Citation

Ding C, Zhou X, Jason Cao X, Yang J. Transp. Res. A Policy Pract. 2023; 171: e103662.

Copyright

(Copyright © 2023, Elsevier Publishing)

DOI

10.1016/j.tra.2023.103662

PMID

unavailable

Abstract

Built environment interventions have been widely promoted to reduce car use and associated carbon emissions. Although many studies have explored the relationship between the built environment and commuting behavior, few have simultaneously accounted for the mediating role of car ownership in the relationship, the effects of both residential and workplace environments, and spatial dependence among respondents. To fill the gap, this study proposes an approach to integrate the merits of structural equation models and discrete choice models while accommodating spatial dependence. We apply it to the 2019 household travel survey data from Zhongshan, China. This study shows that spatial heterogeneity is prevalent, and that overlooking the mediating role of car ownership will produce false statistical inference and understate built environment effects. The results suggest that urban growth boundary, densification and bus supply enhancement at residential neighborhoods, and residential development clustered around centers may discourage commuting by car, whereas road investment is counterproductive.

Language: en

Keywords

Car ownership; Land use; Mode choice; Multilevel cross-classified model; Structural equation model