ORIGINAL RESEARCH
Evolutionary Game Analysis of Green Production Supervision Considering Limited Resources of the Enterprise
Yanhong Ma 1  
,   Zhiyong Wan 1,   Chunhua Jin 1  
 
More details
Hide details
1
School of Economics and Management, Beijing Information Science and Technology University, Beijing, China, 100192
CORRESPONDING AUTHOR
Chunhua Jin   

School of Economics and Management, Beijing Information Science and Technology University, China
Submission date: 2020-06-10
Final revision date: 2020-09-02
Acceptance date: 2020-09-06
Online publication date: 2020-12-10
Publication date: 2021-02-05
 
Pol. J. Environ. Stud. 2021;30(2):1715–1724
 
KEYWORDS
TOPICS
ABSTRACT
Environmental issues recently have emerged as an important research problem. The enterprise’s green production and the government’s supervision is the keyway to reduce environmental hazards. Against this background, in this paper, we described green production supervision as a game between the enterprise and the government. Unlike previous studies, we considered the impact of limited resources of the enterprise when building the game model, which makes the model more in line with the actual situation. Because of the bounded rationality of the players, an evolutionary game model is built. The enterprise’s goal was profit maximization in the game. And the government’s goal was assumed to be social profit maximization. Solving the evolutionary game model, the evolutionarily stable strategy (ESS) of the model is obtained. Then, an impact analysis of how supervisory parameters affected the ESS is provided. Subsequently, we proposed some effective measures to reduce environmental hazards, such as increasing the penalty on the enterprise once pollution is discovered, reducing the mandatory green production cost reasonably, increasing the taxation ratio and improving public participation. The specific conditions of these parameters for better ESS are given based on the impact analysis. These conditions can guide the government’s decision-making in green production supervision.
eISSN:2083-5906
ISSN:1230-1485