%0 Journal Article %A Yan SUN %A Ming HU %A Bei ZHANG %T A quantitative analysis of Shanghai municipal solid waste classification policies from the perspective of policy instruments %D 2021 %R 10.18402/resci.2021.11.07 %J Resources Science %P 2224-2235 %V 43 %N 11 %X

As a leading city in the classification of municipal solid waste in China, Shanghai is representative and typical in the practice of domestic waste classification policy. Based on the policy instruments theory, this study adopted the content analysis method and conducted a quantitative analysis on 31 municipal solid waste classification policies of Shanghai by building an analytical framework, defining the unit of analysis, encoding, and conducting statistical analysis. The sample policies were analyzed from two dimensions of basic policy instruments and waste classification activities. The study found that: (1) The municipal solid waste sorting policy in Shanghai is characterized by high level of government attention, multi-department cooperation and emphasis on government guidance, which are conducive to easing policy inertia, alleviating sectoral barriers and promoting active participation of social subjects in the policy implementation. (2) There are some shortcomings in the design and application of policy instruments. On the one hand, the structure of policy instruments is unbalanced, which is reflected in the over-supply of environmental policy instruments, insufficient supply-oriented policy instruments, and shortage of demand-oriented policy instruments, leading to unsustainable policy implementation. Unreasonable use of various sub-instruments leads to the waste of policy resources. On the other hand, policy instrument application without a clear focus cannot match with current situation of waste sorting. Based on these results, policy recommendations such as increasing the use of demand-oriented policy instruments and focusing on the rational use of policy instruments at all stages were put forward.

%U https://www.resci.cn/EN/10.18402/resci.2021.11.07