A dynamic model of Cyber-entrepreneurship and cluster formation: applications in the United States and in the Low Countries
Introduction
The geographical structure of high-technology industries is often very concentrated, with a multitude of linkages between core firms, their spin-offs and local subcontractors, top-class universities and research centres, and local/regional authorities. Probably the most inspirational and well-known clusters in the field of Information and Communication Technologies (ICT) are Silicon Valley, Route 128, Massachusetts and Silicon Alley (New York). All of them are based on the spontaneous cross-fertilisation between local universities and research laboratories and established high-technology companies through dominant practices such as subcontracting non-core business activities, partnering in research and product development, permanent intra- and entrepreneurship, and practising knowledge diffusion by job-hopping and the creation of spin-offs.
In everyday practice, politicians and civil servants, entrepreneurs and investors, development companies and knowledge centres concern themselves with the significance of information and communication technologies to local and regional developments. They are especially interested in the growth and development potential of local and regional economies and the possible positive effects on employment. Usually, Silicon Valley is seen as the example. The inspiration and imitation of Silicon Valley even makes people refer to its name, as for example in Silicon Alley (New York), Silicon Forest (Seattle), Silicon Hills (Austin-San Antonio), Silicon Dominion (Washington, DC), Silicon Valley (Fairfield, Iowa), Silicon Fen (Cambridge, GB), Shalom Valley, also called Silicon Wady (Israel), Silicon Plateau (Bangalore, India), Multimedia Super Corridor (Malaysia) or Silicon Valley on Ice (Oulu, Finland). Finally, we see the same kind of names in the Low Countries as well: Silicon Polder (referring to the Low Countries in general), Amsterdam Alley, Dommel Valley (Eindhoven, the Netherlands) and Flanders Language Valley (Ypres, Belgium), nowadays also known as S.AI.L Port Flanders. It is often unclear what is the unique character of the developments in some of these areas, in some cases it is more or less obscure (e.g. Multimedia Super Corridor, Malaysia). Other areas follow their own paths, such as for instance Oulu in Finland, Sophia Antipolis in Nice (France) and Hsinchu Science Park in Taiwan. Many analyses focus on the reasons why these areas are successful in building an innovative ICT-cluster within a certain region (e.g. Braczyk et al., 1999; Cooper, 2000; Druilhe and Garnsey, 2000).
In this paper, which deals with the potential of ICT-regions in the Netherlands and Flanders, we describe a cluster as the geographical concentration of mutually interdependent companies with vertical as well as horizontal, and with co-operative as well as competitive relational patterns, companies that in addition operate within the same branch or on the basis of the same basic technology (Jacobs and De Man, 1996). When clustering takes place within high-tech sectors (e.g. biotechnology, information technology, new materials), other terms that are being used are `technopole' (Castells and Hall, 1994) and `technopolis' (Smilor et al., 1988). To describe the growth of successful techno-industrial-scientific complexes (e.g. technology parks, science cities, and techno-industrial districts), Castells and Hall (1994) have introduced the concept of technopoles. The concept refers to “various deliberate attempts to plan and promote within one concentrated area, technologically innovative, industrial-related production” (Castells and Hall, 1994, p. 8). There have been various attempts to create and develop technopoles all around the world. Such a policy serves three purposes (Castells and Hall, 1994): to develop new industries as a national policy, to regenerate a declining or stagnant region, and to develop a milieu of innovation. Those objectives are pursued through furthering collaboration between leading research universities, corporate laboratories, core firms with their subcontractors and spin-offs, and venture capitalists. Another related concept relevant to understanding dynamic techno-industrial districts is milieux of innovation, defined by Castells and Hall (1994, p. 9) as “social, institutional, organisational, economic and territorial structures that create the conditions for the continuous generation of synergy, (…) both for the units of production that are part of the milieu and for the milieu as a whole”.
In this paper, we will talk mainly about regional clustering (Brusco, 1982; Becattini, 1991; Best, 1993; Scott, 1994; Saxenian, 1994) in general, and more specifically about clustering within the context of Internet and multimedia technology (Braczyk et al., 1999). In Silicon Valley in the Polder (Bouwman and Hulsink, 2000), we dedicated, in addition to a number of chapters on emerging ICT-clusters in the Netherlands and Belgium, a section on the analysis of internationally well-known milieux of high-tech innovation. One example is found in Boston, also known as Route 128, after the highway along which the principal companies are located (Raytheon, DEC, etc.) (Rosegrant and Lampe, 1992; Saxenian, 1994). Others are Silicon Valley, the region between San Francisco and San José (Rogers and Larsen, 1984; Saxenian, 1994; Kenney, 2000; Lee et al., 2000), and Silicon Alley, situated in Manhattan, New York, where Internet and e-commerce companies are concentrated (Coopers and Lybrand, 1997; Pavlik, 1999; Heydebrand, 1999; PriceWaterhouseCoopers, 2000). The analyses of these technopoles in the United States and the emerging ICT-clusters in the Netherlands and in Flanders, as well as in other places, along with a number of specific concepts, such as the role played by incubation centres (e.g. the Twinning centres in the Netherlands), venture capitalists and change agents, have led to a dynamic model for the analysis of ICT clustering. This model will be used in this paper to provide a critical description, analysis and comparison of a number of ICT-clusters in the Low Countries. First of all, an introduction and discussion of the model is given.
Section snippets
A dynamic model for ICT clustering
The achievement of a lasting concentration of economic activity within a certain geographical area depends on a number of aspects. One may think of technological innovations and the role played by knowledge centres, the degree of entrepreneurship, company networks and other institutions, and a shared culture where collective learning and mutual trust are essential. Smilor et al. (1988) have introduced a conceptual framework to describe the process of high-technology development and economic
A critical evaluation of the Valleys and Alleys in the Low Countries
The extent to which Dutch and Flemish ICT-clusters will be able to emulate the success of Silicon Valley and other regions can be assessed on the basis of the above-mentioned criteria. If we use these criteria to arrive at a preliminary qualitative assessment with regards to a number of existing local ICT-networks in the Low Countries, five regions stand out (Bouwman and Hulsink, 2000):
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The Louvain Technology Corridor, in which a central role is played by the Inter-university Centre for Micro
Conclusion and discussion
We have briefly described a model that can be used to describe and evaluate the dynamics of ICT-cluster formation. Based on the model we assessed five clusters, namely Dommel Valley (Eindhoven), the Louvain Technology Corridor, Flanders Language Valley, Amsterdam Alley and Twente. Until now we have used qualitative data to assess the potential of these five regions in the Low Countries. The results as presented in this paper are promising and ask for further, more quantitative validation of the
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