The Impacts of the Multiscale Built Environment on Commuting Mode Choice: Spatial Heterogeneity, Moderating Effects, and Implications for Demand Estimation - Wenliang Jian; Xiaoxiao Liu; Hao Liu; Yongshi Hu; Liangpeng Gao (Journal of Advanced Transportation)
Promoting the usage of sustainable commuting modes requires in-depth understanding about residents’ commuting mode choice behavior. This study presents an empirical study to investigate the relationship between the built environment and commuting mode choice using CLDS 2016 cross-city questionnaire data. Several multilevel multinomial logit models including the null model, base model, and moderating effect model are developed to analyze the effects of built environments at both city and neighborhood levels on commuting mode choice. Estimation results of the null model reveal the significant spatial heterogeneities in commuting mode choice across different cities and different neighborhoods within a specific city. We then explore the potential built environment variables yielding the spatial heterogeneity via the base model. Results show that the built environment at the city level (including the urbanization rate, number of public transportation vehicles, metro operating mileage, GDP, city population density, and road area per capita) and neighborhood level (including neighborhood population density, air quality, neighborhood location, and land use diversity) could partially explain the spatial heterogeneities in commuting mode choice. In addition, the moderating effects of these built environments on the link between commuting time and commuting mode choice are examined. Results imply that the urbanization rate and neighborhood population density moderate the effect of commuting time on choosing nonmotorized modes, while neighborhood location moderates the effect of commuting time on choosing public transit. Also, the mode shares of nonmotorized mode and public transit under different levels of commuting time are estimated in different built environment contexts. The findings of this study are expected to provide serviceable support for urban planning and transportation policy making.