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The crucial role that the built environment plays in affecting commuting behavior has been widely examined with a primary focus on the residential built environment. Moreover, the spatial heterogeneities at residential and work locations are rarely considered simultaneously in the literature. Based on data from 2012 Changchun household travel survey, we employed a hierarchical cross-classified structural equation model to explore the relationship between the residential and workplace built environment and commuting mode choice. Additionally, the spatial heterogeneities at both residential and work locations are recognized. The estimation results provide evidence on the necessity of accommodating spatial heterogeneities at both locations. Apart from the residential built environment, all built environment attributes at work locations show significant associations with commuting mode choice. These findings suggest that urban planners should pay more attention to the industrial and commercial areas where most employment opportunities concentrate because of the role that the built environment around workplaces plays. [ABSTRACT FROM AUTHOR]

Urban rail transit (URT) is often implemented in order to reduce car ownership and use. However, it is still unclear how the impacts of the built environment on car dependence differ in transit-oriented development (TOD) areas and non-TOD areas. Based on 2012 Changchun household travel survey data, this study aims to explore whether the relationships between the built environment and household vehicle kilometers traveled (VKT) vary between station and non-station areas by employing a multi-group structural equation model (SEM). The results suggest that the effects of the built environment on household VKT vary between station and non-station areas. Additionally, the results confirm the remarkable role that the built environment plays in influencing car ownership and use by revealing the direct, indiract and total effects. These findings provide a better understanding of the inherent mechanism by which URT moderates the impacts of the built environment on car ownership and use. It suggests that, for urban planners and policy makers, promoting compact land use strategies can have a positive effect on reducing car use, and URT implementation can effectively strengthen the effects. [ABSTRACT FROM AUTHOR]

The relationships between the built environment (BE) and car dependence have been thoroughly evaluated, with a primary focus on the residential BE; however, the effects of the BE at workplaces have remained largely unexplored. Little is known about the potential nonlinear effects of the BE at both locations. Using data from a household travel survey in Changchun, China, we aimed to reveal the nonlinear effects of the residential and workplace BE on car dependence by building a gradient boosting decision trees model. The results show that the BE at both locations has strong explanatory power for car ownership and car purchasing intention. With relative contributions values of 17.90% and 18.13%, respectively, the BE at workplaces contributes less to explaining the two dependent variables than the BE at residences. All BE attributes show nonlinear effects on car ownership, and car purchasing intention and the effects differ between residential and workplace locations. • This study examines the effects of the built environment (BE) on car ownership and car purchasing intention. • The BEs at both residential and workplace locations show impacts on two dependent variables. • The relative contributions of the BE at residences are larger than the BE at workplaces. • The effects of all BE attributes at both locations are nonlinear. [ABSTRACT FROM AUTHOR]