Citation

Wang X, Yin C, Zheng C, Shen Y, Shao C. Transp. Plann. Tech. 2023; 46(7): 888-911.

Copyright

(Copyright © 2023, Informa - Taylor and Francis Group)

DOI

10.1080/03081060.2023.2239236

PMID

unavailable

Abstract

Built environment (BE) planning and parking policy are two major strategies for restricting car use. However, researchers usually explore the independent associations of BE and parking policy with the use of the car in commuting, and most earlier studies are limited to investigating the benefits of integrating them. This study adopts a machine learning approach to explore the associations of home and workplace BE features and parking policy with the use of the car in commuting and whether the associations of BE features are moderated by parking policy.

RESULTS suggest that workplace BE features have larger collective contributions to the use of the car in commuting than home BE features. All BE features have nonlinear associations with the use of the car in commuting, and the nonlinear patterns differ across home and workplace neighborhoods. Moreover, free parking and parking convenience have significant moderating effects on the connection between BE and the use of the car in commuting. Thus, planning practitioners and policy makers should highlight the importance of coordinating BE planning and policy making to restrict the use of the car in commuting.

Language: en

Keywords

Built environment; car use; machine learning model; nonlinear interaction effect; parking policy