Dockless bike sharing (DBS) advances the fast-growing bike sharing market and shows great potential for the revival of bicycle as a feeder mode for metro stations. The paper aims to examine built-environment factors that impact DBS transfer ridership. In this study, we analyze temporal distribution of DBS-metro integration based on the one-week trip data of Mobike in Beijing. The spatial lag models have been developed for DBS transfer ridership. The estimation results show that the high density of residences, offices and secondary roads is related to the high DBS transfer ridership. The density of public transit stations is found to have negative effects on DBS usage. Furthermore, there are some differences between to or from the metro stations during different time periods. The results can be used to optimize the bike infrastructure with high level of service, and rationalize bicycle rebalance to ensure the sustainable development of DBS.

CICTP