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

充分考虑农村"熟人社会"特点，首次采用复杂网络演化博弈模型，通过数值仿真分析了声誉损失和奖励政策对农户垃圾分类行为扩散深度的动态影响.结果表明：政府不干预时，垃圾分类将无法在农村自发持续而普遍推广；在一定范围内提高声誉损失或奖励均可显著促进农户分类；仅依靠单一政策，无法实现分类的深度扩散，若依靠声誉损失与奖励相互配合，可实现低政策强度、高扩散深度的合意效果；搭便车收益的提高会抑制垃圾分类扩散深度；注重经验学习和适应能力的EWA学习策略更有助于促进垃圾分类扩散.上述结论广泛适用于分类初始状态、学习能力、人口规模不同的农村，对中国农村垃圾分类具有普遍性的启发意义.最后，提出了充分利用"熟人社会"优势构建与农村社会经济特征相契合的垃圾分类激励政策建议.

Reward and punishment incentive mechanism of domestic waste classification in rural China: Based on complex network evolutionary game model

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.