarina (NR-based)

Brazil

1960s

750

51.7

23.3

31.0

6.0

23 500

6800

7 Furniture – Chipilo, Mexico Puebla (traditional manufacturing)

1987

146

6.7

17.5

7.0

17.1

5400

8 Metalworking, Espírito Santo (COPS)

1988

66

33.3

23.3

1.7

1.1

12 000

48 000

(Continued)

213

Brazil

–

Cluster

Country

Date of creation

Number of firms

9

Software – Aguascalientes (specialised suppliers)

Mexico

2000s

13

10

Software – D.F. (specialised suppliers)

Mexico

1980s

130

11

Software – Guadalajara (specialized suppliers)

Mexico

1990s

152

12

Software – Monterrey (specialized suppliers)

Mexico

1982

76



Exports 2002 (US$ mill)

Exports 1996 (US$ mill)

4.3

–

–

–

121

–

57.5

–

–

–

2000

–

–

–

–

–

1040

–

120.0

–

–

2000

–

51.1

Source and Notes: Field studies carried out for the present study. – not available (1) 65 firms in main value chain, 150 additional local providers. 40 percent of direct jobs are seasonal. (3–6) For Brazilian fruit clusters sources are: IBGE (www.ibge.gov.br) for production and SECEX (www.aliceweb.desenvolvimento.gov.br) for exports. (3 and 5) These figures are incompatible since value of exports exceeds value of production. (7) Figures for 1996 instead of 1995. (8) Only figures on enterprises associated to the local Center for the Development of Metalworking Industry (CDMEC). (11) In Jalisco (Guadalajara) only 60 firms are formally registered.

Direct jobs

Indirect Jobs

214

Table 11.1 (Continued)

Carlo Pietrobelli and Roberta Rabellotti Table 11.2

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Index of collective efficiency: average

Traditional manufacturing NR-based COPS Specialized suppliers

EE

JA

CE Index*

7.6 8.91 7.61 9.1

5.23 7.36 4.8 7.8

6.31 8.2 6.19 8.7

Note: Collective efficiency index = 0.5*EE + 0.5*JA Source: Authors’ database.

2.1 Collective efficiency enhances SME upgrading On average, collective efficiency appears to reach higher levels in NRbased and software clusters (Table 11.2). Clusters in COPS record lower levels of CE, especially due to infrequent joint action. All clusters share the advantages of a local labor market, sometimes the by-product itself of geographical clustering. Inputs are also locally sourced, except for COPS, where the logic of global sourcing prevails. Moreover, passive external economies are more common than the various forms of joint action in all the groups considered (Table 11.3). This confirms that joint actions require specific investments, and firms get involved in cooperation only if they have to face some external challenges like for example new competitors, an innovation to adopt or a new market to enter (Schmitz, 1999a). In some cases, the poor degree of collective efficiency may seriously hinder upgrading. For example, this has hindered the development of the Chipilo cluster (Zepeda, 2007), and helps provide some important general lessons:

• clusters take time to develop. Passive external economies may be given, but cooperative attitudes and joint actions take much longer to develop. The Chilean salmon cluster has taken nearly a decade to develop (Maggi, 2007). The metalworking cluster in ES has been putting efforts to promote joint actions for almost a decade before getting successful results (Cassiolato et al., 2007); • predominance of strong vertical relationships interferes with the development of external economies and hinders joint actions. This occurred in Chipilo, dominated by vertical relationships between Segusino, the leading firm, and its network of subcontractors. Very similar results are also reported in Torreón’s blue jeans cluster (Bair and Gereffi, 2001). In Nicaragua, foreign aid projects helped develop a cooperative attitude in the dairy sector, that later enhanced joint actions

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Table 11.3 External economies and joint actions (averages) External economies: average Specialized labor market (a) Traditional manufacturing NR-based COPS Specialized suppliers

Availability of inputs (b)

Easy access Market External to access economies information (d) index (c) EEI

2.36

1.76

1.7

1.83

7.6

2.55 2.56 2.8

2.45 0.94 1.5

2.09 2.11 2

1.82 1.56 2.8

8.91 7.17 9.1

Joint action: average Backward vertical linkages (a) Traditional manufacturing NR-based COPS Specialized suppliers

Forward vertical linkages (b)

Horizontal bilateral linkages (c)

Horizontal multilateral linkages (d)

Joint action index (JAI)

1.43

1.36

0.73

1.63

5.15

1.86 1.5 1.2

1.82 1.2 2

1.50 0.7 2

2.18 1.3 2.8

7.36 4.7 8.00

Source: Authors’ database.

Table 11.4 Upgrading (averages) Product Process Functional Inter-sectoral upgrading upgrading upgrading upgrading Traditional manufacturing NR-based COPS Specialized suppliers

1.86 2.64 2.44 3

2.1 2.55 2.67 3

0.7 0.55 0.94 2

0 0.36 0 0

Source: Authors’ database.

and the upgrading efforts of the small breeders and producers (Artola and Parrilli, 2007). Upgrading has occurred in most clusters analysed: however, process and product upgrading are more common while functional upgrading is more rarely achieved (Table 11.4). Collective efficiency positively affects local firms’ capabilities to upgrade. Intersectoral upgrading only occurred


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in the Chilean salmon cluster, with salmon firms venturing into biotechnology and genetics. The influence of collective efficiency on upgrading may follow several channels including the local institutional network, the public support to local joint actions, research centers, universities, international cooperation (e.g. salmon cluster in Chile, mango cluster in PJ, apple cluster in SC, Brazil). 2.2 Many value chains coexist in the same cluster and their strategic governance affects SME upgrading Participation in GVCs dominated by large buyers and/or producers from the developed world facilitates the link with the international market by signaling the need and the modes of the necessary upgrading. Nevertheless, in many cases, and more often in COPS and NR-based clusters, global leaders do not normally foster and support the SME upgrading process. In contrast, in traditional industries large international buyers often facilitate process and product upgrading. This depends on the characteristics of products, whose technology is not customized: in these industries knowledge on products and processes cannot easily be codified in technical norms and is largely tacit, and the quality of products depends on the specialized skills of local producers. Therefore, foreign buyers and chain leaders have the incentive to help local providers to upgrade products and processes, as the risk of non-compliance and late delivery of insufficient quality products is high and very costly. Thus constant monitoring and supervision of local producers is an imperative. Functional upgrading is rarely achieved in the clusters analysed, and this is also the result of the strategic governance of the value chain leaders. In traditional manufacturing, COPS and NR-based clusters local suppliers are discouraged from functional upgrading by their main buyers who do not want to share their core competencies in design, marketing and sale with local suppliers. In most cases, GVC are characterized by a quasi-hierarchical governance: the leaders of these chains control the phases with the highest value added as design, marketing and branding, and producers from developing countries often rely on a few buyers. However, different types of chains often coexist in the same cluster. Many of the clusters do not exclusively participate in quasi-hierarchical chains but also in chains where market conditions dominate. These offer the largest opportunities to functionally upgrade (e.g. Nicaragua dairy cluster and Brazil shoe cluster in Sinos Valley) (Artola and Parrilli, 2007; Bazan and Navas-Aleman, 2003).

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2.3 Sectors matter This is justified on empirical grounds: significant inter-cluster differences emerge when considering the specific features of learning, innovation, and industrial organization of the different sector groups. Clusters and value chains belonging to different groups of industries tend to follow systematically different patterns of collective efficiency, modes of chain governance, and upgrading. In NR-based clusters, process and product upgrading are often related to the scientific base of the activity. Successful clusters of upgrading SMEs in these sectors have often been supported by public–private joint actions, chiefly oriented to research and technology extension services (e.g. fresh fruit SC and PJ clusters in Brazil, salmon cluster in Chile, sugar in Valle del Cauca, Colombia) (Gomes, 2007; Maggi, 2007 and Millan, 2002). Traditional manufacturing clusters may be considered ‘supplierdominated’ as major process innovations are introduced by machinery and materials producers. Upgrading may occur by incremental developments and imitating new products’ designs, sometimes helped by large buyers, who have to rely on the specialized competencies of their local suppliers. However, integration into value chains is a two-edged sword, because on the one hand it facilitates inclusion and rapid enhancement of product and process capabilities; on the other hand, though, SMEs become tied into relationships that prevent functional upgrading and leave them dependent on a small number of powerful customers (e.g. Sinos Valley footwear cluster, Brazil) (Schmitz, 1999b). The access to alternative value chains, with a less hierarchical governance structure and targeting a different market, may offer powerful opportunities to upgrade functionally and enter higher value-added segments of the chain. This has also occurred in the dairy cluster in Nicaragua, with local producers’ cooperatives entering chains alternative to the one led by Parmalat (Artola and Parrilli, 2007). In Complex Product Systems (COPS), the design and development of parts and components of a complex product generate technological accumulation and upgrading, and global value chains are dominated by large assemblers and by their first-tier suppliers. Local suppliers (which are second or third-tier) are required to attain high quality standards and certifications to be part of the subcontracting network, but the lead firms have little understanding and interests in the upgrading concerns of local firms. This set-up offers very few alternatives to local SMEs. The ES metalworking cluster in Brazil, in spite of its being anchored to large commodity exporters, draws useful light on how a local SME cluster may


219

benefit from its good level of CE, and follow a collaborative strategy with the anchor, supported by the local government (Cassiolato et al., 2007). In the software clusters in Brazil and Mexico, firms are usually demanddriven as they develop or adapt software packages to the specific requirements of their local clients. Barriers to entry are low, and proximity to demand encourages start-ups near major clients, and offers the opportunity to develop several market niches (e.g. in Mexico software for tourism applications in the South, and for the oil industry on the Pacific coast). Functional upgrading is more likely to occur than in other sectors because it is favored by the ease of software firms to engage in design and commercialization of their activities. The relationship with clients is usually of a market/network type, and the lead-firms facilitate access to markets, and sustain the formation of a skilled labor force. However, leaders do not provide direct knowledge transfer to locally owned firms, which often perform low value added activities (Ruiz Duran, 2003). Collective efficiency plays a clear role through various means. The relationships with higher education institutions, resulting in a good endowment of cheap and qualified technical workforce and engineers, are essential. Spin-offs seem to be a way of diffusing capabilities locally. In some cases, previous employees of the leading firm found the subcontracting firms, and this in turn fosters smooth collaborative relations with the leaders.

2.4 The power of the macroeconomic framework Favorable macroeconomic conditions are important for all types of clusters, but particularly essential in traditional manufacturing. Similarly, unfavorable macro conditions may rapidly revert success into failure. These are sectors where comparative advantage is based on low labor costs, with new entrants constantly coming from developing countries and crowding out higher-wage and lower-productivity producers. Local potential competitive advantages (e.g. due to external economies and joint actions) cannot reverse unfavorable macroeconomic conditions, such as for example an exchange rate management discriminating against exports. In addition, competitive factors are not given forever, because market niches are likely to attract competitors and macro conditions can rapidly change. Thus, innovation – and its local diffusion – could be locked in by the strategy of a large firm, as in the melon cluster of RN, Brazil, where the two largest firms did not need to upgrade for many years, due

220


to very special market circumstances prevailing, and consciously prevented technology and innovation to diffuse (Gomes, 2007). Similarly, the export success of Segusino, the lead-firm in the Chipilo furniture cluster, did not last because of several reasons, including the failure in undertaking local joint actions (e.g. a technology center), firm-level errors and miscalculations, but also the real appreciation of the Mexican exchange rate (Zepeda, 2007).

3. A sectoral approach to the design and implementation of policies and programs to support SMEs upgrading in clusters and value chains After several years of debates and field experimentation, some degree of consensus has been reached on the design and implementation of policies and programs to support SMEs in clusters and value chains. We try to summarize this in Table 11.5, presenting a ‘menu of actions’, which are organized along three main sets of (complementary) actions: enhancing the development of external economies, promoting linkages, strengthening local positions within a value chain. These proposals are not based on abstract theorizing but on the detailed scrutiny of our original case studies, and on international comparisons and best practices available from the specialized literature.5 The approach suggested here constantly advocates a context-specific approach to policy-design and implementation. Which action (or combination of actions) a cluster should choose depends on its characteristics, its actual degree of collective efficiency, its main sector of specialization and the characteristics of the value chains in which it operates – most importantly, its mode of governance. Besides, it also depends on the stage of its life cycle, given that policies need to evolve over time to reflect cluster evolution. However, given the remarkable sectoral differences emerging from the empirical evidence collected in this research project, in spite of some overlapping, the policy priorities are different in several respects for the different groups of sectors. In this section we overview them in sequence (Table 11.5). 3.1 Traditional manufacturing clusters A preliminary condition that should be ensured by all possible means, and that is relevant everywhere but especially in traditional manufacturing sectors, is the need to maintain macro conditions under control. Recent examples from Mexico and Argentina illustrate this


221

A menu of actions to support cluster development

⇒ Facilitate the development of External Economies • Build a specialized labor force – Cluster Skill Centers ⇒ Promote linkages between firms: • Create and enhance trust between firms • Promote the establishment of collective projects • Create and strengthen business associations • Strengthen local supply of financial and non-financial services • Facilitate external connections of the cluster • Promote innovation ⇒ Strengthen the local position within value chains • Attract the chain leaders into the clusters • Sustain the upgrading of suppliers • Facilitate the interaction within value chains • Promote access to new markets and value chains • Assist SMEs in meeting international standards Source: Based on authors’ field studies.

point. Research has shown that in traditional manufacturing clusters external economies and, above all, joint actions help upgrading remarkably, also if the cluster – or some firms of it – participates in a global value chain. The development of collective efficiency in the cluster (promoting vertical and horizontal joint actions, increasing firms’ sensitivity to co-operation) may be sustained with several actions described in section 3.1. Finally, support to promote access to larger (and foreign) markets is especially relevant in this group. A cluster policy should therefore constantly monitor new developments in technologies and international markets, and help provide local producers with market outlets alternative to their VC, and with stronger power of negotiations with the current main VC. This is especially necessary when the value chain is quasi-hierarchically governed, as in most traditional manufacturing sectors, and leaves ground only for product and process upgrading, but keeps a strong hold over its core areas of competence, and inhibits the functional upgrading of its providers. Actions to foster clusters’ search for markets alternative to their main value chains could include: support marketing and branding of the cluster (e.g. ‘Made in Brazil’ project in the Sinos Valley shoe cluster, or Salmoexport in the Chilean salmon cluster); support the creation of export networks; sustain collective participation in international trade fairs.

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3.2 Natural resource-based clusters In NR-based clusters, an essential field of intervention is the access to scientific knowledge, clearly a necessary condition for participating in global value chains. If research is concentrated in the leader of the chain, SMEs do not easily get access to these findings (i.e. the case studies on Rio Grande do Norte in Brazil in Gomes, 2007). The role played by public, local research institutions aimed at carrying out research, disseminating findings, and assisting SMEs to adapt and internalize the research advancements in their production process therefore become very important. On the other hand, the development of efficient and effective local public research institutions is often difficult for various reasons:

• there is no collaboration between local institutions and large enterprises that also carry out substantial research;

• large firms also control the connections with the market from which the stimulus to innovation usually derives;

• finally, as in the RN melon cluster (Gomes, 2007), large firms may also extend their power of control on local institutions, participating in the definition of their research strategy. Therefore, policy programs should help disseminate research to SMEs, like for example with the programs developed by EMBRAPA/SEBRAE with seedless grape variety in PJ and the development of integrated production practices in PJ and SC (Gomes, 2007). This effort could be undertaken in collaboration with the public sector agricultural research agency active in each case, whenever they exist, as in Brazil with EPAGRI in SC and EMBRAPA in PJ. To this aim, public–private collaboration in research should be promoted. Given the paucity of research on the effectiveness of different mechanisms to promote public–private collaboration in research in Latin America, research in this area is especially needed. Efforts to engage SMEs in collaborations with research institutions should be pursued, in order to help guide the research priorities in directions that are useful to SMEs as well as (and not only to) large firms and traders. In these sectors, SMEs often face higher entry costs in several productive activities and in value chains. Programs and projects that explicitly benefit production by SMEs alongside larger growers should be promoted. This effort could be undertaken with public sector agricultural


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A sectoral approach to policy design

⇒ Traditional manufacturing clusters • Ensure consistency between micro support policies and programs and the overall macroeconomic framewok • Promote linkages between firms • Promote access to new additional value chains ⇒ Natural resource-based clusters • Promote public–private collaboration in research and disseminate research to SMEs • Improve skills and abilities of producers in the backward stages of the value chain (i.e. agriculture, breeding) • Facilitate the entry of SMEs • Promote the adoption of quality and sanitary standards, environmental regulations, and enforce quality inspections and controls • Promote access to foreign markets and overcome non-tariff-barriers (NTB) • Improve the access and availability of good basic infrastructures ⇒ COPS – Complex Product Systems – clusters • Promote/support the active and dynamic role of actors working as ‘network brokers’ of the cluster, and notably of the relationships between the large anchor firms and the local small suppliers; • Set up an incentive framework aimed at inducing large firms to source their intermediate inputs and services locally, and to support their suppliers’ upgrading strategies. ⇒ Specialized suppliers (software) • Invest in highly skilled professionals • Intensify industry-research collaboration Source: Based on authors’ field studies.

agencies whenever they exist (Gomes, 2007 on Brazil), and actions could include:

• • • •

allocation of lots in public projects for SMEs and larger growers, availability of working and investment capital by development banks, access to appropriate storage facilities at ports, support in participating in national and international fruit fairs where SMEs could display their products and make contacts with potential buyers.

Moreover, in this group support is also especially necessary to strengthen skills and abilities in the backward production stages along the chain. Thus, for example, the dairy cluster in Nicaragua needs to help cow breeders and small milk producers to improve their technical

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and managerial expertise, also in areas and with techniques that could be usefully applied but that are little known (e.g. cows productivity, cheese manufacturing). The main VC led by Parmalat contributed to introducing and diffusing a culture of quality in the sector, and imposed higher standards than in the past (Artola and Parrilli, 2007). However, it did not directly help small producers to fulfill such requirements, a hard task for all, and especially for those not involved in producers’ cooperatives. Quality, sanitary and environmental standards and patenting are playing a growing role in these sectors. To this aim, technical assistance may do a lot, especially if administered at the cluster level and through collective institutions and joint actions, involving small growers together with buyers and chain leaders. Policy support actions should be designed and developed together with local cluster agencies, or business associations, and may include:

• awareness-raising campaigns, directed at small producers, of the relevance of environmental and hygienic standards;

• technical assistance to help local SMEs fulfill international standards requirements;

• technical assistance to strengthen local regulatory institutions, and institutions setting environmental and sanitary standards for local producers; • conditioning of the access to loans and grants on the effective implementation and maintenance of quality and sanitary standards. In addition to the rising requirements that international standards create, other forms of non-tariff barriers to international trade are widespread in these sectors. While larger firms usually have competences and means to overcome these barriers, SMEs are especially threatened by them. Several examples may be quoted. A cooperative of small enterprises in Pará, in the Brazilian Amazon, tried to export to Europe traditional sweets made with cupuaçú (a very tasty Amazon fruit) and learned that a Japanese trading company had already registered the Indian name cupuaçú in the European Patent Office, together with the traditional process of extracting the pulp and making the sweet. Now with the support of the Brazilian government these firms are suing the Japanese firm, but the process will take some time and harm has been done. There are several similar cases, including the attempt to increase exports of cachaça, the Brazilian sugar cane spirit to the US, by a cluster of SMEs in Minas Gerais.6 These cases show that access to the external market when tried independently is very difficult, revealing the need for programs to support SMEs’ access to international markets.


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Finally, the access and availability of good basic infrastructures (e.g. roads, water, energy) is a key competitive factor for this group of sectors. Competitiveness policies at the local level should cater for such needs. 3.3 COPS – Complex Product Systems – clusters According to the evidence presented thus far, this group offers the fewest opportunities for SME upgrading, as it is governed by the global logic of large TNCs, and quasi-hierarchical value chains. However, in order to exploit the limited chances for upgrading, some policies may still be useful. A ‘network broker’ may be the appropriate institution to help the local cluster improve its collective efficiency and, notably, build bridges and negotiate with large value chain leaders. For a while she/he can be someone from an existing organization (e.g. local firms, cooperatives, institutes, universities, agencies in charge of promotion, development or financing) or an individual agent (e.g. a leading entrepreneur, researcher, consultant, policy maker). As the constraints and opportunities become clearer to the group, there must be someone available for a considerable period of time. Who should play the broker’s role? There is no ready-made recipe. What the case of CDMEC in Espírito Santo, Brazil, suggests is that it can at times be someone from a development agency run by the government; other times it may be crucial it is someone chosen among the SME’s peers; and in other situations the best choice might be someone with deeper understanding of what is taking place in the frontier of the industry and might be better prepared to foresee opportunities and challenges for the local cluster. In the ES cluster, the person who became the main cluster broker had the technical credibility of the group (his previous work was with an engineering consultancy firm) and the political ability to build bridges between SMEs and their anchor customers (Cassiolato et al., 2007). Financial backing in this stage is also essential. In the case of the Espírito Santo cluster, the local development bank (BANDES) played an important role when in 1995 it helped CDMEC to finance a study about the potential of SMEs to supply the anchor companies during their expansion projects. Moreover, the direct involvement of anchor firms is crucial to promote local SMEs upgrading. In the ES metalworking cluster, the anchor (leader) Aracruz Cellulose was essential in opening doors abroad and allowing SMEs to visit some of the paper pulp industry’s leading international companies. This enabled SMEs to present themselves as potential local

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partners for these top firms, and as they interacted with them, they learnt from technologically better-equipped customers. Nevertheless, if there is not any obvious reward for anchors to collaborate and promote suppliers’ upgrading, some external pressure must be sought. It can come from a financial institution in the format of a clause demanding improvement in their local suppliers/customers when anchor companies are being financed. Or it can come from the local government if a special license (e.g. an environmental license) is required for the operation of anchor companies (Cassiolato et al., 2007). The above evidence suggests that local governments may play an indispensable role to convince large chain leaders to foster local SMEs’ upgrading efforts. Traditionally, local-content and trade-balancing requirements were among the instruments utilized to induce TNCs to cooperate with local small providers. However, they have often produced disillusioning results, revealing that forcing TNCs usually leads to multiple inefficiencies and undermines the competitiveness of the cluster as a whole (Altenburg and Meyer-Stamer, 1999:1706). Rather, the advantages accruing to the chain leaders should be emphasized, in an effort to engage them in cooperative and mutually beneficial initiatives. Related policy programs should, whenever possible, that is whenever a tradition of collaboration is already in place and producing mutual benefits, assist second and third-tier suppliers to accumulate financial and managerial expertise needed to internationalize when they have the opportunity to follow sourcing, i.e. supplying services and parts to the same anchor-firm in its different locations. 3.4 Specialized suppliers (software) The evidence on the Brazilian (Bercovich and Swanke, 2003) and Mexican software clusters (Ruiz Duran, 2003) analysed reveals that the endowments and constant investments in qualified professionals are essential for the cluster competitiveness. To this aim, the integration with universities and higher education institutions should be sought, in order to orient the curricula in the directions useful for the industry. Moreover, policy programs may grant the incentives for highly qualified migrants (e.g. groups of Mexicans producing software in Boston) to come back and work for the cluster’s firms. Similar efforts have been successful in other software clusters in the world, such as in Bangalore, India. Furthermore, the recent Mexican experience (Ruiz Duran, 2003) suggests that cluster-based Techno poles and incubators may provide useful infrastructure support to start-ups in this sector. Also in this sector international certification is a process that is increasingly gaining strategic


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importance, and could be usefully supported by international agencies and development banks.

4. Conclusions Several policy lessons may be drawn from the research summarized in this chapter, and fully explored elsewhere (Pietrobelli and Rabellotti, 2004 and 2007). First, considering that Latin American countries generally have very limited financial resources which should be used as efficiently as possible, clusters to be supported should be selected in view of their strategic role for future growth. Besides, interventions within clusters should be directed to address few essential priorities. Given that selectivity is a very difficult task, there is a strong need to develop good tools to map and analyse clusters, investing adequate financial resources in the exploratory and diagnostics phase before interventions. The information available is often insufficient, collected for different purposes, and following a different logic. All policy design and implementation should be preceded by well-directed and purposeful analyses of the local circumstances. Several techniques are available and could be usefully employed.7 Secondly, policies need to be context-specific and – in several regards – sector-specific. They need to take into account the local specificities of the cluster and its collective efficiency, together with the mode of governance of the prevailing value chain(s), and the detailed sectoral specialization of the local area: no general recipes are valid and may be applied everywhere, regardless of local history, idiosyncrasies and peculiarities. Furthermore, policies need to evolve over time and consider the evolution of clusters and value chains. To this aim, the Chilean salmon cluster offers a remarkable example (Maggi, 2007). Finally, we do need to remind ourselves that cluster policies are not the panacea to all economic development problems. In recent times, local and national policy makers have often labeled generic initiatives to support SMEs, sectors, localities as ‘cluster policies’, creating confusion, false expectations and much disillusion and reluctance among firms to spend time and efforts on such projects.

References Altenburg, T. and Meyer-Stamer, J. (1999), ‘How to Promote Clusters: Policy Experiences from Latin America’, World Development, Vol. 27(9): 1693–713.

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Artola, N. and Parrilli, D. (2007), ‘The development of the dairy cluster in Boaco and Chontales Nicaragua’, in Pietrobelli, C. and Rabellotti, R. (eds), pp. 43–70. Bair, J. and Gereffi, G. (2001), ‘Local clusters in global chains: the causes and consequences of export dynamism in Torreon’s blue jeans industry’, World Development, Vol. 29(11). Bazan, L. and Navas-Aleman, L. (2003), ‘The Underground Revolution in the Sinos Valley: a comparison of upgrading in global and national value chain’, Paper for Workshop ‘Local Upgrading in Global Chains’ held at the Institute of Development Studies, University of Sussex, 14–17 February, 2001. Bell, M. and Pavitt, K. (1993), ‘Technological accumulation and industrial growth: contrast between developed and developing countries’, Industrial and corporate change, Vol. 2(2). Bercovich, N. and Swanke, C. (2003), ‘Cooperacao e competitividade na industria de software de Blumenau’, WP. 138, Serie Desarrollo Productivo, CEPAL/United Nations: Santiago de Chile. Cassiolato, J., Villaschi, A. and Lastres, H. (2007), ‘Local Productive and Innovation Systems in Brazil: the metal working cluster in Espírito Santo’, in Pietrobelli, C. and Rabellotti, R. (eds), pp. 77–90. Gereffi, G. (1999), ‘International trade and industrial upgrading in the apparel commodity chain’, Journal of International Economics, Vol. 48: 37–70. Gereffi, G. and Kaplinsky, R. (2001), ‘The value of value chains’, Special issue of IDS Bulletin, 32. Giuliani, E. (2003), ‘Knowledge in the Air and its Uneven Distribution: A Story of a Chilean Wine Cluster’, paper presented at the DRUID Winter Conference, Aalborg, 16–18 January. Giuliani, E., Pietrobelli, C. and Rabellotti, R. (2005), ‘Upgrading in Global Value Chains: Lessons from Latin American Clusters’, World Development, Vol. 33(4). Gomes, R. (2007), ‘Upgrading without exclusion: Lessons from SMEs in fresh fruit clusters in Brazil’, in Pietrobelli, C. and Rabellotti, R. (eds), pp. 77–180. Guerrieri, P. and Pietrobelli, C., (2004), ‘Industrial Districts Evolution and Technological Regimes: Italy and Taiwan’, Technovation, Vol. 23, September. Guerrieri P., Iammarino, S. and Pietrobelli, C. (2001), The Global Challenge to Industrial Districts: SMEs in Italy and Taiwan, Cheltenham, UK and Lyme, US: Edward Elgar. Humphrey, J. (ed.), (1995), ‘Industrial Organization and Manufacturing Competitiveness in Developing Countries’, Special Issue of World Development, Vol. 23(1). Humphrey, J. and Schmitz, H. (2000), ‘Governance and Upgrading: Linking Industrial Cluster and Global Value Chain Research’, IDS Working Paper, No.120, Institute of Development Studies, Brighton: University of Sussex. Humphrey, J. and Schmitz, H. (2002a), ‘How does insertion in global value chains affect upgrading industrial clusters?’, Regional Studies, Vol. 36(9). Humphrey J. and Schmitz, H. (2002b), ‘Developing Country Firms in the World Economy: Governance and Upgrading in Global Value Chains’, INEF Report, No. 61, Duisburg: University of Duisburg. Kaplinsky, R. (2000a), ‘Globalization and Unequalization: What Can be Learned from Value Chain Analysis?’, Journal of Development Studies, 37(2): 117–46. Kaplinsky, R. (2001), ‘Learning Networks in the South African Auto Components Industry’, Innovation News.


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Kaplinsky, R. and Readman, J. (2001), ‘How can SME producers serve global markets and sustain income growth?’, Mimeo, Brighton: University of Brighton and University of Sussex. Maggi, C. (2007), ‘The Salmon farming and processing cluster, in Pietrobelli, C. and Rabellotti, R. (eds), pp. 109–42. Nadvi, K. and Schmitz, H. (1999), ‘Industrial Clusters in Developing Countries’, Special Issue of World Development, Vol. 27(9). Nelson, R.R. and Winter, S.G. (1982), An Evolutionary Theory of Economic Change, Cambridge MA: Harvard University Press. Pavitt, K. (1984), ‘Sectoral patterns of technical change: towards a taxonomy and a theory’, Research Policy, 13. Pietrobelli, C. and Rabellotti, R. (2005), Upgrading to compete, Inter-American Development Bank, Harvard University Press. Pietrobelli, C. and Rabellotti, R. (eds) (2007), ‘Upgrading in clusters and value chains in Latin America: The role of policies’, Sustainable Development Department Best Practices Series, MSM-124, January, Inter-American Development Bank, Washington. Porter, M. (1990), The Competitive Advantage of Nations, Macmillan, London and Basingstoke. Putnam, D. (1993), Making democracy work: civic traditions in modern Italy, Princeton: Princeton University Press. Rabellotti, R. (1997), External Economies and Cooperation in Industrial Districts: a Comparison of Italy and Mexico, Macmillan, London. Ruiz Duran, C. (2003), ‘Cadenas de Valor y Clusters del Software en México’, mimeo Agorà 2000 for IDB. Schmitz, H. (1982), ‘Growth Constraints on Small-scale Manufacturing in Developing Countries: A Critical Review’, World Development, Vol. 10: 429–50. Schmitz, H. (1995), ‘Collective efficiency: growth path for small-scale industry’, Journal of Development Studies, Vol. 31(4): 529–66. Schmitz, H. (1999a), ‘Increasing returns and collective efficiency’, Cambridge Journal of Economics, Vol. 23(4): 465–83. Schmitz, H. (1999b), ‘Global competition and local co-operation: success and failure in the Sinos Valley, Brazil’, World Development, Vol. 27(9): 1627–50. Schmitz, H. (ed.) (2004), Local Enterprises in the Global Economy: Issues of Governance and Upgrading, Cheltenham: Edward Elgar. Zepeda, E. (2007), ‘The Segusino cluster boom and bust in furniture exports’, in Pietrobelli, C. and Rabellotti, R. (eds), 143–74.


Part 5 Conclusions


12 Conclusions Patrizio Bianchi

This volume offers an approach to the development problems that affect production systems that are based on the relation between high technology promotion, productivity increases and the consolidation of networks of firms. It is a collective effort that has grown out of the EU–ALFA project ‘European–Latin American Network for Research and Learning in Industrial Development Policy’, consisting of a large group of Italian, English, Dutch, Costa Rican, Mexican, Chilean, Spanish, US, Argentinean, Nicaraguan experts and, more in general, academics based in European, North, Central and South American institutions. This book focuses in particular on Latin America and Southern Europe as a geographical reference that permits analysing the processes of growth that address the strengthening of SME-based economies. In these economies hi-tech firms are currently quite isolated within their production environment, whereas the latter presents extended underdeveloped areas. These economic contexts demand a wider diffusion of competitive capacities within local production systems as a means to promote the necessary generalized improvement of the standard of living for their populations. This is motivated by the new fractures that can grow between rural and urban areas and between a small number of firms that operate at the international level and a wide majority of firms that work eminently at the local level. For this reason, the objective of the significant increase in the productivity of these developing economies require a necessary dose of realism and recognition of local specificities. In fact, the trajectories of local development are irreplicable; this depends on past history and recent events as well as on social, economic and institutional structures. As a consequence the neoliberal hypothesis proved to be simplistic in addressing the development process through macroeconomic and financial 233

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management centred on the elimination of trade barriers and the standardization of local production to the requirements of international markets. In the past few years, a broad debate has reopened on the limitations of the Washington Consensus. Simultaneously, programmes and actions have been set up to promote SME development within schemes that are shared by all international organizations that focus on adapting to local systems the successful experiences drawn from the rich and heterogeneous literature on industrial districts, clusters and networks of firms. In these years, international organizations handled the risk of re-proposing distant experiences echoed by the literature and of recommending them as solutions to very different local systems. For example, the Italian industrial districts are the result of irreplicable historical conditions; for this reason, this model cannot be simply replicated in different contexts such as in Latin America or in Southern and Eastern Asia; thus, the main objective should not be to re-propose magic solutions but rather to define a model of social aggregation that may appropriately respond to the historical conditions of the specific locality where changes are expected and development promoted. For this reason, as Mario Davide Parrilli presents in his introduction, the objective is not to re-propose abstract models but to define a systemic approach to development in which the generation of high technology, the generalized increase in the productivity of the economic system and the networks of firms are pulled together to promote a balanced and sustainable growth in both national and local production systems. The accelerated extension of the market, generated by the opening of international markets and the entry within the World Trade Organization of countries such as China, shows that the path to incremental innovation typical of industrial districts becomes insufficient. The entry of China in to global markets proposes a new competition based not only on reducing the cost of labour but also on exploiting economies of scale and agglomeration that were formerly unknown. This implies that all countries have to respond through quicker process innovation and product quality upgrading, which are unlikely to take place on the basis of the ordinary process of incremental transformation and diffusion. In the most advanced countries, the acceleration of the development process is an issue addressed through support policies that target high technology activities. In Chapters, on the Emilia-Romagna region, Laura Ramaciotti shows that one of the most advanced European regions needs to define policies to consolidate networks of innovation that in a stable form connect the university system with the firms and other service

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providers. For many years the Emilia-Romagna region represented the model of development centred on small and medium firms; this case showed that a society based on agriculture can generate good conditions for production based on firm agglomerations that hinge on social embeddedness and integration while being simultaneously oriented to international markets. This dynamism was historically based on a mechanism of diffusion of incremental innovations that involved all firms operating in different phases of the same productive cycle and all productive activities connected to the production of inputs as well as activities of distribution and service provision to the core manufacturing firms. In the ‘Emilian model’ all these phases were embedded in the local context due to a deep sense of social belonging, sustained by an efficient civic network of public institutions and services. In this environment, within the framework developed by Brusco, Sabel and Putnam, productive innovation was taking place through incremental steps involving learning processes, imitation and diffusion prompted through a continuum that structured the whole production system. Giorgio Fua wrote on the ‘development without fractures’ in which the tacit knowledge of the local system accumulated through successive contributions created the basis to promote systemic innovation. The capacity to understand market demand and to transfer this understanding of production created a cumulative process that increased the competitiveness of the system. This mechanism was operationalized in different regions, such as Tuscany, Emilia-Romagna, the north-east of Italy and wherever the key characteristics of the quasi-districts were identified. Notwithstanding this, the literature displays that even in the 1970s in the Emilia-Romagna region the mechanism of incremental diffusion was not sufficient to guarantee a position of leadership in international markets. With the formation of the regional development agency (ERVET) and the first centre for servicing the textile sector and cluster (CITER in the Modena area), the regional government produced and led an accelerated development process. This government created a network of service centres that promoted SME development within Emilian industrial districts and spurred their capacity to assume leading positions in their respective traditional sectors. This network of service centres introduced the knowledge that the system could not produce autonomously, including competitive factors in fashion up to certification processes whose bases were to be found outside the local system. In spite of these past efforts the current situation is different because the knowledge base needed to sustain the development of the regional private sector must originate from basic research (i.e. natural sciences).

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For this reason, the new network of centres that promote knowledge generation and acquisition must be the network of Emilian universities, historic institutions linked together. Laura Ramaciotti shows here that the new regional innovation policy focuses on creating a network of service centres (‘Spinners’) which stimulate the universities to jointly manage research labs that may constitute the extended and diffuse bases for the generation of knowledge relevant in the new phase of industrial development. In this way the different relevant economic areas in the region mix with the technologies that support the new industry. Schweitzer and Di Tommaso take these concepts and, analysing the case of the biotech sector in the US, show that clusters may represent a solution to the risks activated by technological changes in advanced industries; in fact, in a context of high technological turbulence and high innovation rate, the presence of a large number of firms interacting among themselves reduces the risk for the entire production system as the vulnerability of innovating firms is compensated by the variety of firms in the local territory, in a context of biodiversity that makes the industrial system dynamic and stable. Kantis and Angelelli take up this concept and re-propose its validity within the context of developing economies and, in particular, in Latin America. This contribution outlines the multiplicity of factors that promote growth and at the same time, require a favourable context that is often absent in developing countries. From this originates the need to create an adequate environment for the diffusion of knowledge, promotion of investment, and integration of experiences between the private sector and the universities. The concentration of knowledge and innovation resources in appropriate environments, such as, for example, business incubators within universities, is necessary to overcome discontinuity in knowledge accumulation. However, if this knowledge does not spread across the economy, the outcome of this effort remains well below the potential and the risk of generating a dual economy rises (between protected hi-tech areas and a traditional non-competitive economy). The many experiences of protected areas for high technology development, including ‘maquiladoras’ and the rest of export processing zones in developing economies, show the strong risk of merging two economies that do not interact with one another; the first being directly oriented to the international market, whereas the second remains totally focused on local markets. The diffusion of spillovers from hi-tech industries to the whole system implies methods of technology transfer to smaller firms that promote the role of clusters of firms as a means of increasing the productivity

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of these industries. In this area, Nicola Bellini offers a conceptual map to identify the real services that support firms and that make the local economy more complex, favouring the growth of new business subjects which become brokers of new services for the new industries. Aranguren, Audretsch and Callejon value business development services as a key point to promote the construction of a complex production system. This issue becomes even more important when the trajectory of development of new firms becomes more discontinuous. In a traditional system the new entrepreneurs are young people who joined existing firms and, within these, increased their skills and capabilities by means of direct daily transfer of competences through processes of learningby-doing. Conversely, the new university start-ups focus directly on international markets. In many cases, they represent a separate sector from the former; this implies a fracture between these firms and local firms oriented to the local market. Promoting a new entrepreneurship is essential in both Emilia-Romagna, where a specific programme of academic spin-offs has been created, and in Latin America, where, for example, Costa Rica shows that the acceleration of the local development process came from taking an export orientation together with active policies for foreign direct investment attraction within hi-tech sectors. The creation of networks of firms becomes the new modality in consolidating systems of local firms that generate knowledge linkages promoted by local agencies, universities and large firms, i.e. a multiplicity of entrepreneurial actors that Nicola Bellini defines as ‘development brokers’. Notwithstanding this, the possibility to create dynamic networks of SMEs in hi-tech sectors requires that firms build up their own internal competences in terms of specializations that permit them to complement the specializations of their partners. This is particularly evident in the biotech sector where a dynamic firm shall have a network of highly specialized firms around in order to develop conditions of mutual complementarity in both the production of existent products and in the fabrication of new products; this complementarity would take place through a continuous interaction that demands mutual trust as well as guarantees on the real capabilities that are contributed by each partner. In this sense, Suzigan, Garcia and Furtado show that the capacity to form networks of local firms implies the capacity of coordination that, in turn, attracts new attention towards the intellectual property rights of each firm. With reference to this aspect De Propris emphasizes the importance of ‘social capital’, which is taken not only as the heritage of the past or as a civic virtue, but also as the construction of a common technological

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base that makes possible the deepening of individual specializations and mutual complementarities; these capabilities are coordinated in the formation of networks of firms that constitute the bases for value chains increasingly based on research and innovation. Knorringa, and Pietrobelli and Rabellotti signal the limitations of the approach based on clusters and, in particular, on the Italian tradition of industrial districts, and refuse the idea that policies to promote the consolidation of clusters are the panacea for all problems linked to local development. The conclusions that they reach on the basis of specific Latin American cases value the multiplicity of development trajectories and their irreplicability or, more in general, the multiplicity of factors and actors that may determine the virtuous conditions for the growth of open economies. In this sense, important lessons can be learned from development experiences realized in different contexts, and a model of action can be extracted in which the key factors that guaranteed that success are identified. These factors may then be explored in new contexts, after the adequate weighing based on the different history, structure, current opportunities and competitors’ behaviour. The conviction that a SME system constitutes the real subject of development re-proposes the reflection on the factors that found industrial efficiency; thus, on the relationship between specialization and complementarity of capabilities, within models of division of labour that are defined on the basis of the effective extension of the market. In the new context of globalization, where developing countries also play an active role, new spheres of production organization need to be defined to respond to the new type of global competition. In this way the new industrial policy intervenes at different levels: on the one hand, trying to consolidate a nucleus of firms capable of generating knowledge which are well connected to the university system, that is the counterpart of the international scientific system; on the other, trying to add networks of firms linked together and in condition to transfer knowledge and to induce a structural modification in the entrepreneurial network that permits the accumulation of specific competences which are mutually complementary. This implies a policy action based on the capacity to create and to promote linkages among different actors, inducing them to develop joint actions that mutually transform them and create further complementarities. In this way a new industrial policy is designed on the basis of the conviction that it is not possible to control all phases of development, but rather the phases that activate an evolutionary process which will

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be more successful when it is animated by a multiplicity of independent actors. Within this overall framework the fundamental aspects of market competition and guarantees need not be neglected; they may permit the creation of market dynamics appropriate to contexts dominated by monopolists. In the new context the new industrial policy is oriented to promote competition through growth in productivity and competitiveness. This may be realized only in a context that protects the economic and political plurality. At the end of the nineteenth century the Sherman Act was approved with the idea that the development of the US nation could not take place under the dominating oil monopoly. Currently, the creation of monopolies in information and knowledge creation can generate strong limitations to development. Initiatives that promote the dynamism of local production systems are needed within a context of guarantee of transparent market rules and, in particular, of access to information and knowledge. In fact, the limitations of all industrial development policies are to be located in the limitations that may eventually be imposed upon democracy and economic pluralism.

Notes 1 Hi-tech development, productivity increase and networking: a systemic approach to the development of small and medium enterprises 1 Former structuralist approaches leading to the paradigm of import substitution industrialization is dismissed by neoclassicals/neoliberals on the basis of the inefficiency produced by such an allocation of public resources (finance) and the widespread phenomenon of corruption involving public institutions. 2 The more recently developed concept of ‘dynamic comparative advantages’ (Redding, 1999), which is based upon the inter-temporal accumulation of comparative advantages, does not alter the substance of the H–O argument that reaffirms the importance of national specializations based on their factor endowment. 3 The SME Department of the World Bank operates as a secretariat for the SME Development Committee of Donor Agencies (www.sedonors.org). This is a wide forum of organizations that work for SME development. 4 For example, the successful cases highlighted by the SME Department of the World Bank refer to a limited number of firms and projects managed by the Bank. This aspect makes it more difficult to measure the aggregate effects on a specific production system (World Bank, 2002). 5 Over time, the same neoclassical and neo-institutional theories have adopted the structuralist and neostructuralist views, by recognizing the problems linked to market failures and information asymmetries (Stiglitz, 1998). 6 Krugman (1994) was one of the first critics of the H–O approach on the basis of the scale economies that large firms enjoy relatively to SMEs and the market of imperfect competition. These aspects help to explain why specialization does not follow the H–O model, but often produces different patterns of international trade, such as intra-sectoral trade. 7 On these issues see also Krugman (1994), Stiglitz (1998) and Sylos Labini (2000). 8 In recent times, a network of non-conventional financial institutions (NGOs) has been growing in almost all developing countries (e.g. the Grameen Banks in Bangla-desh and the Association of Microfinance institutions – Asomif – in Nicaragua) in order to serve micro farmers and craftsmen. Nonetheless, these institutions have the capacity to supply credit for working capital only (in average no more than US$ 500–1000 per credit) and not for capital investments. Moreover, they do not have the capacity to supply credit to ‘larger’ small firms (e.g. firms with between 10 and 50 workers). 9 For details on the informal economy in Latin America see the publications of PREALC-ILO (Tokman, 1992), FLACSO (Perez Sainz, 1995), ILDIS (De Soto, 1989) and other researchers (Portes, Castells and Benton, 1989). On similar tendencies in industrialized countries see Ybarra (2003) with special reference to Spain. 240

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10 The IIC does not represent the most important branch of IADB and IADB budget, which refers to the operations of the Multilateral Investment Fund (MIF). The latter deals with mainly investments in basic infrastructures (e.g. roads, bridges, ports, sewage, etc.) and institutional reforms (e.g. social security, health, finance, etc.). 11 For a review of the projects that the IIC is supporting, see www.iadb.org. 12 The afore-mentioned literature indicates that the different kinds of network do not tend to have the same impact in the local economic environment. This aspect needs to be taken into account in the formulation of projects and in their expected results (Sacchetti and Sugden, 2003; Schmitz, 2004). 13 The analysis of the European Commission on support policies for SMEs organized in the various European countries shows common interests and actions in five key areas for the development of SMEs: ‘administrative/ entrepreneurial environment’, which refers to the frame of administrative operations that SMEs have to implement and can imply a set of administrative simplifications and incentives; ‘financial environment’, which takes into account the SME possibilities of access to finance, and the structuring of systems for venture capital, investment capital, etc.; ‘internationalization and information services’, which include market surveys, search of commercial partners and product promotion; ‘employment, training and innovation’, which include instruments such as incubators of firms, direct incentives to innovation, programs of technology transfer, and all the efforts realized to increase the quality of human resources; and, finally, ‘stimuli to entrepreneurial spirit and culture’, which include educational activities for the weakest sectors and the most sensitive to unemployment, such as women, young people and unemployed (Commission Europeenne, 2002). 14 In the past ten years, Brazil has always attracted more than 30% of total FDI in Latin America (up to a total of 29 000 million dollars in 1998); Mexico has been increasing and reaching the same levels of Brazil (30% in 2002 and 2003); Costa Rica is attracting much less (about 500 million dollars per year), but it is also a very small economy compared with the previous countries; Argentina was able to attract up to 22 000 million dollars in 1999, before falling to 1500 in 2002 due to the deep financial crisis that the country is going through (CEPAL, 2004: 162).

2 The regional innovation system in Emilia-Romagna, Italy 1 The author would like to thank Professor Patrizio Bianchi for his great support over the contents and results of this chapter; in particular, sections 1, 3 and 7. 2 Close to ‘the university system’, Emilia-Romagna can also count on a powerful ‘structured system of research in the public sector’ (ENEA, CNR) including up to 6000 researchers. 3 Agency for technological development in Emilia Romagna. 4 Regional bill of law, Promozione del sistema regionale delle attività di ricerca industriale, innovazione e trasferimento tecnologico, Relazione di Accompagnamento, Emilia-Romagna Region. 5 This category included graduates, post-graduates and researchers that abandon the university activities to work full-time in companies.

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4 The start-up process of knowledge-based companies in Latin America 1 Brazil has 168, Mexico 213, Peru 229, Chile 370, El Salvador 19, Italy 1322, Spain 1562, Singapore 2182, Korea 2139 and Japan 4960. 2 Test-z has been applied to verify significant statistic differences. 3 This chapter is based on a conceptual framework and a database developed under a research project coordinated by the Inter-American Development Bank and Fundes and implemented by the National University of General Sarmiento and the Development Bank of Japan (Kantis et al., 2002, 2004). 4 Brazil and also Mexico lead in the bigger role that universities play in the access to information and technology (although this is smaller compared with the role played by suppliers/clients). 5 This process has influenced not only the creation of new business opportunities, but also the bankruptcy of a large proportion of small companies. Unfortunately, there is no empiric evidence to measure the global outcome of this dynamic. 6 The information available (e.g. number of contacts and interactions) does not show a smaller networking activity of businessmen compared with the conventional sector. 7 More details about support business policies are presented in Kantis, et al., 2004.

5 Business support services: a conceptual framework and some interesting practices 1 This chapter summarizes some of the findings that are more extensively discussed in Bellini, 2003. 2 Although it may be confusing in everyday English, the term ‘real services’ has already been introduced in the international economic literature (Bianchi and Bellini, 1991; Brusco, 1992; Glasmeier, 1999; Bellini, 2000). In Englishlanguage literature and policy documents other expressions, such as ‘external assistance’ or ‘external advice’, are frequently found. In the US business support services are mostly referred to as industrial or manufacturing ‘extension services’. The term ‘extension’ was borrowed from the previous experience in the agricultural sector (and from the Agricultural Cooperative Extension Service, started in 1914). Within international organizations dealing with developing countries one can also find the expression ‘business development services’. 3 In October 2001 a ‘workshop agreement’ was signed by eight support service agencies within the European Committee for Standardization – CEN (CEN, 2001). ‘Recommended specifications for business support services to small companies in Europe’ were presented by the DG Enterprises in October 2004. 4 E.g. the databases of support measures and good practices set up by the European Commission – Enterprise Directorate and the database on support services of the Austrian Institute for Small Business Research (Österreichisches Institut für Gewerbe- und Handelsforschung, IfGH) (Sheikh et al., 2002).

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5 One example is the European Committee for Business Support Services (CESCE). CESCE is an association of organizations involved with the provision of business support to SMEs. CESCE has been active as a network since 1969. Specialized networks exist with reference to some support services, like the European Business Angels Network. 6 A systematic discussion of the market failure argument is provided by FSMED, 2002. Several authors have stressed specific aspects of it, e.g.: Brusco, 1992; Feller, 1997; Bellini and De Laurentis, 2000. 7 The MEP website states that ‘MEP is committed to being industry-driven and market-defined’. 8 The legal status of some actors may vary depending on the country. For example, Chambers of Commerce are private organizations in some countries, while they have public-law status in others. 9 Among the most noticeable: the Economic Development Institute of Georgia Tech, which has been active for 40 years and is now part of the MEP network, with an outstanding record of activities, also compared with other US universities (Tornatzky et al., 2002); the Steinbeis Foundation, whose transfer centers are mostly located in research facilities and universities; the Technology Development Group (Technologie Entwicklungsgruppe) of the Fraunhofer-Gesellschaft, that conveys into industrial development projects the know-how of 56 research establishments throughout Germany. 10 In the case of MEP, an analysis of 8443 technical assistance projects of 8 h or more with companies completed by 59 MEP centers in 1996 shows that outside service providers were involved in 24% of projects (Shapira, 2001).

6 Entrepreneurship, small firms and self-employment 1 An earlier version of this chapter was presented at the Workshop on the Demography of Firms and Industries, University of Barcelona, 2001. The present version was presented at the Workshop on the Post-Entry Performance of Firms, Bologna, 2002. We acknowledge support from the Ministerio de Ciencia y Tecnología, grant SEC0882-C02-01. 2 Entrepreneurship is the center of Schumpeter’s theory and innovation and growth evolutionist theory.

7 Competitiveness based on low production costs or on high specialization and productivity: the case of SMEs in Costa Rica 1 Costa Rican Institute for Social Insurance (CCSS) is a public institution that administrates insurances for concept of invality, old age and death, sickness and maternity, and non contributive pension regimes. Workers and their bosses operating in the formal sector obligatorily participate in these health regimes, and this is why CCSS has information related to the businesses and employment of the formal sector of the economy. 2 A simple average is used for this purpose: Combinated Index = (Qualification of the Personnel Index + Technological Development Index)/2. 3 This survey was coordinated by Luis Zárate, researcher of the Institute for Research in Economic Sciences of the University of Costa Rica.

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4 The formal sector represents the SMEs that participate in the Costa Rican Social Insurance regimes. The informal sector does not appear in these registries and neither as a contributor for national taxation.

8 Trust and social capital in glo-cal networks 1 In fact, the ‘shadow’ of the last game, where players again have an incentive not to cooperate, leads the game back to a non-cooperative solution. For a more detailed discussion on the cooperator’s dilemma, see Rothstein (2003). 2 Dasgputa (1988) also agrees that the mere presence of a realistic penalty acts as a deterrent against defaulting and as an incentive prompting the trustee to remain faithful to his word. 3 Contractual trust is associated with the expectation of a certain behaviour prompted by a formal/informal, implicit/explicit agreement (see Sako, 1992, 1998). 4 The concept of systemic trust introduced in this contribution is different from institutional trust as referred to by Luhmann (1979). The latter refers to trust or, to be more precise, confidence that each individual invests in major institutions such as the government, the police, the church and the law. This confidence generates a sense of overall security and allows society to function. At the same time, however, it also leaves individuals helpless when it comes to regulating or controlling a trust relationship. 5 This happens even when the cooperative relationship has a temporal dimension as in the case of repeated games. 6 Putman (1993) distinguishes horizontal networks from vertical networks. He argues that the latter are incapable of generating trust and cooperation because they are characterized by relational asymmetry and dependence. 7 According to Portes (1998) social capital can also be considered as a resource shared by a bounded solidarity community in which participants mutually recognize each other and are able to discriminate between trust and non-trust relations. 8 Systemic trust can, for example, be found in industrial districts. For more details see Dei Ottati (1994 and 1995). 9 See Gambetta (1988) on the social cost of social liability in cartels or criminal organizations. 10 For a definition of inter-organizational trust, see Sydow (1998). 11 The conceptualization of strong and weak ties has been reviewed by Putnam (2000) in his definition of bonding and bridging relationships, where the former is common to individuals belonging to the same social group or clan, whereas the latter is applied to relations between individuals who pertain to different groups or clans.

9 Local and global linkages of SMEs in local production systems in Brazil 1 The research on which this chapter is based was assisted by a grant from CNPq. 2 Firms appropriate these economies asymmetrically according to their ability to control the system of linkages.

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3 There are important exceptions, of course. For example, a small firm that adapts for the Brazilian market new models of footwear launched in the international market, especially by the Italian industry, produces a small volume of striking men’s shoes, some in exotic colors, for a highly demanding clientele that values quality and design. 4 Entrepreneurs interviewed by the authors on several occasions have expressed profound skepticism about the chances of succeeding in any kind of joint action with other SMEs. 5 Brazilian exports to the US still account for about 70% of the total, according to Abicalçados, the national footwear industry association. In Europe, however, the penetration of Brazilian footwear has never been very significant. 6 This impression was confirmed by several local entrepreneurs, who said average prices of products for sale in the domestic market are significantly higher than prices of exports. 7 There is much discussion in Brazil on the possibility of replicating the CEMAD/Votuporanga experience in other furniture production clusters elsewhere. At a seminar held in 2001 at Macapá, state capital of Amapá, representatives of various furniture production clusters in the North region (Amazonia) informally discussed this point on more than one occasion.

10 Industrial cluster trajectories and opportunities for endogenous upgrading in developing countries 1 This chapter is an updated and expanded version of a chapter called ‘Cluster trajectories and the likelihood of endogenous upgrading’, in: M.P. van Dijk and H. Sandee (eds) 2002 ‘Innovation and Small Enterprises in the Third World’ Cheltenham, Edward Elgar, pp. 48–65. It builds on a paper presented at a European Management and Organization in Transition (EMOT) workshop, at the ISTUD, in Stresa, Italy, 11–14 September 1997 and an EADI workshop on the importance of innovation for small enterprises development in the Third World at the Institute of Social Studies (ISS), The Hague, 18–19 September 1998. I thank participants in these workshops for their constructive comments. 2 In turn, rural clusters tend to be concentrated in traditional sectors, often with artisanal roots. 3 From a discussion with D. McCormick, W. Mitullah and M. Kinyanjui at the IDS, Sussex University, April 1997. 4 The fourth type of industrial district identified by Markusen, the State Anchored District, is not dealt with in this paper. However, it could be a useful metaphor in a discussion on the role of the state in trying to create industrial districts from scratch. Among researchers in the area of small enterprise development in developing countries, however there is a consensus that this is impossible (Humphrey and Schmitz, 1996). 5 On Italy see, e.g., Dei Ottati, 1996: Lazerson and Lorenzoni, 1996; Albino et al., 1996; Rabellotti 2004; for an analogy with one of the oldest industrial districts, Rochdale (Manchester), see Penn, 1994. 6 Most of these case studies are brought together in a special issue of World Development, September 1999.

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11 A sectoral approach to policies for clusters and value chains in Latin America 1 This chapter draws on the empirical findings of a project on ‘Clusters, Value Chains and Competitiveness’, carried out for AGORA’ 2000, Italy on behalf of the Micro and SME Division, Department of Sustainable Development (SDS/MSM) of the Inter-American Development Bank (IDB), and directed by Carlo Pietrobelli and Roberta Rabellotti (see Pietrobelli and Rabellotti, 2005, and 2007). The authors wish to thank the Italian Government Trust Fund for financing the project. Collaboration and comments from Alessandro Bolondi, Carlo Manfredi (AGORA’ 2000), Juan José Llisterri, Claudio Cortellese and Pablo Angelelli (IDB), Elisa Giuliani, Alessia Amighini, José Eduardo Cassiolato, Helena Lastres, Arlindo Villaschi, Raquel S. Gomes, Clemente Ruiz Duran, Eduardo Zepeda Miramontes, Claudio E. Maggi Campos, Ner Artola, Marco Dini, Gianfranco Viesti, Domenico Cersosimo, Manuel Albaladejo, Carlos Guaipatin, Sanjaya Lall, Jorg Meyer-Stamer, Mario Davide Parrilli, Rajah Rasiah, Andrés Rodríguez-Clare, Fréderic Richard, Giovanni Stumpo, Morris Teubal, are gratefully acknowledged. Preliminary drafts were presented at seminars at IDB in Washington DC and Buenos Aires, UNCTAD, Geneva, IberPYME in Guadalajara, Mexico, CEPAL-UAM Atzcapozalco in Mexico City, Mexico, University of Modena, Italy, EADI at University of Piemonte Orientale, Novara, and Universidade Federal do Espirito Santo, Brazil. 2 For a list of all cases see Pietrobelli and Rabellotti (2005). 3 The indexes of external economies and joint action are computed by summing up the figures obtained in each component. Then, the index of collective efficiency is the simple average of the two. 4 Whenever the evidence was derived from the literature, with the collaboration of our team of experts, we carefully tried to minimize the occurrence of bias and misinterpretations complementing and cross-referencing information in all possible ways, also testing it with interviews to key informants and local experts. Nevertheless, as with any study of this kind there may be potential problems on the accuracy of the results, which calls for cautious interpretations. 5 Further details on this ‘menu of actions’ may be found in Pietrobelli and Rabellotti, 2004. 6 José Cassiolato, personal communication, 7 March 2003. 7 See for example the methodology used for the present study, and the PACA – Participatory Appraisal of Competitive Advantage – http://www.pacaonline.de/.

Index agglomeration centrifugal forces 64 geographical 36 industrial 63 market potential 64 synergies 64 see also clustering agglomeration economies clustering 58, 65 competitiveness 27, 181 networking 23 Aguilar, Justo xi, 23, 138–51 Angelelli, Pablo xi, 20, 71–91, 140 Aranguren, Mari Jose xi, 22, 117–37, 237 Audretsch, David xi, 22, 117–37, 237

manufacturing 218 supply chain coordination 176–81, 184–6 bridging firms 169 business development services accreditation 104 business outcomes 107–8 CATAS network 99–100, 111, 112 clustering 101 conceptual framework 99–102 customers 111–12 developing countries 97 European Union (EU) 98 evaluation 107–12 external linkages 99 industry outcomes 108 internal linkages 99 Italy 22, 95–116 learning induced 96 market distortion 104 market failure 101–2 market response 109–12 operational outcomes 197 outcomes 107–9 positive externalities of consumption 96 private/public providers 102–3 producers/brokers 105–7, 237 providers 102–7 public expenditure 97 real services 95–7 relevance 99–101 socio-economic outcomes 108 state of the art 97–9 sticky knowledge resources 96 strengths/weaknesses 103–4 support service policies 97–9 technology transfer 102 territorialization 106 United Kingdom 98, 104–7, 109 United States 105, 110 universities 102–3

Baumol, W.J. 123, 124 Bellini, Nicola xi, 22, 95–116, 237 Bianchi, Patrizio xi, 233–9 biotechnology clustering 58, 63–6 comparative size of firms 58, 59–63 entrepreneurship 60 industrial policy 58 linkages 61 outsourcing 60–2 pharmaceutical companies 61–2 scientific discovery/platform 59 spin-off companies 59–60 sub-contractors 62 United States 20, 57–70 see also high technology development Bourdieu, P. 163 Brazil clustering 25 collective action 186–9 footwear industry 181–6 furniture industry 186–9 linkages 175–92 local production systems 175–92 247

248

Index

Callejon, Maria xi, 22, 117–37, 237 CATAS network 99–100, 111, 112 Central and Eastern European Countries, labour costs 37 China 234 Clinical Research Organizations (CROs) 62 clustering agglomeration economies 58, 65 biotechnology 58, 63–6 Brazil 25 business development services 101 collective efficiency (CE) 212, 215–17, 219 commodity chains 202 competitiveness 25 complex product systems (COPS) 218–19, 225–6 critical mass 23 developing countries 25–6, 193–208 development time 215 dynamics 12 Emilian model 35 empirical results 212–20 external economies (EE) 212, 216 global value chains 26, 209–29 high technology development 83–6 hub-and-spoke 25, 178, 180, 199, 201, 203–4, 205 inclusive growth 24 industrial territories 13 joint action (JA) 212, 216 Latin America 26, 73, 209–29 macroeconomic framework 219–20 manufacturing 218, 220–1 natural resources 63–4, 218, 222–5 physical proximity 64–5 satellite districts 26, 201–3 sectors 218–19 software suppliers 226–7 strategic relations 65 stylized trajectories 197–204, 238 survival clusters 195–7 transaction costs 64 trust 25, 157–63 typologies 35 vertical relationships 215–16 vertical/horizontal integration 65 virtual clusters 65

Coleman, J.S. 163–4 collective action Brazil 186–9 Italy 66 local production systems 183 social capital 165 competitiveness agglomeration economies 27, 181 clustering 25 Costa Rica 147 developing countries 4, 140 functional upgrading 210 globalization 36 international pressure 142 intersectional upgrading 210 local accumulation 155 local production systems 155, 179 market economy 6–7 neoclassical/neoliberal approach 6 process upgrading 209–10 product upgrading 210 production chain 21 size-rigidity 60 social capital 25, 166–7 complex product systems (COPS) 218–19, 225–6 corruption 5, 6 Costa Rica agriculture 146 competitiveness 147 economic recession (1980s) 138 employment 146 findings 147–50 foreign direct investment (FDI) 23 Homogeneity Analysis (HOMALS) 139, 143, 148 information 144–5 manufacturing 146 methodology 143–4 micro enterprises 145, 146 QUAL-TEC 144, 148 results 145–7 small and medium enterprises (SMEs) 23, 138–51 statistical analysis 143–4 structural adjustment 138 tertiary sector 145–6 traditional enterprises 142–3 Cowling, K. 12, 19

Index De Propris, Lisa xi, 25, 155–74, 237 developing countries brain drain 57 business development services 97 clusters 25–6, 193–208 competitiveness 4, 140 family businesses 140 industrial districts 97 multinational companies 4 outsourcing 57, 66 resource scarcity 15 small and medium enterprises (SMEs) xiii, 4, 21, 140 traditional sectors 21, 140 Di Tommaso, Marco R. xi, 20, 57–70, 141, 149, 236 diseconomies of scale 20, 60 division of labour geographical aggregation 23 productivity 22 Economic Commission for Latin America and the Caribbean (ECLAC) 8 economies of scale 62, 141 Elizondo, Maikol xi, 23, 138–51 Emilia-Romagna see Italy employment Costa Rica 146 entrepreneurship background 75 self-employment 118, 129–30 subsistence production 139 entrepreneurship biotechnology 60 business opportunities 121–2 change 121 commerciality 80 dynamism 117 economic growth 123, 124 educational background 74 employment background 75 entrepreneurial economy 120 gazelles 127 innovation 124, 126–7, 142 institutional arrangements 125 Italy 40, 48 Latin America 13, 20–1, 73–5, 76–7 measures of activity 125–8

249

motivation 77 nature of entrepreneurship 121–3 necessity 125 opportunity 125 personal networks 79–80 self-employment 118, 129–30 Spain 22, 117–37 United States 123 university research 67 European Charter for Small Enterprises 98 European Economic Area (EEA) 14 European Union (EU) business development services 98 firms without employees 128 labour productivity 14 research and development (R&D) 44–6 small and medium enterprises (SMEs) 13–16, 119, 124 structural policies 22 subsidiarity 14 technology production gap 40 export markets globalization 135–6 small and medium enterprises (SMEs) 141 Fordist companies 3 foreign debt crisis 5 foreign direct investment (FDI) Costa Rica 23 Latin America 19 Fua, Giorgio 235 Fukuyama, F. 162, 165 Furtado, Jo˜ao xi, 25, 175–92, 237 Garcia, Renato xi, 25, 175–92, 237 Gentzoglanis, A. 141, 142 global commodity chains 178, 202 global value chains clustering 26, 209–29 Latin America 12, 13, 26 local development 24, 25 globalization competitiveness 36 export markets 135–6

250

Index

Granovetter, M. 169, 170 gross domestic product (GDP) formation per sector 39 Hayek, Friedrich August von 121–2 high technology development biotechnology see biotechnology clustering 83–6 diseconomies of scale 20, 60 economies of scale 62 expertise 67 firm size 59–63 increasing complexity 60 industrialized economies 57 intangible assets 61 life-cycle model 62–3 mortality 62 outsourcing 60–2, 66 permits 67 policy options 66–7 promotion 35–91 risk 62–6 small and medium enterprises (SMEs) 18–21 spillovers 58 start-up companies 63, 66–7 venture capital 63, 66 volatility 62 Hobbes, Thomas 157 Homogeneity Analysis (HOMALS) 139, 143, 148 hub-and-spoke 25, 178, 180, 199, 201, 203–4, 205 import substitution industrialization (ISI) 5, 6 industrial development complementarity 17–18 tripartite framework xiii–xiv, 17–18 industrial districts developing countries 97 Italy 36–7, 140, 193–4, 198–201 marshallian industrial districts 25, 26 industrial policy biotechnology 58 import substitution industrialization (ISI) 5, 6 Italy 55

industrialized economies, high technology development 57 informal economy developing countries 140 Latin America 9 information technology (IT), outsourcing 61 innovation entrepreneurship 124, 126–7, 142 Italy 20, 35–56 Latin America 18–20, 71 national innovation systems 45, 71 promotion 139 size 142 value generation 140–3 intangible assets high technology development 61 start-up companies 83 Inter-American Development Bank (IADB) 12–13 International Investment Corporation (IIC) 12 International Monetary Fund (IMF) 5 intrapreneurships 127 Italy business development centres 35–6 business development services 22, 95–116 chemical industries 36, 38 civil society 35, 38 collective action 66 Emilia-Romagna 20, 35–56, 234–6 entrepreneurship 40, 48 evolution of Emilian model 35–7 geographical agglomeration 36 groups of companies 38 industrial districts 36–7, 140, 193–4, 198–201 industrial policy 55 industry trends 38–44 innovation 20, 35–56 knowledge-based industries 48–9 low-tech/traditional sectors 38 multinational companies 35 networks 38–9, 40, 49, 50 regional plans 37 research and development (R&D) 40, 42–4, 55

Index research network/production network 49, 50 research system 46–7 research-based companies 49, 51–4 small and medium enterprises (SMEs) 14 social capital 35, 38 spin-off companies 52–3, 55, 237 Spinner system 49, 51–4, 236 sub-contractors 38, 39 technology transfer 53–4 university research 37, 46–7, 52–3, 54–5, 236 value added 40, 41 Japan, global sub-contractors 140 Kantis, Hugo xi, 20, 71–91, 140, 236 Knorringa, Peter xi, 25–6, 193–208, 238 knowledge-based industries geographic limitations removed 65 Italy 48–9 Latin America 71–91 role models 76 start-up companies 71–91 see also high technology development Korea, traditional sub-contractors 140 labour productivity European Union (EU) 14 Latin America 9 traditional SMEs 21, 140 Latin America average annual sales 73 brain drain 18 capital substitution 9 clustering 26, 73, 209–29 double problem of newness responsibility 73 dynamic companies 71–2 entrepreneurship 13, 20–1, 73–5, 76–7 foreign direct investment (FDI) 19 global value chains 12, 13, 26, 209–29 human capital 19

251

informal economy 9 innovation 18–20, 71 investment 73 knowledge-based industries 71–91 labour productivity 9 liberalization 8–9 new approach 12–13 productivity gaps 71 profile of firms 72–5 research and development (R&D) 71 sectoral approach 209–29 SME performance 9–11 start-up companies 71–91 structuralism 7–9 universities 74, 77–9, 81 liberalization comparative advantage 5, 6 Latin America 8–9 linkages biotechnology 61 Brazil 175–92 business development services 99 local production systems Brazil 175–92 collective action 183 competitiveness 155, 179 hub-and-spoke 178, 180 networks 156 organization asymmetries 182–3 policy suggestions 189–91 quasi-hierarchy 181–6 supply chain coordination 176–81, 184–6 managed economy 120–1 manufacturing Brazil 218 clustering 218, 220–1 Costa Rica 146 upgrading 220–1 market failure business development services 101–2 local/regional responses 101–2 neostructuralism 8 Markusen, A. 25, 32, 178, 180, 197 marshallian industrial districts 25, 26

252

Index

micro enterprises Costa Rica 145, 146 public policy 11 rural subsistence 7 multinational companies developing countries 4 global value chains 25 Italy 35 low value-added activities 19

productivity division of labour 22 growth 21–3, 95–151 low-road/high-road 4, 17, 209 see also labour productivity Putnam, R.D. 163, 164–5, 167

national champions 5, 14 natural resources clustering 63–4, 218, 222–5 Latin America 71 neoclassical/neoliberal approach 5–7 neostructuralist approach 7–11 networks access to resources 81–3 clusters see clustering external economies 24 glo-cal networks 144–74 Italy 38–9, 40, 49, 50 personal networks 79–80 relationship building 169–70 relationship sustainability 170 research network/production network 49, 50 SME development 23–6, 155–229 start-up companies 79–83 typology 178 North Africa, Mise-à-niveau (renewal) 22

Rabellotti, Roberta xii, 26, 209–29, 238 Ramaciotti, Laura xii, 20, 35–56, 234–6 research and development (R&D) European Union (EU) 44–6 Italy 40, 42–4, 55 Latin America 71 national innovation systems 45, 71 universities see university research risk, high technology development 62–6

outsourcing developing countries 57, 66 high technology development 60–2, 66 information technology (IT) 61 Parrilli, Mario Davide xii–xiv, 3–31, 179, 192, 234 Pavitt’s industrial taxonomy 26 Pietroblelli, Carlo xii, 26, 209–29, 238 prisoner’s dilemma 157, 158, 161, 165 production systems LPS see local production systems typology 177–8

quality upgrading, standardization and certification 21

satellite districts 26, 201–3 Scandanavia, State-Providence 14 Schumpeter, J.A. 120, 121, 122, 124, 127, 141 Schweitzer, Stuart O. xii, 20, 57–70, 141, 149, 236 sectors clustering 218–19 Costa Rica 145–6 developing countries 21, 140 GDP formation 39 Italy 38 Latin America 209–29 services 85–6, 145–6 start-up companies 84–6 traditional sectors 21, 38, 84, 86, 140 upgrading 220–7 self-employment 118, 129–30 Singapore, medium-sized niche enterprises 140 size biotechnology firms 58, 59–63 businesses/technology 141–3 diseconomies of scale 20, 60

Index economies of scale 62, 141 firm demography by size 129, 130 firms without employees 128 innovation 142 medium-sized niche enterprises 140 size-rigidity 60 small and medium enterprises (SMEs) approaches to development 5–13, 17–26 comparative advantage 5 Costa Rica 23, 138–51 critical mass 13, 23 developing countries xiii, 4, 21, 140 empirical analysis 128–33 employment 139 entrepreneurs see entrepreneurship European Union (EU) 13–16, 119, 124 evolution 131, 132 export markets 141 firm demography by size 129, 130 firms without employees 128 geographical aggregation 23 global context 3–5 high technology development 18–21 industrial change 118–21 information costs 8 Italy 14 neoclassical/neoliberal approach 5–7 neostructuralist approach 7–11 net entry rates 131 old/new trends 13–16 political/social significance 4 productivity growth 21–3 size 141–3 Spain 128–33 strategic development lines 17–18 survival rates 130 systemic approach 3–31 technology 141–3 traditional/non-traditional 140–3 typology 140 United States 119–20 social capital collective action 165 competitiveness 25, 166–7

253

definition 163–4 economic approach 164 economic relationships 163–6 Italy 35, 38 relational capital 163, 164 spontaneous sociality 165 trust 166–70 Spain entrepreneurship 22, 117–37 small and medium enterprises (SMEs) 128–33 spin-off companies biotechnology 59–60 bureaucracy 67 Italy 52–3, 55, 237 start-up companies 66 Spinner system 49, 51–4, 236 start-up companies access to resources 81–3 acquisition of vocation and skills 77–9 business angels 84 business opportunity/enterprise idea 79–80 conception phase 76–80 conventional sector 84, 86 domestic markets 85 early development phase 84–8 firms and markets 85–6 high technology development 63, 66–7 intangible assets 83 knowledge-based industries 71–91 Latin America 71–91 main problems 87 management 86–8 networks 79–83 policy implications 88–90 project design 80 reasons to create new company 76–7 restrictions/key factors 75–88 services sector 85–6 sources of finance 83–4 sources of support 87 spin-off companies 66 start-up phase 80–4 venture capital 63, 66 Storper and Harrison 176, 177

254

Index

sub-contractors biotechnology 62 global sub-contractors 140 Italy 38, 39 traditional sub-contractors 140 Sugden, Roger xii, 12, 19 Suzigan, Wilson xii, 25, 175–92, 237 technology transfer business development services 102 Italy 53–4 trickle-down effects 11, 12 trust calculative 25, 157–61, 166 goodwill trust 169 prisoner’s dilemma 157, 158, 161, 165 relational memory 168, 169 social capital 166–70 systemic 25, 161–3, 166, 167–8, 169 transferability 168–9 United Kingdom business development services 98, 104–7, 109 Business Link 98, 104–5, 106, 109 Personal Business Adviser services (PBAs) 106–7 Small Business Service 104 United States biotechnology 20, 57–70 business development services 105, 110 entrepreneurship 123 Food and Drug Administration (FDA) 60 Mid-America Manufacturing Technology Center (MAMTC) 105, 110

small and medium enterprises (SMEs) 119–20 universities business development services 102–3 Latin America 74, 77–9, 81 university research bureaucracy 67 entrepreneurship 67 Italy 37, 46–7, 52–3, 54–5, 236 policy options 66 spin-offs see spin-off companies upgrading collective efficiency (CE) 215–17 competitiveness 209–10 manufacturing 220–1 sectoral approach 220–7 value chain strategic governance 217 value chains 194–5, 220–7 value chains global see global value chains sectoral approach 220–7 strategic governance 217 upgrading 194–5, 217, 220–7 venture capital, high technology development 63, 66 Washington Consensus 234 World Bank import substitution industrialization (ISI) policies 5 market economy 6–7 structural adjustment 138 World Trade Organization (WTO) 3, 234

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