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Micromobility evolution and expansion: Understanding how docked and dockless bikesharing models complement and compete – A case study of San Francisco

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  • Lazarus, Jessica
  • Pourquier, Jean Carpentier
  • Feng, Frank
  • Hammel, Henry
  • Shaheen, Susan

Abstract

Shared micromobility – the shared use of bicycles, scooters, or other low-speed modes – is an innovative transportation strategy growing across the United States that includes various service models such as docked, dockless, and e-bike service models. This research focuses on understanding how docked bikesharing and dockless e-bikesharing models complement and compete with respect to user travel behaviors. To inform our analysis, we used two datasets from February 2018 of Ford GoBike (docked) and JUMP (dockless electric) bikesharing trips in San Francisco. We employed three methodological approaches: 1) travel behavior analysis, 2) discrete choice analysis with a destination choice model, and 3) geospatial suitability analysis based on the Spatial Temporal Economic Physiological Social (STEPS) to Transportation Equity framework. We found that dockless e-bikesharing trips were longer in distance and duration than docked trips. The average JUMP trip was about a third longer in distance and about twice as long in duration than the average GoBike trip. JUMP users were far less sensitive to estimated total elevation gain than were GoBike users, making trips with total elevation gain about three times larger than those of GoBike users, on average. The JUMP system achieved greater usage rates than GoBike, with 0.8 more daily trips per bike and 2.3 more miles traveled on each bike per day, on average. The destination choice model results suggest that JUMP users traveled to lower-density destinations, and GoBike users were largely traveling to dense employment areas. Bike rack density was a significant positive factor for JUMP users. The location of GoBike docking stations may attract users and/or be well-placed to the destination preferences of users. The STEPS-based bikeability analysis revealed opportunities for the expansion of both bikesharing systems in areas of the city where high-job density and bike facility availability converge with older resident populations.

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  • 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).
    • Handle: RePEc:eee:jotrge:v:84:y:2020:i:c:s0966692319302510
    DOI: 10.1016/j.jtrangeo.2019.102620
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    2. 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.
    3. Shahram Heydari & Garyfallos Konstantinoudis & Abdul Wahid Behsoodi, 2021. "Effect of the COVID-19 pandemic on bike-sharing demand and hire time: Evidence from Santander Cycles in London," Papers 2107.11589, arXiv.org.
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    5. Daniela Arias-Molinares & Juan Carlos García-Palomares & Gustavo Romanillos & Javier Gutiérrez, 2023. "Uncovering spatiotemporal micromobility patterns through the lens of space–time cubes and GIS tools," Journal of Geographical Systems, Springer, vol. 25(3), pages 403-427, July.
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    9. Morteza Hossein Sabbaghian & David Llopis-Castelló & Alfredo García, 2023. "A Safe Infrastructure for Micromobility: The Current State of Knowledge," Sustainability, MDPI, vol. 15(13), pages 1-20, June.
    10. Post, Alison PhD & Ratan, Ishana & Hill, Mary & Huang, Amy & Soga, Kenichi PhD & Zhao, Bingyu PhD, 2021. "Benchmarking “Smart City” Technology Adoption in California: An Innovative Web Platform for Exploring New Data and Tracking Adoption," Institute of Transportation Studies, Research Reports, Working Papers, Proceedings qt5mt4m51n, Institute of Transportation Studies, UC Berkeley.
    11. Namkung, Ok Stella & Park, Jonghan & Ko, Joonho, 2023. "Public bike users’ annual travel distance: Findings from combined data of user survey and annual rental records," Transportation Research Part A: Policy and Practice, Elsevier, vol. 170(C).
    12. Fei-Hui Huang, 2021. "User Behavioral Intentions toward a Scooter-Sharing Service: An Empirical Study," Sustainability, MDPI, vol. 13(23), pages 1-21, November.
    13. Cheng, Long & Yang, Junjian & Chen, Xuewu & Cao, Mengqiu & Zhou, Hang & Sun, Yu, 2020. "How could the station-based bike sharing system and the free-floating bike sharing system be coordinated?," Journal of Transport Geography, Elsevier, vol. 89(C).
    14. Nigro, Marialisa & Castiglione, Marisdea & Maria Colasanti, Fabio & De Vincentis, Rosita & Valenti, Gaetano & Liberto, Carlo & Comi, Antonio, 2022. "Exploiting floating car data to derive the shifting potential to electric micromobility," Transportation Research Part A: Policy and Practice, Elsevier, vol. 157(C), pages 78-93.
    15. Bach, Xavier & Marquet, Oriol & Miralles-Guasch, Carme, 2023. "Assessing social and spatial access equity in regulatory frameworks for moped-style scooter sharing services," Transport Policy, Elsevier, vol. 132(C), pages 154-162.
    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. Meng, Si'an & Brown, Anne, 2021. "Docked vs. dockless equity: Comparing three micromobility service geographies," Journal of Transport Geography, Elsevier, vol. 96(C).
    18. Zhang, Yunchang & Fricker, Jon D., 2021. "Quantifying the impact of COVID-19 on non-motorized transportation: A Bayesian structural time series model," Transport Policy, Elsevier, vol. 103(C), pages 11-20.
    19. Sobrino, Natalia & Gonzalez, Juan Nicolas & Vassallo, Jose Manuel & Baeza, Maria de los Angeles, 2023. "Regulation of shared electric kick scooters in urban areas: Key drivers from expert stakeholders," Transport Policy, Elsevier, vol. 134(C), pages 1-18.
    20. 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).
    21. Samadzad, Mahdi & Nosratzadeh, Hossein & Karami, Hossein & Karami, Ali, 2023. "What are the factors affecting the adoption and use of electric scooter sharing systems from the end user's perspective?," Transport Policy, Elsevier, vol. 136(C), pages 70-82.
    22. Maximilian Heumann & Tobias Kraschewski & Tim Brauner & Lukas Tilch & Michael H. Breitner, 2021. "A Spatiotemporal Study and Location-Specific Trip Pattern Categorization of Shared E-Scooter Usage," Sustainability, MDPI, vol. 13(22), pages 1-24, November.
    23. Hosseinzadeh, Aryan & Algomaiah, Majeed & Kluger, Robert & Li, Zhixia, 2021. "Spatial analysis of shared e-scooter trips," Journal of Transport Geography, Elsevier, vol. 92(C).
    24. Steve O’Hern & Nora Estgfaeller, 2020. "A Scientometric Review of Powered Micromobility," Sustainability, MDPI, vol. 12(22), pages 1-21, November.
    25. Riggs, William & Kawashima, Matt & Batstone, David, 2021. "Exploring best practice for municipal e-scooter policy in the United States," Transportation Research Part A: Policy and Practice, Elsevier, vol. 151(C), pages 18-27.

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