Association of the Built Environment with Residents’ Car Dependence: Evidence from Shenzhen, China

Jie Jiang, Jiaorong Wu (), Xiaochun Zhang (), Maopeng Sun and Shu Chen
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Jie Jiang: Key Laboratory of Road and Traffic Engineering of the Ministry of Education, Tongji University, Shanghai 201804, China
Jiaorong Wu: Key Laboratory of Road and Traffic Engineering of the Ministry of Education, Tongji University, Shanghai 201804, China
Xiaochun Zhang: Shenzhen Urban Transport Planning Center Co., Ltd., Shenzhen 518000, China
Maopeng Sun: Shenzhen Urban Transport Planning Center Co., Ltd., Shenzhen 518000, China
Shu Chen: Shenzhen Urban Transport Planning Center Co., Ltd., Shenzhen 518000, China

Sustainability, 2023, vol. 15, issue 13, 1-13

Abstract: Reducing car dependence is the key to achieving the goal of green and sustainable development. Compared with the existing studies, which mainly focus on administrative areas, this study takes residential areas as the research unit. Four spatial regression models were used to investigate the effect on car dependence of six factors of the built environment (land use mix, population density, jobs–housing balance, bus stop density, metro station density, and road network density). Various test results show that the geography-weighted regression (GWR) model has more substantial explanatory power and that the estimated coefficients of built environment characteristics vary positively or negatively in diverse residential communities. The findings demonstrate that the impact of built environment characteristics on car dependence is significantly spatially heterogeneous. These results are conducive to better comprehending how built environment factors affect car dependence and help establish policies and strategies to promote sustainable transportation.

Keywords: car dependence; built environment; spatial heterogeneity; sustainable transportation (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2023
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