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Growing Silicon Valley on a landscape: an agent-based approach to high-tech industrial clusters

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  • Junfu Zhang

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Abstract

We propose a Nelson-Winter model with an explicitly defined landscape to study the formation of high-tech industrial clusters such as those in Silicon Valley. The existing literature treats clusters as the result of location choices and focuses on how firms may benefit from locating in a cluster. We deviate from this tradition by emphasizing that high-tech industrial clusters are characterized by concentrated entrepreneurship. We argue that the emergence of clusters can be explained by the social effect through which the appearance of one or a few entrepreneurs inspire many followers locally. Agent-based simulation is employed to show the dynamics of the model. Data from the simulation and the properties of the model are discussed in light of empirical regularities. Variations of the model are simulated to study policies that are favorable to the high-tech economy. Copyright Springer-Verlag Berlin/Heidelberg 2003

Suggested Citation

  • Junfu Zhang, 2003. "Growing Silicon Valley on a landscape: an agent-based approach to high-tech industrial clusters," Journal of Evolutionary Economics, Springer, vol. 13(5), pages 529-548, December.
  • Handle: RePEc:spr:joevec:v:13:y:2003:i:5:p:529-548
    DOI: 10.1007/s00191-003-0178-4
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    Cited by:

    1. Henri L.F. de Groot & Jacques Poot & Martijn J. Smit, 2007. "Agglomeration, Innovation and Regional Development: Theoretical Perspectives and Meta-Analysis," Tinbergen Institute Discussion Papers 07-079/3, Tinbergen Institute.
    2. Ge, Houtian & Gray, Richard & Nolan, James, 2015. "Agricultural supply chain optimization and complexity: A comparison of analytic vs simulated solutions and policies," International Journal of Production Economics, Elsevier, vol. 159(C), pages 208-220.
    3. Per L. Bylund, 2015. "Signifying Williamson's Contribution to the Transaction Cost Approach: An Agent-Based Simulation of Coasean Transaction Costs and Specialization," Journal of Management Studies, Wiley Blackwell, vol. 52(1), pages 148-174, January.
    4. Leonhard Dobusch & Elke Schüßler, 2013. "Theorizing path dependence: a review of positive feedback mechanisms in technology markets, regional clusters, and organizations," Industrial and Corporate Change, Oxford University Press, vol. 22(3), pages 617-647, June.
    5. Guido Fioretti, 2005. "Agent-Based Models of Industrial Clusters and Districts," Urban/Regional 0504009, EconWPA.
    6. Flavio Lenz-Cesar & Almas Heshmati, 2009. "Determinants of Firms Cooperation in Innovation," TEMEP Discussion Papers 200927, Seoul National University; Technology Management, Economics, and Policy Program (TEMEP), revised Nov 2009.
    7. Brenner Thomas, 2008. "Cluster dynamics and policy implications," Zeitschrift für Wirtschaftsgeographie, De Gruyter, vol. 52(1), pages 146-162, October.
    8. Antonelli Cristiano & Ferraris Gianluigi, 2012. "Endogenous knowledge externalities: an agent based simulation model where schumpeter meets Marshall," Department of Economics and Statistics Cognetti de Martiis LEI & BRICK - Laboratory of Economics of Innovation "Franco Momigliano", Bureau of Research in Innovation, Complexity and Knowledge, Collegio 201202, University of Turin.
    9. Ugo Merlone & Michele Sonnessa & Pietro Terna, 2008. "Horizontal and Vertical Multiple Implementations in a Model of Industrial Districts," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 11(2), pages 1-5.
    10. Yoon, Hyungseok & Yun, Sunyoung & Lee, Joosung & Phillips, Fred, 2015. "Entrepreneurship in East Asian Regional Innovation Systems: Role of social capital," Technological Forecasting and Social Change, Elsevier, vol. 100(C), pages 83-95.
    11. Riccardo Boero & Flaminio Squazzoni, 2005. "Does Empirical Embeddedness Matter? Methodological Issues on Agent-Based Models for Analytical Social Science," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 8(4), pages 1-6.
    12. Heshmati, Almas & Lenz-Cesar, Flávio, 2013. "Determinants and Policy Simulation of Firms Cooperation in Innovation," IZA Discussion Papers 7487, Institute for the Study of Labor (IZA).

    More about this item

    Keywords

    Silicon Valley; Agent-based simulation; Industiral clusters;

    JEL classification:

    • B21 - Schools of Economic Thought and Methodology - - History of Economic Thought since 1925 - - - Microeconomics
    • B22 - Schools of Economic Thought and Methodology - - History of Economic Thought since 1925 - - - Macroeconomics
    • G34 - Financial Economics - - Corporate Finance and Governance - - - Mergers; Acquisitions; Restructuring; Corporate Governance
    • D23 - Microeconomics - - Production and Organizations - - - Organizational Behavior; Transaction Costs; Property Rights
    • O47 - Economic Development, Innovation, Technological Change, and Growth - - Economic Growth and Aggregate Productivity - - - Empirical Studies of Economic Growth; Aggregate Productivity; Cross-Country Output Convergence

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