期刊
SCIENCE OF THE TOTAL ENVIRONMENT
卷 646, 期 -, 页码 821-831出版社
ELSEVIER
DOI: 10.1016/j.scitotenv.2018.07.339
关键词
Assessment of river ecosystem; Willingness to pay; Choice experiment; Mixed logit model; Multinomial logit model
资金
- National Natural Social Science Foundation of China [15ZDA052]
The concept of ecosystem services provides a valuable approach for linking humans and nature and for supporting the protection of natural ecosystems. River water services, which influence public health and daily routines, have both social and ecological benefits to a surrounding area. However, river networks and their services have suffered extensive destruction due to urbanization and industrialization, especially in China. An assessment of river system benefits and recognition of public preferences are crucial for sustainable river management and effective river system restoration. The objective of this study was to assess a household's willingness to pay using a choice experiment (CE) with mixed logit and multinomial logit models. This technique was applied to evaluate a respondent's preferences regarding water service attributes such as upper basin, middle basin and lower basin ecological water distribution; water quality; and payment and the possible source of heterogeneity in these attributes. The estimated likelihood ratio test demonstrated that random parameter logit model (RPL) models had considerably more explanatory power than multinomial logit (MNL) models. It was also revealed that the RPL-II model was the most powerful among all the models, demonstrating the capability of that model to predict the choices of the respondents. Furthermore, the findings show that water quality was the most preferred river attribute, and households were willing to pay more for the water quality attribute that derives the highest marginal value. Household income level, residential location, education level, and sex were the main factors influencing willingness to pay. These assessments provide guidance, policy recommendations and a reference for researchers and policy makers to improve and enhance current river water services in the future. (C) 2018 Elsevier B.V. All rights reserved.
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