Developing effective intervention strategies to improve public participation in household waste recycling program: A data-driven agent-based behavior analysis approach

This study addresses the limited impact of the household waste recycling (HWR) program in promoting “Zero Waste City” due to insufficient and ineffective public participation. Given that a particular strategy can only affect certain but not all residents, we argue that diverse strategies are needed to achieve a full public participation. We propose a novel data-driven agent-based behavior analysis approach for developing diverse strategies to effectively and collectively improve HWR participation by changing behavior through their influence on the motivation and ability (M&A) of all residents. We first identify all M&A factors influencing HWR participation behavior based on the Fogg behavior model and develop a set of intervention strategies that encompass all M&A factors. The effectiveness of strategies in influencing the M&A of residents is assessed using multicriteria analysis. An agent-based model is developed to examine how the identified strategies improve HWR participation behavior through their direct effect and consequential interactive influence among residents. A multisectoral collaboration framework is established to facilitate collaborative implementation of the strategies among the key stakeholders. Through a case study in China, our analysis demonstrates that the systematic combination of targeted intervention strategies can increase HWR participation rates by >40 %. This significant improvement validates our approach's effectiveness in promoting behavioral change. This study contributes methodologically and practically to waste recycling efforts and resident behavior change by offering a strategy development approach that considers individual differences and social interactions, potentially leading to more effective HWR programs.