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Effects of dockless bike-sharing systems on the usage of the London Cycle Hire

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  • Li, Haojie
  • Zhang, Yingheng
  • Ding, Hongliang
  • Ren, Gang

Abstract

This paper evaluates the effects of dockless bike-sharing systems on the usage of the London Cycle Hire (LCH). A total number of 707 LCH docking stations are included for a period of 36 weeks. Covariates such as socio-demographic characteristics, traffic conditions, and the built environment are included in the data set. A difference in difference (DID) based propensity score matching (PSM) method is applied to select control docking stations and estimate the effects of the dockless bike-sharing systems on the LCH usage. The results suggest that a significant reduction of 22.42 (5.93%) in the average weekly usage of each LCH docking station is caused by the dockless bike-sharing system after its initial launch. We also investigate the effects of dockless bike-sharing systems on the characteristics of the LCH trips, including travel duration, travel distance, and departure time. The majority of trips replaced by the dockless bikes are short duration (0–15 min) and middle distance (1–3 km) trips. The reduction in the average weekly short duration trips of each station is 16.91 (7.16%), while the figure is 15.11 (6.74%) for middle distance trips. The average travel duration is increased by 0.25 min, but the travel distance shows no significant change due to data restriction. Furthermore, the LCH usage is significantly reduced by 6.85% during the weekday commuting peak, and 10.47% during the weekend leisure peak. As to weekday off-peak and other times, reductions are not statistically significant.

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  • Li, Haojie & Zhang, Yingheng & Ding, Hongliang & Ren, Gang, 2019. "Effects of dockless bike-sharing systems on the usage of the London Cycle Hire," Transportation Research Part A: Policy and Practice, Elsevier, vol. 130(C), pages 398-411.
    • Handle: RePEc:eee:transa:v:130:y:2019:i:c:p:398-411
    DOI: 10.1016/j.tra.2019.09.050
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    9. Ma, Xinwei & Ji, Yanjie & Yuan, Yufei & Van Oort, Niels & Jin, Yuchuan & Hoogendoorn, Serge, 2020. "A comparison in travel patterns and determinants of user demand between docked and dockless bike-sharing systems using multi-sourced data," Transportation Research Part A: Policy and Practice, Elsevier, vol. 139(C), pages 148-173.
    10. Raafat Aburukba & A. R. Al-Ali & Ahmed H. Riaz & Ahmad Al Nabulsi & Danayal Khan & Shavaiz Khan & Moustafa Amer, 2021. "Fog Computing Approach for Shared Mobility in Smart Cities," Energies, MDPI, vol. 14(23), pages 1-19, December.
    11. Bi, Hui & Gao, Hui & Li, Aoyong & Ye, Zhirui, 2024. "Investigation on the joint travel behavior in bike sharing systems during the COVID-19 pandemic: Insights from New York City," Journal of Transport Geography, Elsevier, vol. 117(C).
    12. Yang, Hongtai & Huo, Jinghai & Bao, Yongxing & Li, Xuan & Yang, Linchuan & Cherry, Christopher R., 2021. "Impact of e-scooter sharing on bike sharing in Chicago," Transportation Research Part A: Policy and Practice, Elsevier, vol. 154(C), pages 23-36.
    13. Chang, Ximing & Wu, Jianjun & Sun, Huijun & Correia, Gonçalo Homem de Almeida & Chen, Jianhua, 2021. "Relocating operational and damaged bikes in free-floating systems: A data-driven modeling framework for level of service enhancement," Transportation Research Part A: Policy and Practice, Elsevier, vol. 153(C), pages 235-260.
    14. Cheng, Long & Huang, Jie & Jin, Tanhua & Chen, Wendong & Li, Aoyong & Witlox, Frank, 2023. "Comparison of station-based and free-floating bikeshare systems as feeder modes to the metro," Journal of Transport Geography, Elsevier, vol. 107(C).
    15. Ding, Hongliang & Lu, Yuhuan & Sze, N.N. & Li, Haojie, 2022. "Effect of dockless bike-sharing scheme on the demand for London Cycle Hire at the disaggregate level using a deep learning approach," Transportation Research Part A: Policy and Practice, Elsevier, vol. 166(C), pages 150-163.
    16. Zhang, Yingheng & Li, Haojie & Ren, Gang, 2022. "Quantifying the social impacts of the London Night Tube with a double/debiased machine learning based difference-in-differences approach," Transportation Research Part A: Policy and Practice, Elsevier, vol. 163(C), pages 288-303.
    17. Dongdong Feng & Lin Cheng & Mingyang Du, 2020. "Exploring the Impact of Dockless Bikeshare on Docked Bikeshare—A Case Study in London," Sustainability, MDPI, vol. 12(15), pages 1-18, July.
    18. Ma, Xinwei & Zhang, Shuai & Wu, Tao & Yang, Yizhe & Yu, Jiajie, 2023. "Can dockless and docked bike-sharing substitute each other? Evidence from Nanjing, China," Renewable and Sustainable Energy Reviews, Elsevier, vol. 188(C).
    19. Morton, Craig & Kelley, Scott & Monsuur, Fredrik & Hui, Tianwen, 2021. "A spatial analysis of demand patterns on a bicycle sharing scheme: Evidence from London," Journal of Transport Geography, Elsevier, vol. 94(C).
    20. Lovelace, Robin & Beecham, Roger & Heinen, Eva & Vidal Tortosa, Eugeni & Yang, Yuanxuan & Slade, Chris & Roberts, Antonia, 2020. "Is the London Cycle Hire Scheme becoming more inclusive? An evaluation of the shifting spatial distribution of uptake based on 70 million trips," Transportation Research Part A: Policy and Practice, Elsevier, vol. 140(C), pages 1-15.
    21. Si, Hongyun & Su, Yangyue & Wu, Guangdong & Liu, Bingsheng & Zhao, Xianbo, 2020. "Understanding bike-sharing users’ willingness to participate in repairing damaged bicycles: Evidence from China," Transportation Research Part A: Policy and Practice, Elsevier, vol. 141(C), pages 203-220.

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