Abstract
The frequent occurrence of nuclear NIMBY events seriously affects social stability and the development of the nuclear power industry. Exploring the evolutionary development of nuclear NIMBY events and their control strategies is an important proposition. Different from recent studies on the influence of static government intervention into public participation in the collective action of NIMBY events, this paper aims to analyze how dynamic government interventions affect the decisions of the public from the perspective of complex networks. To better understand the dynamic rewards and punishments, the motivation of the public in nuclear NIMBY events is treated as a cost–benefit decision-making process. Then, a network evolutionary game model (NEGM) is built to analyze the strategy selection of all participants who are connected by an interaction network of the public. In addition, the drivers of the evolution of public participation in nuclear NIMBY events are analyzed with computational experiments. The results indicate the following: (a) Under dynamic punishment conditions, the probability of public participation in protests decreases with the increase in the upper bound of punishment. (b) Static reward measures can better control the development of nuclear NIMBY events. However, under dynamic reward conditions, there is no obvious effect with the increase in the reward ceiling. (c) The effect of the combination of government reward and punishment strategies is different in different network sizes. At the same time, with the continuous expansion of the scale of the network, the effect of government intervention worsens.
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Funding
This research was supported by the National Natural Science Foundation of China (grant no. 71974090), Excellent Youth Program of Hunan Education Department (grant no. 210SJY018099), and Social Science Achievement Appraisal Committee Project in Hunan Province (grant no. XSP22YBZ049).
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Xiaoli Li: complete writing, mathematical modelling, and reference verification. Luo Wu: data analysis, software working. Tian Xie: supervision and conceptualization. Tieli Wang: supervision and conceptualization.
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Li, X., Wu, L., Xie, T. et al. The evolution of public participation under dynamic government intervention in nuclear NIMBY events: a network evolutionary game method. Environ Sci Pollut Res 30, 65026–65040 (2023). https://doi.org/10.1007/s11356-023-26662-6
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DOI: https://doi.org/10.1007/s11356-023-26662-6