Exploring the impacts of built environment on bike-sharing trips on weekends: The case of Guangzhou

Abstract

Shared mobility has brought many disruptive changes to urban transportation systems all over the world. Shared bikes have proven to be among the most successful and influential travel tools in attempting to alleviate the last-mile problem – the difficulty in getting people from transportation stations to their final destinations. This study aims to investigate the impacts of built environment factors on bike-sharing trips. Although many studies have explored these impacts, most have focused on the impacts of urban function, and have paid insufficient attention to the cycling environment. This study used multi-source data, including street view images (SVIs), points of interest (POIs), digital elevation models (DEMs), and road networks, to fully identify the influences of the built environment from five dimensions. The multiscale geographically weighted regression (MGWR) method was used to investigate the impacts of the urban built environment on bike-sharing usage. The results found that high-density roads, recreational POIs, and residential POIs all had positive impacts on the volume of bike-sharing trips in residential areas on weekends, whereas urban greenness negatively impacts bike-sharing usage in parks, because of strict regulations promulgated by local governments. Moreover, the impacts of high-density street networks and residential communities had strong spatial non-stationarity, while the influences of other built environment factors, including road gradient, eye-level greenness, and urban function mixture, were demonstrated spatial stationarity. These findings can facilitate local governments’ and enterprises’ efforts to improve the cycling environment and ensure the efficient management of shared bikes.

Keywords:

• bikes-sharing trips
• built environment
• multiscale geographically weighted regression
• street view images

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

The research is supported by the [National Natural Science Foundation of China] under Grant [42271206]; [Guangdong Basic and Applied Basic Research Foundation] under Grant [2021A1515011073]. The authors declare no conflict of interest.This work was also supported by Guangdong Office of Philosophy and Social Science.