Abstract:Based on the characteristics of rural "acquaintance society", this paper adopts the complex network evolutionary game model for the first time to analyze the dynamic impacts of reputation loss and reward policy on the diffusion depth of farmers' waste classification behavior through numerical simulation. The results show that, if the government does not intervene, garbage classification will not be spontaneously, continuously and widely popularized in rural areas. Within a certain range, improving reputation or reward can significantly promote the classification of farmers. Only relying on a single policy cannot achieve deep diffusion for classification. If both reputation loss and reward incentives are used, desirable effect of high diffusion depth can be achieved based on low policy intensity. An increase in free-ride earnings will inhibit the diffusion depth of waste classification. EWA learning strategy focusing on experience learning and adaptability is more helpful to promote the diffusion of waste classification. The above conclusions are not only comprehensively applicable to rural areas with different initial classification state, learning abilities and population sizes, but have universal implication significance for rural waste classification in China. Finally, this paper puts forward the choice of waste classification incentive policy by fully taking the advantages of "acquaintance society" and building a waste classification incentive policy consistent with the socio-economic characteristics of rural areas.
魏夕凯, 马本. 农村生活垃圾分类治理的奖惩激励机制——基于复杂网络演化博弈模型[J]. 中国环境科学, 2022, 42(8): 3822-3831.
WEI Xi-kai, MA Ben. Reward and punishment incentive mechanism of domestic waste classification in rural China: Based on complex network evolutionary game model. CHINA ENVIRONMENTAL SCIENCECE, 2022, 42(8): 3822-3831.
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