NDLI: Multi-Scenario Evolutionary Game of Rumor-Affected Enterprises under Demand Disruption

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Multi-Scenario Evolutionary Game of Rumor-Affected Enterprises under Demand Disruption

Content Provider	MDPI
Author	Zhao, Chuan Li, Luyao Sun, Hongxia Yang, Hongji
Copyright Year	2021
Description	Rumors regarding food, medicine, epidemic diseases, and public emergencies greatly impact consumers’ purchase intention, disrupt market demand, affect enterprises’ operating strategies, and eventually increase the risk of market chaos. Governments must play an active role with limited resources under the situation of rumor spreading and demand disruption to maintain stable and sustainable market development. To identify the optimal evolutionary stable strategy (ESS) of both small and large enterprises when facing rumors, this paper investigates the following two choices of enterprises: reasonable and unreasonable pricing. The results reveal that government supervision priority should be set based on the rumor severity, collusion in markup and the endogeneity of the enterprises. From an exogenous perspective, rumor spreading induces enterprises to overcharge, and government supervision has the opposite effect. However, the demand disruption ratio is proven to motivate enterprises to implement reasonable pricing. The profit and loss ratio and homoplasy are two endogenous factors affecting enterprise decisions. Small enterprises are more likely to take advantage of public panic and overcharge, while large enterprises are inclined to choose reasonable pricing in consideration of their corporate image. In addition, the evidence indicates that the ESS of large firms has a stronger impact on small firms.
Starting Page	360
e-ISSN	20711050
DOI	10.3390/su13010360
Journal	Sustainability
Issue Number	1
Volume Number	13
Language	English
Publisher	MDPI
Publisher Date	2021-01-03
Access Restriction	Open
Subject Keyword	Sustainability Information and Library Science Rumors Demand Disruption Sustainable Market Government Supervision Evolutionary Game
Content Type	Text
Resource Type	Article

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