Implications from Swarm Simulation on Industrial Clusters’ Evolution

This paper argues that the phenomenon of industrial clusters is a kind of complex and dynamic process. With the heterogeneity of firms involved in clusters and their open connections with external environment being reasonably justified, the paper thinks that the evolution of industrial clusters should be observed and studied by the approach of computer simulation. Some factors from inside or outside, local or global, work together to drive the growth and decline of industrial clusters. Some implications are drawn through the analysis of the results by simulations designed on java-swarm platform. Suggestions are proposed accordingly.

[1]  P. Krugman History and Industry Location: The Case of the Manufacturing Belt , 1991 .

[2]  Peter Nijkamp,et al.  Towards sustainable city policy: an economy-environment technology nexus , 1998 .

[3]  C. Sabel,et al.  The Second Industrial Divide: Possibilities for Prosperity , 1984 .

[4]  Walter Isard,et al.  Location and Space Economy: A General Theory Relating to Industrial Location, Market Areas, Land Use, Trade and Urban Structure , 1957 .

[5]  G. Becattini Italian Industrial Districts: Problems and Perspectives , 1991 .

[6]  R. Camagni,et al.  ICTs and territorial competitiveness in the era of internet , 2005 .

[7]  Michael B. Arthur,et al.  CAREERS, COMMUNITIES, AND INDUSTRY EVOLUTION: LINKS TO COMPLEXITY THEORY , 2001 .

[8]  Marco Bellandi,et al.  Local development and embedded large firms , 2001 .

[9]  M. Porter Clusters and the new economics of competition. , 1998, Harvard business review.

[10]  H. Bathelt,et al.  Clusters and knowledge: local buzz, global pipelines and the process of knowledge creation , 2004 .

[11]  Beatriz Junquera,et al.  Why are clusters beneficial? A review of the literature , 2010 .

[12]  Mark S. Granovetter Economic Institutions as Social Constructions: A Framework for Analysis , 1992 .

[13]  Mark S. Granovetter The Impact of Social Structure on Economic Outcomes Social Networks and Economic Outcomes: Core Principles , 2022 .

[14]  A. Markusen Sticky Places in Slippery Space: A Typology of Industrial Districts* , 1996 .