Residents’ Preferences on Green Infrastructure in Wuhan, China

Chang Lu (), Katsuya Tanaka and Qulin Shen
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Chang Lu: Graduate School of Economics, Shiga University, Hikone, Shiga 522-8522, Japan
Katsuya Tanaka: Faculty of Economics and Research Center for Sustainability and Environment, Shiga University, Hikone, Shiga 522-8522, Japan
Qulin Shen: Tozai Trading (Shanghai Pudong New Area) Co., Ltd., Tozai Trading Co., Ltd., Shanghai 200002, China

Sustainability, 2024, vol. 16, issue 23, 1-19

Abstract: Green infrastructure (GI) provides considerable benefits, including stormwater runoff management, biodiversity conservation, and urban sustainability promotion, and thus has garnered widespread attention. However, the limited research on residents’ preferences for GI constrains further promotion in China. To address this issue, data were collected from 436 residents in Wuhan, China, through an online survey. This study employed a comprehensive analytical framework that integrates best–worst scaling (BWS) with the contingent valuation method (CVM) to assess the preferences of residents in Wuhan, China, for six types of GI and estimate their willingness to pay (WTP) for GI enhancements. The conditional model and mixed logit model results indicated that residents preferred GI facilities that offer direct benefits, such as street trees and permeable pavements, and showed a lower preference for structures less suited to a Chinese context, such as eco-roofs. Regarding heterogeneity, only permeable pavements showed significant variation in preferences. Furthermore, the average WTP for GI enhancement was 142.28 RMB/household/year. Factors including familiarity with GI, information sources, and air quality improvement perceptions positively influenced the WTP, while low income negatively impacted the WTP. These findings offer insights for urban planners to develop effective policies to enhance public support for GI and promote urban sustainability.

Keywords: best–worst scaling; contingent valuation method; green infrastructure; sponge city program; urban flooding; willingness to pay (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2024
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