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An Agent-Based Simulation Model of Knowledge Spillover Under the Influence of High-Speed Railway


  • Zhao Yun

    (School of Public Policy & Management, Tsinghua University, Beijing, 100084, China)

  • Bi Chongren

    (School of Economics and Management, Beijing Jiaotong University, Beijing, 100044, China)


The calculation for the influence of high-speed railway on knowledge spillover is based on the results of global instantaneous equilibrium in the mechanism explanation of knowledge spillover. In real production, the interaction between the high-speed railway and the regional innovation system is dynamic and local. In order to simulate the impact of high-speed railway on innovation activities in the time dimension, it is necessary to simulate scenarios under appropriate parameter assumptions. Based on the interaction of economic participants, a discrete evolutionary simulation model is established, which is helpful to predict and estimate the evolution of spatial effect of high-speed railway according to the theory of cellular automata. It is concluded that high-speed railway accelerates the formation of knowledge innovation industry cluster in the region in the process of regional knowledge innovation and evolution. Under the influence of high-speed railway, the node city will gradually evolve into a regional innovation center. By comparing the production evolution of knowledge innovation system with and without high-speed railway, the results show that high-speed railway has a more significant impact on knowledge spillover in higher knowledge privatization environment. Under the background of low labor migration rate, high-speed railway has increased the potential of regional innovation to external knowledge spillover. In the case of higher labor migration rate, the convergence rate of influence of high-speed railway on the concentration of innovation is faster.

Suggested Citation

  • Zhao Yun & Bi Chongren, 2019. "An Agent-Based Simulation Model of Knowledge Spillover Under the Influence of High-Speed Railway," Journal of Systems Science and Information, De Gruyter, vol. 7(2), pages 99-114, April.
  • Handle: RePEc:bpj:jossai:v:7:y:2019:i:2:p:99-114:n:1
    DOI: 10.21078/JSSI-2019-099-16

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    References listed on IDEAS

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