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| Data-driven Modeling on Incentive Residents′ Behavior in Garbage Classification |
| ZHAN Xiuxiu1,2,3, CHEN Wei3, MAO Jiangqun2, CHEN Xiang2, SHEN Shuying2, LIU Chuang3, ZHANG Zike1
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1. College of Media and International Culture, Zhejiang University, Hangzhou 310058;
2. Zhejiang Jinghe Intelligent Technology Co., Ltd, Hangzhou 311122;
3. Alibaba Research Center for Complexity Sciences, Hangzhou Normal University, Hangzhou 311121 |
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Abstract To explore the driving effect of incentive mechanisms on residents′ enthusiasm for participating in garbage classification, this article is based on empirical data analysis of garbage classification in multiple communities. Using the RFM model, it quantifies residents′ enthusiasm for participating in garbage classification and categorizes user value. Based on this, a multi-agent simulation model of user value transformation is established around subjective norms, classification knowledge, and classification attitudes. The results show that residents′ enthusiasm for garbage disposal is influenced by subjective norms; there is a positive correlation between classification knowledge, classification attitudes, and residents′ enthusiasm for garbage disposal.
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Received: 23 December 2023
Published: 03 June 2025
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