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

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  • Jie Jiang

    (Key Laboratory of Road and Traffic Engineering of the Ministry of Education, Tongji University, Shanghai 201804, China
    Tongji University Urban Mobility Institution, Tongji University, Shanghai 200082, China
    Shenzhen Urban Transport Planning Center Co., Ltd., Shenzhen 518000, China)

  • Jiaorong Wu

    (Key Laboratory of Road and Traffic Engineering of the Ministry of Education, Tongji University, Shanghai 201804, China
    Tongji University Urban Mobility Institution, Tongji University, Shanghai 200082, 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)

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.

Suggested Citation

  • Jie Jiang & Jiaorong Wu & Xiaochun Zhang & Maopeng Sun & Shu Chen, 2023. "Association of the Built Environment with Residents’ Car Dependence: Evidence from Shenzhen, China," Sustainability, MDPI, vol. 15(13), pages 1-13, June.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:13:p:9888-:d:1176121
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    References listed on IDEAS

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    1. Yang, Wenyue & Chen, Bi Yu & Cao, Xiaoshu & Li, Tao & Li, Peng, 2017. "The spatial characteristics and influencing factors of modal accessibility gaps: A case study for Guangzhou, China," Journal of Transport Geography, Elsevier, vol. 60(C), pages 21-32.
    2. Zhao, Pengjun & Bai, Yu, 2019. "The gap between and determinants of growth in car ownership in urban and rural areas of China: A longitudinal data case study," Journal of Transport Geography, Elsevier, vol. 79(C), pages 1-1.
    3. Wang, Xiaoquan & Yin, Chaoying & Zhang, Junyi & Shao, Chunfu & Wang, Shengyou, 2021. "Nonlinear effects of residential and workplace built environment on car dependence," Journal of Transport Geography, Elsevier, vol. 96(C).
    4. Chaoying Yin & Chunfu Shao & Xiaoquan Wang, 2018. "Built Environment and Parking Availability: Impacts on Car Ownership and Use," Sustainability, MDPI, vol. 10(7), pages 1-15, July.
    5. François Sprumont & Ariane Scheffer & Geoffrey Caruso & Eric Cornelis & Francesco Viti, 2022. "Quantifying the Relation between Activity Pattern Complexity and Car Use Using a Partial Least Square Structural Equation Model," Sustainability, MDPI, vol. 14(19), pages 1-16, September.
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