Examining the effects of the built environment on topological properties of the bike-sharing network in Suzhou, China

Chunliang Wu, Hyungchul Chung, Zhiyuan Liu, Inhi Kim

Research output: Contribution to journalArticleResearchpeer-review

1 Citation (Scopus)

Abstract

In recent years, many cities around the world have implemented bike-sharing programs. A number of studies on the relationship between the built environment and bike usage have provided important insights into understanding bike-sharing systems. However, the effects of the built environment on the structural properties of bike-sharing networks are seldom discussed in the literature. This research proposes a novel and interdisciplinary framework to explore how built environment factors affect the topological properties of bike-sharing networks. Firstly, this research applies a complex network approach to quantify the importance of bike stations in the network. Then, multisource data are utilized to identify comprehensive built environment attributes. Finally, spatial regression models are used to reveal the relationship between the importance of bike stations and built environment. In this study, the bike-sharing system in Suzhou, China, is taken as a case study. The empirical result shows that the importance of bike stations displays strong spatial dependence. Also, built environment attributes such as resident population, accessibility to subway stations, the capacity of bike stations, and the total length of main roads within a catchment area have different effects on the importance of bike stations. It should be noted that the floating population and the number of bus stops surrounding bike stations do not have strong correlations with the importance of bike stations. The findings of this study can guide urban planners and operators to improve the service quality and resilience of bike-sharing systems.

Original languageEnglish
Pages (from-to)338-350
Number of pages13
JournalInternational Journal of Sustainable Transportation
Volume15
Issue number5
DOIs
Publication statusPublished - 2021

Keywords

  • bike-sharing network
  • built environment
  • complex network
  • spatial regression model

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