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Evolutionary Game Analysis of the Innovation Behavior of High-Tech Enterprises with Government Participation

Author

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  • Chen Gong
  • Jian Liu
  • Jinping Chang

Abstract

High-tech enterprises, as the key subjects that can stimulate innovation vitality and promote innovation-driven development strategies in China, require government guidance for their innovative activities. However, the existing research has not answered the issue of how the government behavior activates the innovation ability of high-tech enterprises and what is the internal mechanism. As such, this paper takes government participation in high-tech enterprises as its research object, constructs an evolutionary game model of government participation in enterprise innovation, analyzes the internal mechanism of improvements to high-tech enterprises’ innovation ability under government tax and fee policy incentives and regulatory measures, and uses MATLAB numerical simulation to verify the results. The research shows that (1) increasing the general corporate income tax rate and reducing the high-tech corporate income tax rate can promote the transformation of general enterprises into high-tech enterprises and encourage enterprises to engage in scientific and technological innovation activities. However, when the high-tech corporate income tax rate is lower than 0.1, the marginal effect will be reduced. (2) Increasing the deduction coefficient and amortization coefficient can make high-tech enterprises more motivated to participate in innovation activities and thus render enterprise innovation more lucrative. (3) Increasing administrative penalties from regulatory authorities can promote the development of innovative activities in high-tech enterprises, but their intensity must be controlled within a reasonable range. The presented results have reference value for the adjustment of tax and fee policies among high-tech enterprises.

Suggested Citation

  • Chen Gong & Jian Liu & Jinping Chang, 2021. "Evolutionary Game Analysis of the Innovation Behavior of High-Tech Enterprises with Government Participation," Mathematical Problems in Engineering, Hindawi, vol. 2021, pages 1-15, September.
  • Handle: RePEc:hin:jnlmpe:5528042
    DOI: 10.1155/2021/5528042
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    Cited by:

    1. Kun Liang & Peng Wu & Rui Zhang, 2024. "Research on the Evaluation of Regional Scientific and Technological Innovation Capabilities Driven by Big Data," Sustainability, MDPI, vol. 16(4), pages 1-22, February.

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