How to Control Waste Incineration Pollution? Cost-Sharing or Penalty Mechanism—Based on Two Differential Game Models

焚化 微分博弈 机制(生物学) 污染 博弈论 控制(管理) 经济 惩罚法 计算机科学 数学优化 微观经济学 环境科学 废物管理 数学 工程类 人工智能 哲学 生态学 认识论 生物
作者
Huijie Li,Deqing Tan
出处
期刊:Decision Analysis [Institute for Operations Research and the Management Sciences]
卷期号:21 (2): 91-109 被引量:7
标识
DOI:10.1287/deca.2023.0078
摘要

This study explores whether the government should implement a cost-sharing or penalty mechanism to control waste incineration pollution and investigates which policy can best incentivize incineration plants to invest in pollution control. We design two differential game models, one based on a cost-sharing approach and one on a penalty system, to model the interactions between the government and incineration plants. We then compare and analyze the equilibrium outcomes in both scenarios. Our findings reveal that when incineration pollution significantly impacts the government, both the cost-sharing and penalty mechanisms are effective in stimulating incineration plants to enhance their pollution control efforts. However, when incineration pollution significantly affects the incineration plants themselves, the cost-sharing mechanism proves to be more effective in terms of pollution control. Furthermore, we find that the government derives greater utility under the cost-sharing mechanism compared with the penalty mechanism, especially as the amount of municipal solid waste (MSW) increases. In contrast, incineration plants tend to generate higher profits under the cost-sharing mechanism. These findings and their accompanying managerial implications may provide valuable guidance for government agencies in formulating policies to manage incineration pollution and encourage waste incineration plants to invest in improving their pollution control systems. Funding: This work was supported by the National Natural Science Foundation of China [Grant 71571149], Humanities and Social Sciences Foundation for Youth Scholars of Ministry of Education of China [Grant 22YJC630171], and Natural Science Foundation of Sichuan Province of China [Grant 2023NSFSC1055].
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