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Spatiotemporal Characteristics of Bike-Sharing Usage around Rail Transit Stations: Evidence from Beijing, China

Author

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  • Zijia Wang

    (School of Civil Engineering, Beijing Jiaotong University, Beijing 100044, China)

  • Lei Cheng

    (School of Civil Engineering, Beijing Jiaotong University, Beijing 100044, China)

  • Yongxing Li

    (School of Civil and Environmental Engineering, Nanyang Technological University, 50 Nanyang Avenue, Singapore 639798, Singapore)

  • Zhiqiang Li

    (School of Civil Engineering, Beijing Jiaotong University, Beijing 100044, China)

Abstract

As an emerging mode of transport, bike-sharing is being quickly accepted by Chinese residents due to its convenience and environmental friendliness. As hotspots for bike-sharing, railway-station service areas attract thousands of bikes during peak hours, which can block roads and pedestrian walkways. Of the many works devoted to the connection between bikes and rail, few have addressed the spatial‒temporal pattern of bike-sharing accumulating around station service areas. In this work, we investigate the distribution patterns of bike-sharing in station service areas, which are influenced not only by railway-station ridership but also by the built environment around the station, illustrating obvious spatial heterogeneity. To this end, we established a geographic weighted regression (GWR) model to capture this feature considering the variables of passenger flow and the built environment. Using the data from bike-sharing in Beijing, China, we applied the GWR model to carry out a spatiotemporal characteristic analysis of the relationship between bike-sharing usage in railway-station service areas and its determinants, including the passenger flow in stations, land use, bus lines, and road-network characteristics. The influence of these factors on bike-sharing usage is quite different in time and space. For instance, bus lines are a competing mode of transport with bike-sharing in suburban areas but not in city centers, whereas industrial and residential areas could also heavily affect the bike-sharing demand as well as railway-station ridership. The results of this work can help facilitate the dynamic allocation of bike-sharing and increase the efficiency of this emerging mode of transport.

Suggested Citation

  • Zijia Wang & Lei Cheng & Yongxing Li & Zhiqiang Li, 2020. "Spatiotemporal Characteristics of Bike-Sharing Usage around Rail Transit Stations: Evidence from Beijing, China," Sustainability, MDPI, vol. 12(4), pages 1-19, February.
    • Handle: RePEc:gam:jsusta:v:12:y:2020:i:4:p:1299-:d:319056
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    References listed on IDEAS

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    Cited by:

    1. Kumar Dey, Bibhas & Anowar, Sabreena & Eluru, Naveen, 2021. "A framework for estimating bikeshare origin destination flows using a multiple discrete continuous system," Transportation Research Part A: Policy and Practice, Elsevier, vol. 144(C), pages 119-133.
    2. Zhan, Zilin & Guo, Yuanyuan & Noland, Robert B. & He, Sylvia Y. & Wang, Yacan, 2023. "Analysis of links between dockless bikeshare and metro trips in Beijing," Transportation Research Part A: Policy and Practice, Elsevier, vol. 175(C).
    3. 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).
    4. Tomasz Bieliński & Łukasz Dopierała & Maciej Tarkowski & Agnieszka Ważna, 2020. "Lessons from Implementing a Metropolitan Electric Bike Sharing System," Energies, MDPI, vol. 13(23), pages 1-21, November.
    5. Andreas Piter & Philipp Otto & Hamza Alkhatib, 2022. "The Helsinki bike‐sharing system—Insights gained from a spatiotemporal functional model," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 185(3), pages 1294-1318, July.
    6. Nikolaos-Fivos Galatoulas & Konstantinos N. Genikomsakis & Christos S. Ioakimidis, 2020. "Spatio-Temporal Trends of E-Bike Sharing System Deployment: A Review in Europe, North America and Asia," Sustainability, MDPI, vol. 12(11), pages 1-17, June.

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