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Evolutionary game of platform enterprises, government and consumers in the context of digital economy

Author

Listed:
  • Li, Cui
  • Li, Hong
  • Tao, Changqi

Abstract

The game process of stable strategies among the government, consumers, and platform enterprises is analyzed by using tripartite evolutionary game theory. The evolution path of platform enterprise, government and consumers is analyzed through numerical simulation by introducing parameters such as the degree of discriminatory pricing, the degree of data property right confirmation, and the intensity of supervision. Results show that the government can improve the market order by strengthening supervision and defining data property rights. When the benefits is higher than the punishment cost, the platform enterprises will choose to discriminatory pricing. But consumers and the media can effectively restrain the discriminatory behavior of platform enterprises by social exposure. In addition, in the face of discriminatory pricing on the platform and lax government supervision, consumers who are vulnerable can only “vote with their feet”, and their personal rights and supervision rights are difficult to protected.

Suggested Citation

  • Li, Cui & Li, Hong & Tao, Changqi, 2023. "Evolutionary game of platform enterprises, government and consumers in the context of digital economy," Journal of Business Research, Elsevier, vol. 167(C).
    • Handle: RePEc:eee:jbrese:v:167:y:2023:i:c:s0148296323002163
    DOI: 10.1016/j.jbusres.2023.113858
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    References listed on IDEAS

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    Cited by:

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    2. Han, Minglong & Liu, Yupeng, 2026. "Dynamic pricing mechanisms for generative artificial intelligence models across heterogeneous scenarios: An evolutionary game and complex network approach," Applied Mathematics and Computation, Elsevier, vol. 516(C).
    3. Wang, Ruipeng & Tai, Yuhong, 2025. "How does blockchain mitigate false advertising in live streaming E-commerce? A tripartite stochastic evolutionary game approach," Journal of Retailing and Consumer Services, Elsevier, vol. 85(C).
    4. Guo, Wenqiang & Liang, Yunze & Lei, Ming & Cai, Dongliang & Wu, Xinwei, 2024. "A stochastic catastrophe model of construction site safety hazards supervision and its resilience," Energy, Elsevier, vol. 300(C).
    5. Wei, Xiaochao & She, Qiping, 2026. "Cooperative supervision of livestreaming e-commerce based on stochastic evolutionary game and overconfidence," Technology in Society, Elsevier, vol. 84(C).
    6. Qu, Qixing & Wei, Chengxi & Wang, Mingxian & Wang, Yaxin, 2026. "From disclosure to compliance: Modeling the evolutionary dynamics of tripartite privacy regulation," Applied Mathematics and Computation, Elsevier, vol. 512(C).
    7. Xiyin Deng & Erfang Shan, 2026. "Tripartite strategies of intelligent assistants in shared accommodation considering privacy risks: an evolutionary game analysis," Information Technology & Tourism, Springer, vol. 28(1), pages 1-41, June.
    8. Li, Na & Lv, Tao & Guo, Yuxia & Xu, Jie & Zang, Xiuzhu & Guo, Jianli & Li, Mengyue, 2025. "Can government supervision ensure compliance by photovoltaic enterprises? An evolutionary game analysis," Energy Policy, Elsevier, vol. 206(C).
    9. Ma, Jia & Xie, Tingting, 2025. "Customer artificial intelligence, supply chain spillover effects, and supplier capacity utilization," International Review of Economics & Finance, Elsevier, vol. 103(C).
    10. Zhaoyue Qin & Yiming Chen & Yue Yan & Yi Huang, 2024. "Influencer Marketing Platforms’ Effect on Light Meal Purchase Intention and Behavior," Sustainability, MDPI, vol. 16(11), pages 1-20, May.
    11. Yang Song & Yijun Kong, 2024. "Tripartite Evolutionary Game Analysis of Product Quality Supervision in Live-Streaming E-Commerce," Mathematics, MDPI, vol. 12(16), pages 1-23, August.

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