Journal
TRANSPORTATION RESEARCH PART A-POLICY AND PRACTICE
Volume 171, Issue -, Pages -Publisher
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.tra.2023.103662
Keywords
Land use; Car ownership; Mode choice; Structural equation model; Multilevel cross-classified model
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This study proposes an approach to integrate the merits of structural equation models and discrete choice models while accommodating spatial dependence to explore the relationship between the built environment and commuting behavior. The results show that overlooking the mediating role of car ownership will produce false statistical inference and understate built environment effects. The study suggests 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.
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.
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