运筹与管理 ›› 2021, Vol. 30 ›› Issue (5): 110-115.DOI: 10.12005/orms.2021.0152

• 理论分析与方法探讨 • 上一篇    下一篇

区域大气污染协同治理的府际间信任演化博弈研究

景熠, 杜鹏琦, 曹柳   

  1. 重庆理工大学 管理学院,重庆 400054
  • 收稿日期:2019-04-15 出版日期:2021-05-25
  • 作者简介:景熠(1987-),男,贵州都匀人,博士,副教授,研究方向:供应链管理、环境与生态管理等;杜鹏琦(1993-),男,甘肃陇南人,硕士研究生,研究方向:协同管理;曹柳(1997-),四川宜宾人,硕士研究生,研究方向:环境与生态管理。
  • 基金资助:
    国家社会科学基金项目:我国重点区域大气污染协同治理模式研究(14BGL100);重庆市人文社会科学研究项目:成渝区域大气污染协同治理的影响机理和动态演化研究(18SKGH096)

Evolutionary Game on Trust among Local Governments in Collaborative Governance of Regional Air Pollution

JING Yi, DU Peng-qi, CAO Liu   

  1. College of Management,Chongqing University of Technology, Chongqing400054, China
  • Received:2019-04-15 Online:2021-05-25

摘要: “空气流域”内各个地方政府之间的信任程度,是影响大气污染协同治理关系稳定性的关键因素。从地方政府的有限理性出发,构建了三个地方政府参与区域大气污染协同治理的非对称信任演化博弈模型。在求解模型均衡点并分析其稳定性的基础上,探讨了不同情况下的信任演化路径,以及各个参数变化对信任概率的影响。研究表明:提高直接治理效益、协同加成效益、协同间接效益,降低治理风险成本,显化潜在损失,并合理确定生态补偿数额,能够提升协同治理关系最终达到信任均衡状态的可能性。

关键词: 协同治理, 区域大气污染, 信任均衡, 演化博弈

Abstract: The degree of trust among local governments in the air basin is a key factor affecting the stability of the collaborative governance relationship of air pollution. Based on the bounded rationality of local governments, an asymmetric trust evolutionary game model of three local governments participating in the collaborative governance of regional air pollution is constructed. On the basis of solving the equilibrium point of the model and analyzing its stability, the evolutionary path of trust in different situations and the influence of the variations of each parameter on trust probability are discussed. This research shows that improving the direct governance benefit, collaborative addition benefit, collaborative indirect benefit, reducing governance risk cost, revealing potential loss, and reasonably determining the amount of ecological compensation can enhance the possibility that the collaborative governance relationship ultimately reaches the state of trust equilibrium.

Key words: collaborative governance, regional air pollution, trust equilibrium, evolutionary game

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