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Growing Silicon Valley On A Landscape: An Agent-Based Approach To High-Tech Industrial Clusters

In: Industry And Labor Dynamics The Agent-Based Computational Economics Approach

Author

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  • JUNFU ZHANG

    (Public Policy Institute of California, 500 Washington Street, Suite 800, San Francisco, CA 94111, USA)

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.

Suggested Citation

  • Junfu Zhang, 2004. "Growing Silicon Valley On A Landscape: An Agent-Based Approach To High-Tech Industrial Clusters," World Scientific Book Chapters, in: Roberto Leombruni & Matteo Richiardi (ed.), Industry And Labor Dynamics The Agent-Based Computational Economics Approach, chapter 13, pages 259-283, World Scientific Publishing Co. Pte. Ltd..
    • Handle: RePEc:wsi:wschap:9789812702258_0013
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    Cited by:

    1. Mingze Li & Jiaze Li & Xiaofang Chen, 2022. "Employees’ Entrepreneurial Dreams and Turnover Intention to Start-Up: The Moderating Role of Job Embeddedness," IJERPH, MDPI, vol. 19(15), pages 1-22, July.
    2. 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.
    3. Lucio Biggiero & Enrico Sevi, 2009. "Opportunism by cheating and its effects on industry profitability. The CIOPS model," Computational and Mathematical Organization Theory, Springer, vol. 15(3), pages 191-236, September.
    4. Brenner Thomas, 2008. "Cluster dynamics and policy implications," ZFW – Advances in Economic Geography, De Gruyter, vol. 52(1), pages 146-162, October.
    5. 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.
    6. 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.
    7. Junfu Zhang, 2007. "Access to Venture Capital and the Performance of Venture-Backed Start-Ups in Silicon Valley," Economic Development Quarterly, , vol. 21(2), pages 124-147, May.
    8. 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.
    9. 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 and the Associazione ICC, vol. 22(3), pages 617-647, June.
    10. 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.
    11. Guido Fioretti, 2005. "Agent-Based Models of Industrial Clusters and Districts," Urban/Regional 0504009, University Library of Munich, Germany.
    12. 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.
    13. 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.
    14. James Lee Caton, 2019. "Creativity in a theory of entrepreneurship," Journal of Entrepreneurship and Public Policy, Emerald Group Publishing Limited, vol. 8(4), pages 442-469, September.
    15. Isaak, Robert, 2009. "From collective learning to Silicon Valley replication: The limits to synergistic entrepreneurship in Sophia Antipolis," Research in International Business and Finance, Elsevier, vol. 23(2), pages 134-143, June.
    16. Flavio Lenz-Cesar & Almas Heshmati, 2010. "Agent-based Simulation of Cooperative Innovation," TEMEP Discussion Papers 201052, Seoul National University; Technology Management, Economics, and Policy Program (TEMEP), revised Jan 2010.
    17. Heshmati, Almas & Lenz-Cesar, Flávio, 2013. "Determinants and Policy Simulation of Firms Cooperation in Innovation," IZA Discussion Papers 7487, Institute of Labor Economics (IZA).
    18. Kamath, Ram & Sun, Zhanli & Hermans, Frans, 2022. "Policy instruments for green-growth of clusters: Implications from an agent-based model," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 43, pages 257-269.
    19. 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.
    20. Emiliano Brancaccio & Mauro Gallegati & Raffaele Giammetti, 2022. "Neoclassical influences in agent‐based literature: A systematic review," Journal of Economic Surveys, Wiley Blackwell, vol. 36(2), pages 350-385, April.

    More about this item

    Keywords

    Simulation; Agent-Based; Computational Economics; Labor; Industrial Dynamics; Innovation; Cluster; Firm Behavior;
    All these keywords.

    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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