The newly prevailing dockless bike-sharing system offers a decent solution to the first- and last-mile problem and connects trip origins/destinations and transit (mostly metro) stations. Few studies, however, have explored the effects of built environment characteristics on the integrated usage of dockless bike-sharing and the metro, especially in different conditions (e.g., access versus egress and morning peak versus evening peak) and using panel data. To fill the gap, this study proposes a people–metro–bike–route–urban space framework to describe the feeder-related built environment from the perspective of the feeder process. Using 3-day data of ofo bikes in Shenzhen, China, this study then develops multilevel negative binomial models that incorporate random effects and address the intracluster correlation attributed to repeated measures to scrutinize the feeder-related built environment effects on the integrated usage. The findings are listed as follows: (1) The majority of access and egress integrated trips have a distance range of 500–2000 m and a duration range of 2.5–10 min; (2) Popular metro stations (with a large ridership) are positively related to the access integrated usage; (3) The number of available shared bikes and the length of bikeway in the catchment areas of the metro are positively related to the integrated usage; and (4) Mixed land use increases the integrated usage, whereas urban villages are places with few demands for the integrated usage. These findings are beneficial in developing a bike-friendly built environment that facilitates the seamless connection between dockless bike-sharing and the metro.
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