The aim of this study is to evaluate the performance of urban environmental governance by developing hesitant fuzzy linguistic analytic network process (HFL-ANP). The study bridges the gaps in current knowledge in the following ways: the study methodically develops the HFL-ANP method to evaluate and pick the optimal environmental governance strategy from alternatives; theoretically, network structure of evaluation indicators system on environmental governance is constructed, and the objective and subjective information in the evaluation process of environmental governance is combined. In detail, based on the environmental Kuznets curve (EKC) and the pollution haven hypothesis, the paper constructs the evaluation indexes system of environmental governance and takes observation time length into consideration. Then, we choose three urban cases of environmental governance by exploring the existing literature. Furthermore, we develop the HFL-ANP method and apply it to the cases. The study calculates the initial weights of all indexes by using multiplicative consistency of the HFL preference relation, and derives the decision matrix through combining objective information with subjective information of environmental governance. Finally, we come to the following conclusions: ANP network stricture is close to real-world practical problems and provides the basis for HFL-ANP method; HFL-ANP is a very suitable method of assessing environmental governance; and based on the urban cases of environmental governance, Shanghai is the optimal alternative. In addition, this indicator system can only be applied to cities in China, and the administrative hierarchy of policies has not been considered by this method. Thus, future studies should expand this method and indicator network to contain different countries and different administrative hierarchy.
|Number of pages||20|
|Journal||International Journal of Environmental Research and Public Health|
|Early online date||4 Nov 2018|
|Publication status||Published - Nov 2018|
Bibliographical noteFunding Information:
Funding: The study was funded by National Nature Science Foundation of China (Grant No. 51808392).
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- Control indexes
- Environmental governance
- Network structure