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Exploring the spatial variations of transfer distances between dockless bike-sharing systems and metros

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  • Li, Wenxiang
  • Chen, Shawen
  • Dong, Jieshuang
  • Wu, Jingxian

Abstract

Dockless bike-sharing is emerging as a convenient transfer mode for metros. The riding distances of bike-sharing to or from metro stations are defined as transfer distances between dockless bike-sharing systems and metros, which determine the service coverages of metro stations. However, the transfer distances have rarely been studied and they may vary from station to station. Therefore, this study aims to explore the influencing factors and spatial variations of transfer distances between dockless bike-sharing systems and metros. First, a catchment method was proposed to identify bike-sharing transfer trips. Then, the Mobike trip data, metro smartcard data, and built environment data in Shanghai were utilized to calculate the transfer distances and travel-related and built environment variables. Next, a multicollinearity test, stepwise regression, and spatial autocorrelation test were conducted to select the best explanatory variables. Finally, a geographically weighted regression model was adopted to examine the spatially varying relationships between the 85th percentile transfer distances and selected explanatory variables at different metro stations. The results show that the transfer distances are correlated with the daily metro ridership, daily bike-sharing ridership, population density, parking lot density, footway density, percentage of tourism attraction, distance from CBD, and bus stop density around metro stations. Besides, the effects of the explanatory variables on transfer distances vary across space. Generally, most variables have greater effects on transfer distances in the city suburbs. This study can help governments and operators expand the service coverage of metro stations and facilitate the integration of dockless bike-sharing and metros.

Suggested Citation

  • Li, Wenxiang & Chen, Shawen & Dong, Jieshuang & Wu, Jingxian, 2021. "Exploring the spatial variations of transfer distances between dockless bike-sharing systems and metros," Journal of Transport Geography, Elsevier, vol. 92(C).
    • Handle: RePEc:eee:jotrge:v:92:y:2021:i:c:s0966692321000855
    DOI: 10.1016/j.jtrangeo.2021.103032
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    References listed on IDEAS

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    3. Wu, Xueying & Lu, Yi & Gong, Yongxi & Kang, Yuhao & Yang, Linchuan & Gou, Zhonghua, 2021. "The impacts of the built environment on bicycle-metro transfer trips: A new method to delineate metro catchment area based on people's actual cycling space," Journal of Transport Geography, Elsevier, vol. 97(C).
    4. Hu, Songhua & Chen, Mingyang & Jiang, Yuan & Sun, Wei & Xiong, Chenfeng, 2022. "Examining factors associated with bike-and-ride (BnR) activities around metro stations in large-scale dockless bikesharing systems," Journal of Transport Geography, Elsevier, vol. 98(C).
    5. Zhitao Li & Yuzhen Shang & Guanwei Zhao & Muzhuang Yang, 2022. "Exploring the Multiscale Relationship between the Built Environment and the Metro-Oriented Dockless Bike-Sharing Usage," IJERPH, MDPI, vol. 19(4), pages 1-21, February.
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    9. Bi, Hui & Li, Aoyong & Hua, Mingzhuang & Zhu, He & Ye, Zhirui, 2022. "Examining the varying influences of built environment on bike-sharing commuting: Empirical evidence from Shanghai," Transport Policy, Elsevier, vol. 129(C), pages 51-65.
    10. Pan Wu & Jinlong Li & Yuzhuang Pian & Xiaochen Li & Zilin Huang & Lunhui Xu & Guilin Li & Ruonan Li, 2022. "How Determinants Affect Transfer Ridership between Metro and Bus Systems: A Multivariate Generalized Poisson Regression Analysis Method," Sustainability, MDPI, vol. 14(15), pages 1-31, August.

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