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Discovering spatiotemporal usage patterns of a bike-sharing system by type of pass: a case study from Seoul

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  • Kyoungok Kim

    (Seoul National University of Science and Technology (SeoulTech))

Abstract

Determining bike-sharing usage patterns and their explanatory factors on demand is essential for the effective and efficient operation of bike-sharing systems (BSSs). Most BSSs provide different passes that vary with the period of use. However, studies investigating the differences in usage patterns are rare compared to studies conducted at the system level, even though explanatory factors depending on the type of pass may cause different characteristics in terms of usage patterns. This study explores the differences in the usage patterns of BSSs and the impact of explanatory factors on the demand depending on the type of pass. Various machine learning techniques, including clustering, regression, and classification, are used, in addition to basic statistical analysis. As observed, long-term season passes of over six months are mainly used for transportation (especially commuting), whereas one-day or short-term season passes seem to be used more for leisure than for other purposes. Furthermore, differences in the purpose of bike rentals seem to cause differences in usage patterns and variations in demand over time and space. This study improves ther understanding of the usage patterns that appear differently for each pass type, and provides insights into the efficient operation of BSSs in urban areas.

Suggested Citation

  • Kyoungok Kim, 2024. "Discovering spatiotemporal usage patterns of a bike-sharing system by type of pass: a case study from Seoul," Transportation, Springer, vol. 51(4), pages 1373-1407, August.
    • Handle: RePEc:kap:transp:v:51:y:2024:i:4:d:10.1007_s11116-023-10371-7
    DOI: 10.1007/s11116-023-10371-7
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    References listed on IDEAS

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    1. Schuijbroek, J. & Hampshire, R.C. & van Hoeve, W.-J., 2017. "Inventory rebalancing and vehicle routing in bike sharing systems," European Journal of Operational Research, Elsevier, vol. 257(3), pages 992-1004.
    2. Faghih-Imani, Ahmadreza & Hampshire, Robert & Marla, Lavanya & Eluru, Naveen, 2017. "An empirical analysis of bike sharing usage and rebalancing: Evidence from Barcelona and Seville," Transportation Research Part A: Policy and Practice, Elsevier, vol. 97(C), pages 177-191.
    3. Raux, Charles & Zoubir, Ayman & Geyik, Mirkan, 2017. "Who are bike sharing schemes members and do they travel differently? The case of Lyon’s “Velo’v” scheme," Transportation Research Part A: Policy and Practice, Elsevier, vol. 106(C), pages 350-363.
    4. Böcker, Lars & Anderson, Ellinor & Uteng, Tanu Priya & Throndsen, Torstein, 2020. "Bike sharing use in conjunction to public transport: Exploring spatiotemporal, age and gender dimensions in Oslo, Norway," Transportation Research Part A: Policy and Practice, Elsevier, vol. 138(C), pages 389-401.
    5. Zhang, Yongping & Mi, Zhifu, 2018. "Environmental benefits of bike sharing: A big data-based analysis," Applied Energy, Elsevier, vol. 220(C), pages 296-301.
    6. Faghih-Imani, Ahmadreza & Eluru, Naveen, 2016. "Incorporating the impact of spatio-temporal interactions on bicycle sharing system demand: A case study of New York CitiBike system," Journal of Transport Geography, Elsevier, vol. 54(C), pages 218-227.
    7. Wang, Mingshu & Zhou, Xiaolu, 2017. "Bike-sharing systems and congestion: Evidence from US cities," Journal of Transport Geography, Elsevier, vol. 65(C), pages 147-154.
    8. Ma, Xinwei & Ji, Yanjie & Yang, Mingyuan & Jin, Yuchuan & Tan, Xu, 2018. "Understanding bikeshare mode as a feeder to metro by isolating metro-bikeshare transfers from smart card data," Transport Policy, Elsevier, vol. 71(C), pages 57-69.
    9. Xiaolu Zhou, 2015. "Understanding Spatiotemporal Patterns of Biking Behavior by Analyzing Massive Bike Sharing Data in Chicago," PLOS ONE, Public Library of Science, vol. 10(10), pages 1-20, October.
    10. Kim, Kyoungok, 2018. "Investigation on the effects of weather and calendar events on bike-sharing according to the trip patterns of bike rentals of stations," Journal of Transport Geography, Elsevier, vol. 66(C), pages 309-320.
    11. Rachel Aldred & James Woodcock & Anna Goodman, 2016. "Does More Cycling Mean More Diversity in Cycling?," Transport Reviews, Taylor & Francis Journals, vol. 36(1), pages 28-44, January.
    12. Faghih-Imani, Ahmadreza & Eluru, Naveen & El-Geneidy, Ahmed M. & Rabbat, Michael & Haq, Usama, 2014. "How land-use and urban form impact bicycle flows: evidence from the bicycle-sharing system (BIXI) in Montreal," Journal of Transport Geography, Elsevier, vol. 41(C), pages 306-314.
    13. Xing, Yingying & Wang, Ke & Lu, Jian John, 2020. "Exploring travel patterns and trip purposes of dockless bike-sharing by analyzing massive bike-sharing data in Shanghai, China," Journal of Transport Geography, Elsevier, vol. 87(C).
    14. Guidon, Sergio & Reck, Daniel J. & Axhausen, Kay, 2020. "Expanding a(n) (electric) bicycle-sharing system to a new city: Prediction of demand with spatial regression and random forests," Journal of Transport Geography, Elsevier, vol. 84(C).
    15. Hu, Songhua & Xiong, Chenfeng & Liu, Zhanqin & Zhang, Lei, 2021. "Examining spatiotemporal changing patterns of bike-sharing usage during COVID-19 pandemic," Journal of Transport Geography, Elsevier, vol. 91(C).
    16. Wafic El-Assi & Mohamed Salah Mahmoud & Khandker Nurul Habib, 2017. "Effects of built environment and weather on bike sharing demand: a station level analysis of commercial bike sharing in Toronto," Transportation, Springer, vol. 44(3), pages 589-613, May.
    17. Elliot Fishman & Simon Washington & Narelle Haworth, 2013. "Bike Share: A Synthesis of the Literature," Transport Reviews, Taylor & Francis Journals, vol. 33(2), pages 148-165, March.
    18. Jie Bao & Chengcheng Xu & Pan Liu & Wei Wang, 2017. "Exploring Bikesharing Travel Patterns and Trip Purposes Using Smart Card Data and Online Point of Interests," Networks and Spatial Economics, Springer, vol. 17(4), pages 1231-1253, December.
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