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作者

Liya Yang;Chuan Ding;Yang Ju;Bin Yu

来源

CITIES,Vol.112,Issue1,Article 103114

语言

英文

关键字

Built environment;Car ownership;Commuting behavior;Multilevel sample selection model;Spatial heterogeneity

作者单位

School of Public Administration, Renmin University of China, Beijing 100872, China;School of Transportation Science and Engineering, Beijing Key Laboratory for Cooperative Vehicle Infrastructure System and Safety Control, Beihang University, Beijing 100191, China;Beijing Advanced Innovation Center for Big Data and Brain Computing, Beihang University, Beijing 100191, China;Institute of Urban and Regional Development, University of California, Berkeley, CA, United States;School of Public Administration, Renmin University of China, Beijing 100872, China;School of Transportation Science and Engineering, Beijing Key Laboratory for Cooperative Vehicle Infrastructure System and Safety Control, Beihang University, Beijing 100191, China;Beijing Advanced Innovation Center for Big Data and Brain Computing, Beihang University, Beijing 100191, China;Institute of Urban and Regional Development, University of California, Berkeley, CA, United States

摘要

Car dependency has been well recognized in low-density urban areas in developed countries, where travel demand management (TDM) has focused on providing transit-riding and non-motorized modes of transport, rather than restricting car ownership. In contrast, many megacities in China have adopted vehicle quota systems, fearing that additional car owners will become addicted to driving despite the soaring travel congestion and air pollution. This study investigated two research questions: Under what built environment characteristics would China's car owners give up driving for other commuting modes? Are the effects of built environment characteristics on car ownership and commuting mode choice spatially heterogeneous across zones? We use a household travel survey in Nanjing city, where no car quota system exists, to examine car owners' commuting mode choice. Innovatively, a multilevel discrete choice model with sample selection was used to reveal the effects of the built environment on car ownership and commuting mode choice simultaneously. We found significant spatial heterogeneities in car ownership and commuting mode choice across traffic analysis zones, while the built environment was found to play an important role. Our findings suggest that Chinese urbanites may be less addicted to driving than they appear, and city governments should be more progressive in regulating driving by improving the urban form.