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基于随机Petri网的邻避冲突演化过程模型及情景仿真分析——以垃圾焚烧发电厂为例 被引量:4

Evolutionary Process Model and Scenario Simulation Analysis of NIMBY Conflict Based on Stochastic Petri Nets-A case study of MSW Incineration Power Plant
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摘要 在中国城镇化发展过程中,因某些基础设施的选址与建设而引发的“邻避冲突”时有发生,针对这一问题,对该类冲突的影响因素及其演化过程进行深入而系统的分析。通过借鉴扎根理论思想及多案例研究,对影响冲突演化过程的主要因素进行提炼与归纳,并构建冲突演化过程系统图。然后基于随机Petri网理论,对冲突演化过程进行建模,并进行情景仿真分析。结果表明,政府单边决策、意见领袖的组织策划及与设施有关的负面信息传播扩散容易引发周边居民不良的情绪反应及抵制抗议行为;政府妥协有利于事件的平息,但会使周边居民对政府形成负面经验认知、对政府产生不信任以及对风险产生过高的感知;政府无效的风险沟通行为可能会导致冲突升级,但能减少周边居民对于政府的不信任及风险感知。 In the process of China’s urbanization,the NIMBY conflict caused by the location and construction of some infrastructure has occurred from time to time.Based on the grounded theory and multi-case study,the main factors affecting the evolutionary process of the conflict are extracted,on this basis,and the structured description method is used to construct the systematic diagram of the conflict.Then the stochastic Petri network is introduced to model theprocess of the conflict,and the following is the scenario simulation analysis of the factors.The results show that:unilateral decision-making of the government,organized planning of the opinion leader and the spread of negative information related to facilities can easily lead to negative emotion and resistance of the surrounding residents.Compromise of the government is helpful to appease the conflict,but will make the surrounding residents to form a negative perception of the government,higher perception of the risk and distrust of the government.The ineffective risk communication of the government may lead to the escalation of the conflict,but can reduce the surrounding residents’distrust and risk perception.
作者 全雄伟 左高山 QUAN Xiong-wei;ZUO Gao-shan(Central South University, School of Business, Changsha, 410083,China;Central South University,School of Public Administration, Changsha 410083, China)
出处 《运筹与管理》 CSSCI CSCD 北大核心 2022年第1期135-141,共7页 Operations Research and Management Science
基金 国家自然科学基金面上项目(71573280)。
关键词 邻避冲突 演化过程 随机PETRI网 情景仿真 NIMBY conflict evolutionary process stochastic petri nets scenario simulation
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