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.

Although the impacts of built environment on car ownership and use have been extensively studied, limited evidence has been offered for the role of spatial effects in influencing the interaction between built environment and travel behavior. Ignoring the spatial effects may lead to misunderstanding the role of the built environment and providing inconsistent transportation policies. In response to this, we try to employ a two-step modeling approach to investigate the impacts of built environment on car ownership and use by combining multilevel Bayesian model and conditional autocorrelation (CAR) model to control for spatial autocorrelation. In the two-step model, the predicting car ownership status in the first-step model is used as a mediating variable in the second-step car use model. Taking Changchun as a case study, this paper identifies the presence of spatial effects in influencing the effects of built environment on car ownership and use. Meanwhile, the direct and cascading effects of built environment on car ownership and use are revealed. The results show that the spatial autocorrelation exists in influencing the interaction between built environment and car dependency. The results suggest that it is necessary for urban planners to pay attention to the spatial effects and make targeted policy according to local land use characteristics.

Public transport services are often improved to decrease auto-related mobility. However, it remains unclear how the built environment influences auto ownership and commuting mode choice near public transit stations. Using 3318 individuals across China, this study contributes to investigating the relationship between the built environment, auto ownership and commuting mode choice simultaneously in neighborhoods near public transit stations by employing an integration of a structural equation model (SEM) and discrete choice model (DCM). The results indicate that the built environment exhibits significant impacts on auto-related mobility near public transit stations and auto ownership plays an intermediary role between the exogenous variables and commuting mode choice, thus it can moderate the influences of built environment attributes on commuting mode choice. The results suggest that increasing green coverage rates and promoting diverse land use development strategies in transit-oriented development (TOD) areas may make contributions to auto-related mobility reduction and low-carbon travel initiatives.

Along with urbanization and economic development, the number of private cars has increased rapidly in recent years in China, which contributes to concerns about traffic congestion, hard parking, energy consumption, and emissions. This study aims to investigate the joint effect of built environment and parking availability on car ownership and use based on a household travel survey conducted in Changchun, China. The binary logistic model was first employed to investigate the determinants of the car ownership in Changchun. Next, this study examined the potential impacts of the built environment and parking availability on car use for the journey to work. The result shows that built environment and parking availability can be both significantly associated with car ownership and use after controlling for the socio-economic characteristics. Moreover, in contrast with the model ignoring the parking availability, the model for car use considering the joint effect fit the data better. The results indicate that car dependency depends on the joint effect of the built environment and parking availability. These results suggest that transit-oriented urban expansion and compact land use can contribute to reducing car commuting. Meanwhile, parking restrictions at both trip start and end would be effective for sustainable transport because parking oversupply could encourage more car dependency.

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.

The literature has offered much evidence regarding associations between the built environment (BE) and commuting behavior. However, most prior studies are conducted based on cross-sectional samples from developed countries, and little is known about the longitudinal link between BE and commuting behavior. Based on two rounds of survey data from China, this study examines relationships of BE with commuting mode choice from both cross-sectional and longitudinal perspectives. The effects of life-cycle events are considered within a unified framework. Results of the longitudinal examination of BE and commuting mode shift largely support the cross-sectional analysis. Specifically, promoting more balanced land use and improving residential density are important for car use reductions and active travel initiatives. Meanwhile, more balanced land use improves the probability of commuting by motorcycle and electric bike, but reduces the probability of commuting by public transit. This study also highlights the remarkable role played by life-cycle events in affecting commuting mode shifts.