Nonlinear and interaction effects of land use and motorcycles/E-bikes on car ownership

Qifan Shao, Wenjia Zhang, Xinyu (Jason) Cao, Jiawen Yang

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

Although many studies examine the relationship between the built environment and car ownership in large cities, few focus on smaller cities in developing countries. Their nonlinear and interaction relationships are often neglected. Using the 2019 data from Zhongshan, a medium-sized city in China, we employed gradient boosting decision trees to estimate the nonlinear and interaction effects of the built environment and motorcycles/E-bikes on car ownership. We found that wealth plays a crucial role in households’ car ownership decisions. Most built environment variables have threshold associations with car ownership, but the size of the associations is limited. The findings suggest that polycentricity and densification around centers help mitigate the growth of cars. More importantly, motorcycles and E-bikes, particularly owning a second one, attenuate the positive effects of income and/or distance to city center on car ownership. This challenges the policies of banning motorcycles and E-bikes.

Original languageEnglish (US)
Article number103115
JournalTransportation Research Part D: Transport and Environment
Volume102
DOIs
StatePublished - Jan 2022

Bibliographical note

Funding Information:
This study was supported by the Natural Science Foundation of China (41801158, 42171201), the Shenzhen Municipal Natural Science Foundation (Key Project) (GXWD20201231165807007-20200810223326001), and the Shenzhen Municipal Natural Science Foundation (JCYJ20190808173611341).

Publisher Copyright:
© 2021 Elsevier Ltd

Keywords

  • Auto ownership
  • Gradient boosting decision trees (GBDT)
  • Medium-sized city
  • Motorcycle and E-bike ban
  • Threshold effect

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