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Sophia-Antipolis as a technopolis phenomenon: is myth becoming reality?

  • Michel Quéré
Part of the Economics of Science, Technology and Innovation book series (ESTI, volume 29)

Abstract

This contribution discusses the importance of the spatial dimension of localized knowledge by focussing the analysis on a specific territorial area: the Sophia-Antipolis park, located in the south of France. This chapter establishes how the production of knowledge is closely related to the process of accumulation that has moulded the economic working of companies located in the Sophia-Antipolis park. Economic working refers partly to quantitative aspects, but mainly to the nature of inter-firms relationships, to the physiology of local science-industry partnerships, and, more largely, to the characteristics of the local labour market (Quéré, 1999). In that respect, Sophia-Antipolis is very interesting. Obviously, it starts from scratch in the seventies and progressively appears for some sectoral patterns as one of the most suited locations in Europe where “high-tech” activities have concentrated (mainly information and communication technologies [ICTs]). As this project is only 30 years old, it is possible to have a complete vision of its development and to analyse its transformation toward an actual technopolis-type of economic working. Section 17.2 analyses the role of history in the emergence of localized knowledge for some of the dominant activities. Section 17.3 deals in more detail with the transition toward the technopolis-type of economic functioning. Section 17.4 discusses the necessary conditions to promote the development of localized knowledge by focussing more especially on major requirements for the local institutional infrastructure. Concluding remarks address some related policy implications.

Keywords

Localize Knowledge Large Company Local Labour Market Industrial District Innovative Behaviour 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

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Copyright information

© Springer Science+Business Media New York 2003

Authors and Affiliations

  • Michel Quéré

There are no affiliations available

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