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Quantifying economic benefits from free-floating bike-sharing systems: A trip-level inference approach and city-scale analysis

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  • Gao, Kun
  • Yang, Ying
  • Li, Aoyong
  • Li, Junhong
  • Yu, Bo

Abstract

Despite many qualitative discussions about the benefits of free-floating bike-sharing systems (FFBS), high-resolution and quantitative assessments about the economic benefits of FFBS for users are absent. This study proposes an innovative trip-level inference approach for quantifying the economic benefits of FFBS, leveraging massive FFBS transaction data, the emerging multimodal routing Application Programming Interface from online navigators and travel choice modeling. The proposed approach is able to analyze the economic benefit for every single bike-sharing trip and investigate the spatiotemporal heterogeneity in the economic benefits from FFBS. An empirical analysis in Shanghai is conducted using the proposed approach. The estimated saved travel time, cost, and economic benefit due to using FFBS per trip are estimated to be 9.95 min, 3.64 CNY, and 8.68 CNY-eq, respectively. The annual saved travel time, cost, and economic benefits from FFBS in Shanghai are estimated to be 17.665 billion min, 6.463 billion CNY, and 15.410 billion CNY-eq, respectively. The relationships between economic benefits from FFBS and built environment factors in different urban contexts are quantitatively examined using Multiple Linear Regression to explain the spatial heterogeneity in the economic benefits of FFBS. The outcomes provide a useful tool for evaluating the benefits of shared mobility systems, insights into the users’ economic benefit from using FFBS from per-trip, aggregated and spatial perspective, as well as its influencing factors. The results could efficiently support the scientific planning, operation and policy making concerning FFBS in different urban contexts.

Suggested Citation

  • Gao, Kun & Yang, Ying & Li, Aoyong & Li, Junhong & Yu, Bo, 2021. "Quantifying economic benefits from free-floating bike-sharing systems: A trip-level inference approach and city-scale analysis," Transportation Research Part A: Policy and Practice, Elsevier, vol. 144(C), pages 89-103.
    • Handle: RePEc:eee:transa:v:144:y:2021:i:c:p:89-103
    DOI: 10.1016/j.tra.2020.12.009
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    1. Li, Aoyong & Zhao, Pengxiang & Huang, Yizhe & Gao, Kun & Axhausen, Kay W., 2020. "An empirical analysis of dockless bike-sharing utilization and its explanatory factors: Case study from Shanghai, China," Journal of Transport Geography, Elsevier, vol. 88(C).
    2. 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.
    3. Ma, Liang & Zhang, Xin & Ding, Xiaoyan & Wang, Gaoshan, 2018. "Bike sharing and users’ subjective well-being: An empirical study in China," Transportation Research Part A: Policy and Practice, Elsevier, vol. 118(C), pages 14-24.
    4. Lu-Yi Qiu & Ling-Yun He, 2018. "Bike Sharing and the Economy, the Environment, and Health-Related Externalities," Sustainability, MDPI, vol. 10(4), pages 1-10, April.
    5. Rose, John M. & Bliemer, Michiel C.J. & Hensher, David A. & Collins, Andrew T., 2008. "Designing efficient stated choice experiments in the presence of reference alternatives," Transportation Research Part B: Methodological, Elsevier, vol. 42(4), pages 395-406, May.
    6. Cherchi, Elisabetta & Ortúzar, Juan de Dios, 2006. "On fitting mode specific constants in the presence of new options in RP/SP models," Transportation Research Part A: Policy and Practice, Elsevier, vol. 40(1), pages 1-18, January.
    7. Greene, William H. & Hensher, David A. & Rose, John, 2006. "Accounting for heterogeneity in the variance of unobserved effects in mixed logit models," Transportation Research Part B: Methodological, Elsevier, vol. 40(1), pages 75-92, January.
    8. Lazarus, Jessica & Pourquier, Jean Carpentier & Feng, Frank & Hammel, Henry & Shaheen, Susan, 2020. "Micromobility evolution and expansion: Understanding how docked and dockless bikesharing models complement and compete – A case study of San Francisco," Journal of Transport Geography, Elsevier, vol. 84(C).
    9. Liu, Kang & Yin, Ling & Ma, Zhanwu & Zhang, Fan & Zhao, Juanjuan, 2020. "Investigating physical encounters of individuals in urban metro systems with large-scale smart card data," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 545(C).
    10. Lazarus, Jessica & Pourquier, Jean Carpentier & Feng, Frank & Hammel, Henry & Shaheen, Susan, 2020. "Micromobility evolution and expansion: Understanding how docked and dockless bikesharing models complement and compete – A case study of San Francisco," Institute of Transportation Studies, Research Reports, Working Papers, Proceedings qt96g9c9nd, Institute of Transportation Studies, UC Berkeley.
    11. Médard de Chardon, Cyrille, 2019. "The contradictions of bike-share benefits, purposes and outcomes," Transportation Research Part A: Policy and Practice, Elsevier, vol. 121(C), pages 401-419.
    12. David Hensher & William Greene, 2003. "The Mixed Logit model: The state of practice," Transportation, Springer, vol. 30(2), pages 133-176, May.
    13. Martin, Elliot W. & Shaheen, Susan A., 2014. "Evaluating public transit modal shift dynamics in response to bikesharing: a tale of two U.S. cities," Journal of Transport Geography, Elsevier, vol. 41(C), pages 315-324.
    14. Martin, Elliot PhD & Shaheen, Susan PhD, 2014. "Evaluating Public Transit Modal Shift Dynamics In Response to Bikesharing: A Tale of Two U.S. Cities," Institute of Transportation Studies, Research Reports, Working Papers, Proceedings qt6x29n876, Institute of Transportation Studies, UC Berkeley.
    15. Elisabetta Cherchi & Juan de Dios Ortúzar, 2011. "On the Use of Mixed RP/SP Models in Prediction: Accounting for Systematic and Random Taste Heterogeneity," Transportation Science, INFORMS, vol. 45(1), pages 98-108, February.
    16. 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.
    17. Zhang, Yongping & Mi, Zhifu, 2018. "Environmental benefits of bike sharing: A big data-based analysis," Applied Energy, Elsevier, vol. 220(C), pages 296-301.
    18. Abrantes, Pedro A.L. & Wardman, Mark R., 2011. "Meta-analysis of UK values of travel time: An update," Transportation Research Part A: Policy and Practice, Elsevier, vol. 45(1), pages 1-17, January.
    19. 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.
    20. Liu, Hung-Chi & Lin, Jen-Jia, 2019. "Associations of built environments with spatiotemporal patterns of public bicycle use," Journal of Transport Geography, Elsevier, vol. 74(C), pages 299-312.
    21. Wardman, Mark, 2004. "Public transport values of time," Transport Policy, Elsevier, vol. 11(4), pages 363-377, October.
    22. Chen, Zhiwei & Guo, Yujie & Stuart, Amy L. & Zhang, Yu & Li, Xiaopeng, 2019. "Exploring the equity performance of bike-sharing systems with disaggregated data: A story of southern Tampa," Transportation Research Part A: Policy and Practice, Elsevier, vol. 130(C), pages 529-545.
    23. Faghih-Imani, Ahmadreza & Anowar, Sabreena & Miller, Eric J. & Eluru, Naveen, 2017. "Hail a cab or ride a bike? A travel time comparison of taxi and bicycle-sharing systems in New York City," Transportation Research Part A: Policy and Practice, Elsevier, vol. 101(C), pages 11-21.
    24. Shaheen, Susan PhD & Martin, Elliot PhD & Cohen, Adam, 2013. "Public Bikesharing and Modal Shift Behavior: A Comparative Study of Early Bikesharing Systems in North America," Institute of Transportation Studies, Research Reports, Working Papers, Proceedings qt7010k9p3, Institute of Transportation Studies, UC Berkeley.
    25. Li, Aoyong & Huang, Yizhe & Axhausen, Kay W., 2020. "An approach to imputing destination activities for inclusion in measures of bicycle accessibility," Journal of Transport Geography, Elsevier, vol. 82(C).
    26. Zheyan Chen & Dea van Lierop & Dick Ettema, 2020. "Dockless bike-sharing systems: what are the implications?," Transport Reviews, Taylor & Francis Journals, vol. 40(3), pages 333-353, May.
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    6. Zhang, Yuhan & Shao, Yichang & Bi, Hui & Aoyong, Li & Ye, Zhirui, 2023. "Bike-sharing systems rebalancing considering redistribution proportions: A user-based repositioning approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 610(C).
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