›› 2019, Vol. 31 ›› Issue (5): 254-266.

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Evolutionary Game Analysison Herding Behavior of Non-direct Stakeholders in Mass Emergencies

Xu Hao, Tan Deqing, Zhang Jingqin, Han Wei   

  1. School of Economics and Management, Southwest Jiaotong University, Chengdu 610031
  • Received:2017-01-09 Online:2019-05-28 Published:2019-05-31

Abstract:

As a hot issue that threatens political and social stability, mass emergencies are the important challenges faced by governments at all levels in China. It's important to analyze the psychological characteristics and behavioral mechanism of participants correctly, which has great significance to prevention and timely disposal of mass emergencies. For herding behavior in mass emergencies, this paper establishes an evolutionary game model of non-direct stakeholders who participate in mass emergencies to analyze the formation mechanism and influencing factors of herding behavior by considering the psychological effects of non-direct stakeholders, the cost of participation, the loss of personal image when not involved, the chances of "making trouble", the loss of opportunity when not involved and the fluke mind that the law is not responsible for the public, and on this basis, we introduce the government intervention to analyze the evolution mechanism and influencing factors of herd behavior. The results show that the herd behavior of non-direct stakeholders is affected by a series of very complex influencing factors, the numerical analysis of multi-equilibrium evolution shows that the proportion and evolution have an obvious correlation with participation cost, fluke mind, the loss of opportunity, government intervention, and so on. At the end of paper, some suggestions are given according to the numerical analysis, which provide a theoretical support for analyzing the psychological and herding behavior of the participants in the mass emergencies.

Key words: mass emergencies, herding behavior, non-direct stakeholders, evolutionary mechanism, group psychology, government intervention