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Multi-Agent Evolutionary Game Analysis of Group Panic Buying in China during the COVID-19 Pandemic

Author

Listed:
  • Xunqing Wang

    (School of Public Administration, Shandong Technology and Business University, Yantai 264005, China)

  • Nan Zhang

    (School of Public Administration, Shandong Technology and Business University, Yantai 264005, China)

  • Hang Zhou

    (School of Public Administration, Shandong Technology and Business University, Yantai 264005, China)

  • Xinpeng Huang

    (School of Public Administration, Shandong Technology and Business University, Yantai 264005, China)

  • Rundong Luo

    (School of Business, Shandong University, Weihai 264209, China)

Abstract

With the global outbreak of COVID-19, the panic-buying incidents triggered by the variants of the Omicron strain have severely affected the normal social order. This paper considers the complex interest game and interactive relationship among multiple subjects in the mass-panic buying event caused by rumors and constructs a three-party evolution game model of local government, rumor-monger, and public. The strategy-selection process of each subject based on evolutionary game theory is studied, and the strategy selection of three game subjects in different situations and related influencing factors are analyzed. Taking the example of the montmorillonite powder panic buying caused by the XBB virus strain rumor in China, the evolutionary game model constructed in this study is simulated and analyzed. The study shows that the evolutionary process of the mass panic-buying event is characterized by six stages: the initial stage; the outbreak stage; the spread stage; the climax stage; the relief stage; and the recovery stage. There are four stable points in the evolutionary game of the three game subjects, namely (no intervention, no rumor, no panic buying), (no intervention, rumor, no panic buying), (intervention, no rumor, no panic buying), and (intervention, rumor, no panic buying). The strategy of government intervention will be adjusted according to the strategy selection of the public and the rumor-monger. Under the mechanism of reward and punishment of the higher-level government, increasing the punishment and reward intensity of the higher-level government will promote the local government to intervene in the rumor-mongering event faster, but increasing the reward intensity has a more significant impact on the intervention behavior of the local government than punishment, and increasing punishment intensity has a more significant impact on the non-rumor-mongering behavior of the rumor-monger than reward. The parameters of social risk-bearing cost, risk transmission coefficient, rumor-mongering income and cost, and public drug purchase cost have different degrees of influence on the evolutionary behavior of game subjects. Therefore, this study provides new ideas for effectively responding to mass panic buying events in the context of public emergencies.

Suggested Citation

  • Xunqing Wang & Nan Zhang & Hang Zhou & Xinpeng Huang & Rundong Luo, 2023. "Multi-Agent Evolutionary Game Analysis of Group Panic Buying in China during the COVID-19 Pandemic," Mathematics, MDPI, vol. 11(13), pages 1-24, July.
    • Handle: RePEc:gam:jmathe:v:11:y:2023:i:13:p:3006-:d:1187910
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    References listed on IDEAS

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    1. Yaodong Yang & Huaqing Ren & Han Zhang, 2022. "Understanding Consumer Panic Buying Behaviors during the Strict Lockdown on Omicron Variant: A Risk Perception View," Sustainability, MDPI, vol. 14(24), pages 1-19, December.
    2. Guohua He & Zirun Hu, 2022. "A Model of Panic Buying and Workforce under COVID-19," IJERPH, MDPI, vol. 19(24), pages 1-14, December.
    3. Youwei Yuan & Lanying Du & Xiumei Li & Fan Chen, 2022. "An Evolutionary Game Model of the Supply Decisions between GNPOs and Hospitals during a Public Health Emergency," Sustainability, MDPI, vol. 14(3), pages 1-23, January.
    4. Chen, Tinggui & Jin, Yumei & Yang, Jianjun & Cong, Guodong, 2022. "Identifying emergence process of group panic buying behavior under the COVID-19 pandemic," Journal of Retailing and Consumer Services, Elsevier, vol. 67(C).
    5. Shan, Haiyan & Pi, Wenjie, 2023. "Mitigating panic buying behavior in the epidemic: An evolutionary game perspective," Journal of Retailing and Consumer Services, Elsevier, vol. 73(C).
    6. Irineu de Brito Junior & Hugo Tsugunobu Yoshida Yoshizaki & Flaviane Azevedo Saraiva & Nathan de Campos Bruno & Roberto Fray da Silva & Celso Mitsuo Hino & Larissa Limongi Aguiar & Isabella Marrey Fer, 2023. "Panic Buying Behavior Analysis according to Consumer Income and Product Type during COVID-19," Sustainability, MDPI, vol. 15(2), pages 1-17, January.
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