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

Ruguo Fan, Yibo Wang and Jinchai Lin
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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

IJERPH, 2021, vol. 18, issue 16, 1-22

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.

Keywords: COVID-19; regulation; evolutionary game; subsidy and punishment mechanism (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (9)

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