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Study on Multi-Agent Evolutionary Game of Emergency Management of Public Health Emergencies Based on Dynamic Rewards and Punishments

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  • Ruguo Fan

    (School of Economics and Management, Wuhan University, Wuhan 430072, China)

  • Yibo Wang

    (School of Economics and Management, Wuhan University, Wuhan 430072, China)

  • Jinchai Lin

    (School of Economics and Management, Wuhan University, Wuhan 430072, China)

Abstract

In the context of public health emergency management, it is worth studying ways to mobilize the enthusiasm of government, community, and residents. This paper adopts the method of combining evolutionary game and system dynamics to conduct a theoretical modeling and simulation analysis on the interactions of the behavioral strategies of the three participants. In response to opportunistic behavior and inadequate supervision in the static reward and punishment mechanism, we introduced a dynamic reward and punishment mechanism that considers changes in the social environment and the situation of epidemic prevention and control. This paper proves that the dynamic reward and punishment mechanism can effectively suppress the fluctuation problem in the evolutionary game process under static scenarios and achieve better supervision results through scenario analysis and simulation experiments.

Suggested Citation

  • Ruguo Fan & Yibo Wang & Jinchai Lin, 2021. "Study on Multi-Agent Evolutionary Game of Emergency Management of Public Health Emergencies Based on Dynamic Rewards and Punishments," IJERPH, MDPI, vol. 18(16), pages 1-22, August.
    • Handle: RePEc:gam:jijerp:v:18:y:2021:i:16:p:8278-:d:608547
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    References listed on IDEAS

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    Cited by:

    1. Shuwen Zhao & Guojian Ma & Juan Ding, 2023. "Symbiotic Mechanism of Multiple Subjects for the Resource-Based Disposal of Medical Waste in China in the Post-Pandemic Context," Sustainability, MDPI, vol. 15(1), pages 1-19, January.
    2. Jiguang Wang & Yushang Hu & Weihua Qu & Liuxin Ma, 2022. "Research on Emergency Supply Chain Collaboration Based on Tripartite Evolutionary Game," Sustainability, MDPI, vol. 14(19), pages 1-25, September.
    3. Ma, Xuan & Yu, Deqing & Wang, Ke, 2024. "Unraveling the intricacies of panic buying: An evolutionary game-theoretic exploration of the evolution and intervention," Journal of Retailing and Consumer Services, Elsevier, vol. 79(C).
    4. Ruguo Fan & Rongkai Chen, 2022. "Promotion Policies for Electric Vehicle Diffusion in China Considering Dynamic Consumer Preferences: A Network-Based Evolutionary Analysis," IJERPH, MDPI, vol. 19(9), pages 1-21, April.
    5. Dezhen Wang & Buwajian Abula & Aniu Jizuo & Jianhua Si & Kaiyang Zhong & Yujiao Zhou, 2022. "Agricultural Openness and the Risk of COVID-19 Incidence: Evidence from China," IJERPH, MDPI, vol. 19(6), pages 1-18, March.
    6. Bong Gu Kang & Hee-Mun Park & Mi Jang & Kyung-Min Seo, 2021. "Hybrid Model-Based Simulation Analysis on the Effects of Social Distancing Policy of the COVID-19 Epidemic," IJERPH, MDPI, vol. 18(21), pages 1-17, October.
    7. Yanmin Ouyang & Haoran Zhao, 2022. "Evolutionary Game Analysis of Collaborative Prevention and Control for Public Health Emergencies," Sustainability, MDPI, vol. 14(22), pages 1-20, November.
    8. Jida Liu & Yuwei Song & Shi An & Changqi Dong, 2022. "How to Improve the Cooperation Mechanism of Emergency Rescue and Optimize the Cooperation Strategy in China: A Tripartite Evolutionary Game Model," IJERPH, MDPI, vol. 19(3), pages 1-27, January.
    9. Ruzhi Xu & Chenglong Yan & Chenlong Wang & Huawei Zhao, 2023. "The Game Analysis among Governments, the Public and Green Smart Supply Chain Enterprises in Necessity Purchase and Supply during COVID-19 Pandemic," Sustainability, MDPI, vol. 15(9), pages 1-30, April.

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