High-technology Clusters, Networking and Collective Learning in Europe

David Keeble, Frank Wilkinson, David Keeble, Frank Wilkinson

• Publisher: Routledge
• Year: 2017
• ISBN:
  9781351744515
• Edition: 1
• Topic: Social Sciences
• Subtopic: Sociology
• Index: Social Sciences

This title was first published in 2000: This text presents a study of collective learning, networking and high-technology regions in Europe. It first provides an overview of the subject area, then goes on to discuss topics such as the role of inter-SME networking and collective learning processes in European high-technology milieux.

1 High-Technology SMEs, Regional Clustering and Collective Learning: An Overview

DAVID KEEBLE AND FRANK WILKINSON

1.1 Introduction, Aims and Objectives

This book brings together and synthesises findings from original research by a group of leading European researchers into the recent evolution and dynamic processes underpinning the growth of key European regional clusters of technology-based small and medium-sized enterprises (SMEs). The growth of these regional clusters of technology-intensive firms, as exemplified in such regions as Cambridge, Oxford, Grenoble, Sophia-Antipolis, Munich and Goteborg, represents one of the most fascinating and arguably significant examples of the emergence since the 1970s of what have been termed ‘new industrial spaces’ (Scott, 1988; Storper, 1993, 1995) and ‘innovative milieux’ (Aydalot, 1986; Aydalot and Keeble, 1988a; Camagni, 1991a; Ratti et. al., 1997) in both previously non-industrial areas and through the restructuring of existing metropolitan and industrial regions. While large firms are often involved in the growth of these regional high-technology clusters, all are characterised by substantial numbers of small, new and innovative enterprises engaged in technologically-advanced manufacturing and service activities. Notwithstanding the impact of the early-1990s European-wide recession, most of these clusters appear to have been growing rapidly in the 1990s, through processes such as new firm spin-off and endogenous expansion: and many observers have suggested that they are characterised by new forms of production organisation, based on high levels of inter-firm collaboration and cooperation, strong links with local knowledge centres such as universities, and the development of a regionally-embedded capacity for ‘collective learning’ and technology development linked to the growing local concentration of scientific, technological and managerial expertise.

The growth of key examples of these regional clusters, and the processes involved, have been studied in detail by members of the TSER European research network on ‘Networks, Collective Learning and RTD (Research and Technology Development) in Regionally-Clustered High-Technology Small and Medium-Sized Enterprises’. Meetings of this network have been funded by Directorate-General XII for Science, Research and Development of the European Commission, under the Targeted Socio-Economic Research (TSER) Initiative of the Fourth Framework Programme, whose financial support is gratefully acknowledged. The regions studied and the researchers involved are: Cambridge (David Keeble, Clive Lawson, Barry Moore, Frank Wilkinson and Elisabeth Gamsey), Oxford (Helen Lawton Smith), Grenoble (Michel de Bernardy), Sophia-Antipolis (Christian Longhi), Munich (Rolf Sternberg and Christine Tamásy), the Dutch Randstad (Egbert Wever), Pisa, Piacenza and NE Milano (Roberta Capello and Roberto Camagni), Goteborg (Asa Lindholm Dahlstrand), Helsinki (Ilkka Kauranen and Erkko Autio), and Barcelona (Pere Escorsa, Ramon Maspons and Jaume Valls), with theoretical contributions from Edward Lorenz. The network was coordinated by David Keeble and Frank Wilkinson of the ESRC Centre for Business Research, University of Cambridge, with Clive Lawson as network rapporteur. While not all network members have contributed to this book, the chapters which follow are greatly indebted to the collective endeavours and debates of the whole network.¹

The aim of this book is to provide a thematic overview of key findings of the network, rather than to present a series of individual regional case studies.² Each chapter investigates a different and specific theme identified from both the theoretical and empirical literature as being important in understanding the processes and dynamics of regional clustering and growth of high-technology SMEs, and attempts to draw general conclusions from comparison of findings across a range of the network’s case study regions. The book thus begins with an introductory discussion of key contextual issues and definitions (chapter 1, Keeble and Wilkinson), followed by an examination of the nature of recent European high-technology region evolutionary trajectories and the forces driving these trajectories (chapter 2, Longhi and Keeble). Chapter 3 (Tamásy and Sternberg) outlines the nature and reviews the impact of different regional institutional and policy contexts, while chapter 4 (Lawton Smith and de Bernardy) examines the role of local universities and public research institutes in shaping the recent growth of European regional clusters of technology-based SMEs. The issue of the nature and importance of inter-SME collaborative links and networks within these regions is addressed in chapter 5 (Camagni and Capello), and that of the impact on regional clusters of large firms, especially through their activities in spinning-off and acquiring regional technology-based SMEs, is discussed in chapter 6 (Lindholm Dahlstrand). Chapter 7 (Lawson) provides a theoretical perspective on the concept of ‘regional collective learning’, which is increasingly being argued by commentators as being of central importance for understanding how successful regional SME clusters maintain and enhance their innovativeness in a technologically-dynamic world: while chapter 8 (Keeble) assesses the extent and importance of specific regional collective learning processes identified by the network’s research as currently operating in European high-technology regions. Finally, chapter 9 (Wilkinson and Moore) considers some of the main policy implications and conclusions for promoting and supporting Europe’s technology-based regional SME clusters arising from the network’s findings.

1.2 High-Technology SMEs: Conceptualisation and Definition

The term ‘high-technology’ is widely – and loosely – used as a catch-all phrase usually denoting industries producing technologically-advanced, sophisticated and changing products. Its uncritical usage has in the past led researchers such as McArthur (1990) to argue that the concept of ‘high-technology’ is too ‘chaotic’ to justify continued use. McArthur’s preferred alternative two-fold categorisation of technologically-based activities into those involving ‘widely diffusing’ and ‘newly emerging’ technologies has not however itself been adopted subsequently, while the academic literature continues to find the ‘high-technology’ categorisation useful (Anselin et al., 1997; Westhead and Storey, 1997; Bolland and Hofer, 1998; Gamsey, 1998; Pfirrman, 1998; Oakey and Mukhtar, 1999). In this book, the terms ‘high-technology’, ‘technology-intensive’ and ‘technology-based’ are used broadly and interchangeably to refer to firms and industries whose products or services embody new, innovative and advanced technologies developed by the application of scientific and technological expertise. Such firms almost invariably regard such expertise and resultant technological leadership as the firm’s leading competitive advantage, and are usually identified in practice by high R&D-intensity (high levels of research and development expenditure and/or employment relative to turnover or total workforce) (Aydalot and Keeble, 1988b; Keeble, 1992).

Butchart (1987) used R&D-intensity indicators for UK sectors to identify a set of high-technology industries which can be contrasted with medium-or low-technology industries. Butchart’s list of high-technology sectors (Table 1.1), though now somewhat dated, highlights the important fact that some of the most rapidly-growing technology-based sectors are service industries, such as computer software and services, rather than manufacturing industries. Computer services and software in fact recorded the largest volume of growth in numbers of businesses – overwhelmingly small businesses – of all 4-digit sectors of the British economy between 1985 and 1990 (Keeble et al., 1992), while employment in this high-technology service sector grew by no less than 186 per cent (+102 thousand jobs) between 1981 and 1994 (Keeble and Oakey, 1995). This growth has continued in the 1990s (see chapter 2, section 2.7).

Table 1.1 High-technology industries in the United Kingdom

Standard Industrial Classification (1980) Activity Heading and Industry Description

2514	Synthetic resins and plastics materials
2515	Synthetic rubber
2570	Pharmaceutical products
3301	Office machinery
3302	Electronic data processing equipment
3420	Basic electrical equipment
3441	Telegraph and telephone apparatus and equipment
3442	Electrical instruments and control systems
3443	Radio and electronic capital goods
3444	Components other than active components mainly for electronic equipment
3453	Active components and electronic sub-assemblies
3640	Aerospace equipment manufacturing and repairing
3710	Measuring, checking and precision instruments and apparatus
3720	Medical and surgical equipment and orthopaedic appliances
3732	Optical precision instruments
3733	Photographic and cinematographic equipment
7902	Telecommunications services
8394	Computing services
9400	Research and development services

Source: Butchart 1987.

This said, it is clear that many research-based firms producing technology-intensive goods and services are to be found in sectors other than those listed in Table 1.1, while conversely, some firms in these sectors are neither research-intensive nor technologically-dynamic. Indeed, recent Cambridge research by Hughes (1998), applying a firm-level approach to high-technology definition (R&D expenditure relative to sales) to data from a large national stratified random sample of British manufacturing and business service SMEs, has found that there are considerably more research-intensive firms outside these sectors (8.3 per cent of the sample) than within them (5.3 per cent). For these reasons, the approach taken to identifying technology-based SMEs in the network’s investigations of the various European clusters studied has been inclusive rather than exclusive, industry lists such as Butchart’s providing only a starting point for identifying local populations of high-technology SMEs which satisfy the broad definition given in the first paragraph above.

The best general definition of a small firm probably remains that of the UK Bolton Committee in its 1971 Report on Small Firms, namely that a small firm is an independent business which has only a relatively small share of its market and is managed by its owner(s) in a personalised way (Storey, 1994, p. 9). By extension, the European Commission has since 1996 defined small and medium-sized enterprises (SMEs) as having no more than 250 employees, an annual sales turnover of no more than 40 million ecus (1996), and no more than 25 per cent external ownership by larger firms. Again, the approach adopted in the network’s case studies has been to focus on SMEs which broadly fit this latter definition, while explicitly acknowledging that close links with large firms are often important to their competitive success and that successful high-technology SMEs are often prime targets for acquisition as subsidiaries by larger firms (see chapter 6).

1.3 Why are High-Technology SMEs Important?

The network’s focus on high-technology SMEs can be justified on various grounds. Though such firms account for only a small proportion of European SMEs,³ empirical research has clearly shown that they differ significantly from their more conventional counterparts, in ways which indicate a significantly more favourable and longer term economic impact upon regional and national economies and labour markets. Some of these differences are discussed in Keeble and Oakey (1995) and examined in detail in section 2.7 in relation to Hughes’ (1998) recent research. Suffice it to note here that high-technology SMEs are significantly more innovative, whether this is conceptualised as involving radical technological innovations (Tether, 1995, ch. 2) or simply the development or introduction of products which are new to the firm;⁴ they grow more rapidly in both employment and sales; they are much less vulnerable to closure and more likely to survive over any given period (Reid and Gamsey, 1996, 1997; Storey and Tether, 1998); they more frequently serve wider national and global markets (Keeble et al., 1998), thus generating significantly greater basic income for regional and national economies; they are much more likely to engage in collaborative and co-operative arrangements with other firms and organisations, thus exerting wider multiplier effects; and they employ much higher proportions of highly-skilled and high-income professional, scientific and managerial staff, thus enriching regional labour markets, boosting regional incomes and stimulating regional entrepreneurship via researchers spinning-off new firms from existing high-technology SMEs. Technology-based SMEs also appear to be playing a key role in the rapid growth of new and dynamic sectors of Europe’s economy, such as bio-technology and computer software and internet applications (Ernst and Young, 1999), and hence in structural economic change of a more fundamental kind.

1.4 The Growth of High-Technology SMEs in Europe: Nature and Causes

Although no comprehensive statistics are availab...