Why some clusters succeed whereas others decline ? Modelling the ambivalent stability properties of clusters
AbstractThe aim of this paper is to study the ambivalent properties of stabilities of clusters. We propose to enter the black box of the local knowledge externalities by focusing on the location decision externalities. In particular, we show that the nature of mimetic strategies in the convergence process of locational choices influence the dynamic stability of clusters. Thus, when uncertainty and search for legitimacy prevail on the need for coordination and the associated necessities of compatibility and technological convergence, the clusters are unstable, due to an excess of cognitive proximity and a risk of unintended spillovers. Nevertheless, this search for legitimacy, through the strategy which consists in following the locational choice of companies leader of a sector, can lead to the fast emergence of a cluster. But without relational proximity, its stability is not insured. These results are obtained following the formulation of some theoretical proposals on the links between location decision externalities and the resulting forms of socioeconomic proximities. This set of proposals is validated firstly by a model of simulation which makes it possible to test the properties of stability of aggregate outcomes of locational choices. Secondly, they are illustrated by a comparative empirical analysis of two main French clusters (Silicon Sentier and Sophia-Antipolis)..
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Bibliographic InfoPaper provided by Center for Research in Economics and Management (CREM), University of Rennes 1, University of Caen and CNRS in its series Economics Working Paper Archive (University of Rennes 1 & University of Caen) with number 200619.
Date of creation: 2006
Date of revision:
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Postal: CREM (UMR CNRS 6211) - Faculty of Economics, 7 place Hoche, 35065 Rennes Cedex - France
Find related papers by JEL classification:
- C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
- D85 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Network Formation
- R3 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Real Estate Markets, Spatial Production Analysis, and Firm Location
This paper has been announced in the following NEP Reports:
- NEP-ALL-2006-10-14 (All new papers)
- NEP-BEC-2006-10-14 (Business Economics)
- NEP-GEO-2006-10-14 (Economic Geography)
- NEP-INO-2006-10-14 (Innovation)
- NEP-URE-2006-10-14 (Urban & Real Estate Economics)
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