The spatially varying effects of built environment characteristics on the integrated usage of dockless bike-sharing and public transport

The dockless bike-sharing (DBS) system offers a flexible feeder mode for connecting to public transport. Using multi-source big data, this study employs a multi-scale geographically weighted regression to analyze the effects of built environment characteristics on the integrated usage of DBS and public transport. Different modes of public transport (i.e., bus and subway) are further considered to explore these effects by defining two scenarios in Beijing, namely the bike-bus scenario and the bike-subway scenario. The results show that the number of points of interest around public transport stations (e.g., education and culture places, leisure services, and residential and accommodation services), length of main road, and length of cycle path significantly affect the integrated usage in the two scenarios. However, population density, number of workplaces, and number of shopping and eating places only play a vital role in the integrated DBS and bus system. Access to bus stops significantly impacts the integration of DBS and the subway. In addition, the effects of these built environment characteristics on the integrated usage are diverse in different areas. These findings can be utilized to create a bike-friendly envi-ronment to encourage a connection between DBS and public transport.

Automated summary

Using multi-source big data, this study analyzed the effects of built environment characteristics on the integrated usage of dockless bike-sharing (DBS) and public transport. The results showed that factors such as points of interest around public transport stations, length of main road, and length of cycle path significantly influenced the integrated usage. However, the impact of these factors varied in different areas. These findings can be used to create a bike-friendly environment and encourage the connection between DBS and public transport.