An Analysis of Heuristic Behavior in NIMBY Conflicts Based on Evolutionary Game Theory

Xueguang Lyu, Hui-min Liu, Feng Xu
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引用次数: 1

Abstract

The accelerating process of urbanization has expanded the citizens’ demands of integral NIMBY(Not-In-My-Back-Yard) facilities in their daily life, which in turn leads to a series of NIMBY conflicts, thus affected social stability as well as the effective construction of public facilities severely. The resistance feeling in the surrounding general public, who are the primary stakeholders of NIMBY facilities, is likely to make them misjudge the project, thus oppose the construction and operation of the project. To better depict the public’s heuristic behavior in the decision-making process, this paper considering heuristic bias, presents an evolutionary game model between the public and the government. Then it analyzes the stable strategy according to replicator dynamics equation. Further, it aims to discuss the effect of heuristic bias coefficient, environmental loss compensation and financial compensation difference on the Evolutionary Stable Strategy(ESS) through MATLAB simulations. The results show that the existence of heuristic bias may turn the public’s behavior from cooperation to resistance, while in the meantime, increasing the financial compensation difference can offset the impact of heuristic bias to a certain degree. Finally, this paper offers policy recommendations from the perspective of reducing heuristic bias and providing financial support, in order to ensure the construction and operation of NIMBY facilities smoothly while maximizing their social benefits.
基于进化博弈论的邻避冲突中的启发式行为分析
城市化进程的加快扩大了市民在日常生活中对整体邻避设施的需求,进而引发了一系列邻避冲突,严重影响了社会稳定和公共设施的有效建设。作为邻避设施的主要利益相关者,周边公众的抵触情绪很可能使他们对项目产生误判,从而反对项目的建设和运营。为了更好地描述公众在决策过程中的启发式行为,本文考虑了启发式偏差,提出了公众与政府之间的演化博弈模型。然后根据复制机动力学方程分析了稳定策略。进一步,通过MATLAB仿真,探讨了启发式偏差系数、环境损失补偿和财务补偿差异对进化稳定策略(ESS)的影响。结果表明,启发式偏见的存在可能使公众的行为从合作转向抵抗,同时,增加经济补偿差异可以在一定程度上抵消启发式偏见的影响。最后,本文从减少启发式偏差和提供资金支持的角度提出政策建议,以保证邻避设施建设和运营的顺利进行,同时使其社会效益最大化。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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