How does the built environment at residential and work locations affect car ownership? An application of cross-classified multilevel model

被引:65
|
作者
Ding, Chuan [1 ,2 ]
Cao, Xinyu [2 ]
机构
[1] Beihang Univ, Sch Transportat Sci & Engn, Beijing Key Lab Cooperat Vehicle Infrastruct Syst, Beijing 100191, Peoples R China
[2] Beihang Univ, Beijing Adv Innovat Ctr Big Data & Brain Comp, Beijing 100191, Peoples R China
基金
中国国家自然科学基金;
关键词
Auto ownership; Land use; Travel behavior; Spatial dependency; Random effect model; LAND-USE; SELF-SELECTION; TRAVEL BEHAVIOR; CHOICE; IMPACTS; COMMUTE;
D O I
10.1016/j.jtrangeo.2019.01.012
中图分类号
F [经济];
学科分类号
02 ;
摘要
Although many studies investigate the connection between the residential built environment and car ownership, the literature offers limited evidence on the effect of work locations. Using data from the Washington metropolitan area, this study develops a cross-classified multilevel model to examine the influences of the built environment at both residential and workplace locations on car ownership, while controlling for spatial dependency arising from spatial aggregation. We found that built environment characteristics at work locations, particularly bus stop density and employment density, influence household car ownership. They explain one third of the total variation of car ownership across work locations. The residential environment appears to impose a stronger influence than the workplace environment. Density, diversity, design, transit access around residences and distance from home to the city center affect car ownership.
引用
收藏
页码:37 / 45
页数:9
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