Affiliation:
1. Management School, Hainan University, Haikou 570228, China
2. International Business School, Shaanxi Normal University, Xi’an 710119, China
Abstract
Exploring the determinants of residents’ willingness to pay (WTP) for water quality improvements is essential for protecting the water quality and formulating effective governance policies. This paper applies the double-bounded dichotomous contingent valuation method (CVM) to determine residents’ WTP for water quality improvements, calculate the average annual willingness of Haikou residents to pay for water quality improvements, and explore the factors influencing residents’ WTP for water quality improvements. Interpretive structural modeling (ISM) is then used to further analyze the association and hierarchy between the influencing factors. The results show that (1) Residents are willing to pay an average of 28.42 RMB/household/year for water quality improvements, and the total annual value of water quality improvements in Haikou is at least 5.58 × 108 RMB; (2) age, education level, income level, minor family member and government trust are the main factors that significantly (p < 0.05) influence urban residents’ WTP; (3) among the factors identified as significantly affecting WTP, the deeper root factors include educational attainment, age, and ultimately, the willingness of residents to participate in water quality improvements through indirect factors (government trust, income level, presence of minors). This study allows an in-depth and detailed understanding of the determinants of residents’ WTP for water quality improvements and provides a practical and relevant guide to water quality improvements in the tropics.
Funder
National Natural Science Foundation of China
Hainan Provincial Natural Science Foundation of China
Ministry of Education of Humanities and Social Science project
Innovation Capability Support Program of Shaanxi
Shaanxi Philosophy and Social Science Research Project
Subject
Water Science and Technology,Aquatic Science,Geography, Planning and Development,Biochemistry
Cited by
7 articles.
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