Neighborhood design and vehicle type choice: Evidence from Northern California

被引:68
作者
Cao, XY
Mokhtarian, PL
Handy, SL
机构
[1] Univ Calif Davis, Dept Civil & Environm Engn, Davis, CA 95616 USA
[2] Univ Calif Davis, Inst Transportat Studies, Davis, CA 95616 USA
[3] Univ Calif Davis, Dept Stat, Davis, CA 95616 USA
[4] Univ Calif Davis, Dept Environm Sci & Policy, Davis, CA 95616 USA
关键词
air quality; land use; nested logit model; smart growth;
D O I
10.1016/j.trd.2005.10.001
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Previous studies have found that suburban development is associated with the unbalanced choice of light duty trucks. The specific aspects of the built environment that influence vehicle choice, however, have not been well-established. Further, these studies have not shed much light on the underlying direction of causality: whether neighborhood designs themselves, as opposed to preferences for neighborhood characteristics or attitudes towards travel, more strongly influence individuals' decisions regarding vehicle type. Using a sample from Northern California, this study investigated the relationship between neighborhood design and vehicle type choice, controlling for residential self-selection. Correlation analyses showed that neighborhood design has a strong association with vehicle type choice. Specifically, traditional neighborhood designs are correlated with the choice of passenger cars, while suburban designs are associated with the choice of light duty trucks. The nested logit model suggests that sociodemographic and attitudinal factors play an important role, and that an outdoor spaciousness measure (based on perceptions of yard sizes and off-street parking availability) and commute distance also impact vehicle type choice after controlling for those other influences. This study, therefore, supports the premise that land use policies have at least some potential to reduce the choice of light duty trucks, thereby reducing emissions. (c) 2005 Elsevier Ltd. All rights reserved.
引用
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页码:133 / 145
页数:13
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