Driving Public Support for Urban Waste-Sorting Policies: A Configuration Analysis of Policy Factors

The Chinese government has become increasingly concerned about waste sorting and has implemented several supportive policies to promote sustainable development. Public support is critical to successful policy implementation. Hence, this study focused on increasing public support for waste-sorting policies. The complicated mechanisms underlying policy factors’ effects on public support for waste-sorting policies were investigated from a configuration perspective by employing a combination of random forest, necessary condition analysis, and fuzzy set qualitative comparative analysis methodologies. The results indicated that five policy factors, namely, perceived policy effectiveness, policy participation, policy fairness, policy preference, and government trust, have a strong predictive impact on public support outcomes. However, none could stand alone as necessary conditions for public support and their synergistic effects must be exploited. Five configurations were demonstrated as promoting public support for waste-sorting policies, in which the perceived policy effectiveness and policy preference were the core conditions for four of these configurations, playing a universal role in fostering public support. Overall, governments should be flexible in choosing acceptable paths to enhance public support based on local realities, with a focus on enhancing perceived policy effectiveness and policy preference.