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Cooperative protection of technical secrets in cultural industry cluster-based on evolutionary game model of leading enterprises and following enterprises

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  • Mingxia Xu
  • Zuojiao Hu

Abstract

Due to the confidentiality, value and exclusivity of technical secrets, how to protect the technical secrets within cultural industry clusters has become a paradoxical issue and a research hotspot. Focusing on the collaborative protection of technical secrets within cultural industry clusters, this paper analyzes the strategies of collaborative protection of technical secrets between leading enterprises and following enterprises based on evolutionary game theory, and uses dynamic evolution and simulation methods to identify key factors behind the strategy choices, which further enriches the evolutionary mechanism of collaborative protection, and expands the application scenarios of the theory of evolutionary game. As the research results show, the collaborative protection strategy of technical secrets within cultural industry clusters is feasible, the cost of collaborative protection, government subsidies, and compensation for collaborative deposits are key variables that determine the trend of the game. The government subsidy coefficient, the collaborative deposits, and the difference in the number of technology secrets are strongly sensitive factors underlying the mode of protection, while the synergistic benefits between firms are weakly sensitive factors. Therefore, this paper proposes that increasing government subsidies and collaborative deposits, and reducing the differences in the number of technical secrets among game subjects can promote enterprises to eliminate suspicion and increase their willingness to cooperate in protecting technical secrets.

Suggested Citation

  • Mingxia Xu & Zuojiao Hu, 2023. "Cooperative protection of technical secrets in cultural industry cluster-based on evolutionary game model of leading enterprises and following enterprises," PLOS ONE, Public Library of Science, vol. 18(9), pages 1-22, September.
    • Handle: RePEc:plo:pone00:0291459
    DOI: 10.1371/journal.pone.0291459
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    References listed on IDEAS

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    1. Lu, Jinna & Wang, Lu & Wang, Yi-Ling & Zhang, Xiaoguang, 2017. "Logit selection promotes cooperation in voluntary public goods game," Applied Mathematics and Computation, Elsevier, vol. 310(C), pages 134-138.
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