2020
Liu, Y.; Ji, Y.; Feng, T.; Timmermans, H.
Understanding the determinants of young commuters’ metro-bikeshare usage frequency using big data Journal Article
In: Travel Behaviour and Society, vol. 21, 2020, ISSN: 2214367X.
Abstract | Links | BibTeX | Tags: Metro-bikeshare integration, Negative binomial regression, Smart card data, Transfer frequency, Young commuter
@article{Liu2020,
title = {Understanding the determinants of young commuters’ metro-bikeshare usage frequency using big data},
author = {Y. Liu and Y. Ji and T. Feng and H. Timmermans},
doi = {10.1016/j.tbs.2020.06.007},
issn = {2214367X},
year = {2020},
date = {2020-01-01},
journal = {Travel Behaviour and Society},
volume = {21},
abstract = {This paper examines the determinants of young commuters’ frequency of using public bikes as a feeder mode to/from metro. Using three-week metro- and public bike- smart card data from Nanjing, 1,154 metro-bikeshare commuters aged 18–35 were extracted. As possible factors influencing the use of the combined mode, individual and household socio-demographics, travel-related attributes and built environment characteristics were extracted from multi-source data. A negative binomial regression model was used to examine the effects of these factors on usage frequency. We found that young commuters are the biggest group using metro-bikeshare system. They use public bikes frequently to transfer to/from metro when the cycling time is less than 10 min and the transfer happens during the morning peak. Built environment characteristics also influence usage frequencies, with high-density bike facilities being related to higher cycling rates in inner areas, and residential /employment locations related to lower rates of cycling in the core areas. This suggests that different measures and policies designed to encourage the integrated use of metro-bikeshare should be put forward for different regions.},
keywords = {Metro-bikeshare integration, Negative binomial regression, Smart card data, Transfer frequency, Young commuter},
pubstate = {published},
tppubtype = {article}
}
This paper examines the determinants of young commuters’ frequency of using public bikes as a feeder mode to/from metro. Using three-week metro- and public bike- smart card data from Nanjing, 1,154 metro-bikeshare commuters aged 18–35 were extracted. As possible factors influencing the use of the combined mode, individual and household socio-demographics, travel-related attributes and built environment characteristics were extracted from multi-source data. A negative binomial regression model was used to examine the effects of these factors on usage frequency. We found that young commuters are the biggest group using metro-bikeshare system. They use public bikes frequently to transfer to/from metro when the cycling time is less than 10 min and the transfer happens during the morning peak. Built environment characteristics also influence usage frequencies, with high-density bike facilities being related to higher cycling rates in inner areas, and residential /employment locations related to lower rates of cycling in the core areas. This suggests that different measures and policies designed to encourage the integrated use of metro-bikeshare should be put forward for different regions.