IDEAS home Printed from https://ideas.repec.org/a/eee/transa/v178y2023ics0965856423002987.html
   My bibliography  Save this article

Shared e-scooter service providers with large fleet size have a competitive advantage: Findings from e-scooter demand and supply analysis of Nashville, Tennessee

Author

Listed:
  • Shah, Nitesh R.
  • Ziedan, Abubakr
  • Brakewood, Candace
  • Cherry, Christopher R.

Abstract

Shared e-scooter systems are one of the fastest-growing micromobility modes in the United States. In response to service providers’ rapid deployment of e-scooter vehicles, several city governments have regulated shared e-scooters through permits and pilot programs, including the number of service providers, their fleet size, and provisions for expanding/downsizing the fleet size. However, the literature lacks an empirical analysis of the demand elasticity of shared e-scooters. We used a Poisson fixed effects regression to evaluate the demand elasticity of e-scooter vehicle deployment using the Shared Urban Mobility Device (SUMD) dataset from Nashville, Tennessee, between March 1, 2019 and February 2020. This dataset included disaggregated e-scooter trip summary data and vehicle location data that updates approximately every five minutes. We also estimated land-use specific demand elasticity of e-scooter vehicle deployment by clustering Traffic Analysis Zones (TAZs) using the K-means algorithm. We found that the average daily demand elasticity of e-scooter vehicle deployment is inelastic (0.64). Service providers with large fleet sizes (>500 average daily e-scooters) have a demand elasticity of e-scooter deployment that is 1.8 times higher than that of medium fleet-sized service providers (250–500 average daily e-scooters). Fleet size is likely correlated to service provider-specific attributes such as vendor popularity, brand loyalty, and rideshare services. We also found a significant difference in demand elasticity of e-scooter deployment for land use types, with university and park & waterfront land uses having the highest elasticity values. These findings could be helpful for city governments to identify the optimal number of service providers and fleet sizes to permit so that demand is fulfilled without an oversupply of e-scooter vehicles in public spaces.

Suggested Citation

  • Shah, Nitesh R. & Ziedan, Abubakr & Brakewood, Candace & Cherry, Christopher R., 2023. "Shared e-scooter service providers with large fleet size have a competitive advantage: Findings from e-scooter demand and supply analysis of Nashville, Tennessee," Transportation Research Part A: Policy and Practice, Elsevier, vol. 178(C).
    • Handle: RePEc:eee:transa:v:178:y:2023:i:c:s0965856423002987
    DOI: 10.1016/j.tra.2023.103878
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0965856423002987
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.tra.2023.103878?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Wooldridge, Jeffrey M., 1999. "Distribution-free estimation of some nonlinear panel data models," Journal of Econometrics, Elsevier, vol. 90(1), pages 77-97, May.
    2. Mehzabin Tuli, Farzana & Mitra, Suman & Crews, Mariah B., 2021. "Factors influencing the usage of shared E-scooters in Chicago," Transportation Research Part A: Policy and Practice, Elsevier, vol. 154(C), pages 164-185.
    3. Berrebi, Simon J. & Joshi, Sanskruti & Watkins, Kari E., 2021. "On bus ridership and frequency," Transportation Research Part A: Policy and Practice, Elsevier, vol. 148(C), pages 140-154.
    4. Boeing, Geoff, 2017. "OSMnx: New Methods for Acquiring, Constructing, Analyzing, and Visualizing Complex Street Networks," SocArXiv q86sd, Center for Open Science.
    5. Reinhardt, Karl & Deakin, Elizabeth SM., J.D., 2020. "Best Practices for the Public Management of Electric Scooters," Institute of Transportation Studies, Research Reports, Working Papers, Proceedings qt8x67x360, Institute of Transportation Studies, UC Berkeley.
    6. Ziedan, Abubakr & Darling, Wesley & Brakewood, Candace & Erhardt, Greg & Watkins, Kari, 2021. "The impacts of shared e-scooters on bus ridership," Transportation Research Part A: Policy and Practice, Elsevier, vol. 153(C), pages 20-34.
    7. McKenzie, Grant, 2019. "Spatiotemporal comparative analysis of scooter-share and bike-share usage patterns in Washington, D.C," Journal of Transport Geography, Elsevier, vol. 78(C), pages 19-28.
    8. Shaheen, Susan PhD & Cohen, Adam, 2019. "Shared Micromoblity Policy Toolkit: Docked and Dockless Bike and Scooter Sharing," Institute of Transportation Studies, Research Reports, Working Papers, Proceedings qt00k897b5, Institute of Transportation Studies, UC Berkeley.
    9. Guzman, Luis A. & Beltran, Carlos & Bonilla, Jorge & Gomez Cardona, Santiago, 2021. "BRT fare elasticities from smartcard data: Spatial and time-of-the-day differences," Transportation Research Part A: Policy and Practice, Elsevier, vol. 150(C), pages 335-348.
    10. Hosseinzadeh, Aryan & Algomaiah, Majeed & Kluger, Robert & Li, Zhixia, 2021. "Spatial analysis of shared e-scooter trips," Journal of Transport Geography, Elsevier, vol. 92(C).
    11. Button, Kenneth & Frye, Hailey & Reaves, David, 2020. "Economic regulation and E-scooter networks in the USA," Research in Transportation Economics, Elsevier, vol. 84(C).
    12. Hélie Moreau & Loïc de Jamblinne de Meux & Vanessa Zeller & Pierre D’Ans & Coline Ruwet & Wouter M.J. Achten, 2020. "Dockless E-Scooter: A Green Solution for Mobility? Comparative Case Study between Dockless E-Scooters, Displaced Transport, and Personal E-Scooters," Sustainability, MDPI, vol. 12(5), pages 1-17, February.
    13. Adriana Gabriela ALEXANDRU & Irina Miruna RADU & Madalina - Lavinia BIZON, 2018. "Big Data in Healthcare - Opportunities and Challenges," Informatica Economica, Academy of Economic Studies - Bucharest, Romania, vol. 22(2), pages 43-54.
    14. Aarhaug, Jørgen & Fearnley, Nils & Hartveit, Knut Johannes Liland & Johnsson, Espen, 2023. "Price and competition in emerging shared e-scooter markets," Research in Transportation Economics, Elsevier, vol. 98(C).
    15. Younes, Hannah & Zou, Zhenpeng & Wu, Jiahui & Baiocchi, Giovanni, 2020. "Comparing the Temporal Determinants of Dockless Scooter-share and Station-based Bike-share in Washington, D.C," Transportation Research Part A: Policy and Practice, Elsevier, vol. 134(C), pages 308-320.
    16. Huo, Jinghai & Yang, Hongtai & Li, Chaojing & Zheng, Rong & Yang, Linchuan & Wen, Yi, 2021. "Influence of the built environment on E-scooter sharing ridership: A tale of five cities," Journal of Transport Geography, Elsevier, vol. 93(C).
    17. 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.
    18. Shah, Nitesh R. & Guo, Jing & Han, Lee D. & Cherry, Christopher R., 2023. "Why do people take e-scooter trips? Insights on temporal and spatial usage patterns of detailed trip data," Transportation Research Part A: Policy and Practice, Elsevier, vol. 173(C).
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Krauss, Konstantin & Gnann, Till & Burgert, Tobias & Axhausen, Kay W., 2024. "Faster, greener, scooter? An assessment of shared e-scooter usage based on real-world driving data," Transportation Research Part A: Policy and Practice, Elsevier, vol. 181(C).
    2. Abouelela, Mohamed & Chaniotakis, Emmanouil & Antoniou, Constantinos, 2023. "Understanding the landscape of shared-e-scooters in North America; Spatiotemporal analysis and policy insights," Transportation Research Part A: Policy and Practice, Elsevier, vol. 169(C).
    3. 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.
    4. Mehzabin Tuli, Farzana & Mitra, Suman & Crews, Mariah B., 2021. "Factors influencing the usage of shared E-scooters in Chicago," Transportation Research Part A: Policy and Practice, Elsevier, vol. 154(C), pages 164-185.
    5. Jin, Scarlett T. & Wang, Lei & Sui, Daniel, 2023. "How the built environment affects E-scooter sharing link flows: A machine learning approach," Journal of Transport Geography, Elsevier, vol. 112(C).
    6. Huo, Jinghai & Yang, Hongtai & Li, Chaojing & Zheng, Rong & Yang, Linchuan & Wen, Yi, 2021. "Influence of the built environment on E-scooter sharing ridership: A tale of five cities," Journal of Transport Geography, Elsevier, vol. 93(C).
    7. 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.
    8. Kimpton, Anthony & Loginova, Julia & Pojani, Dorina & Bean, Richard & Sigler, Thomas & Corcoran, Jonathan, 2022. "Weather to scoot? How weather shapes shared e-scooter ridership patterns," Journal of Transport Geography, Elsevier, vol. 104(C).
    9. 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.
    10. Draženko Glavić & Marina Milenković & Aleksandar Trifunović & Igor Jokanović & Jelica Komarica, 2023. "Influence of Dockless Shared E-Scooters on Urban Mobility: WTP and Modal Shift," Sustainability, MDPI, vol. 15(12), pages 1-17, June.
    11. Yin, Zehui & Rybarczyk, Greg & Zheng, Anran & Su, Lin & Sun, Bingrong & Yan, Xiang, 2024. "Shared micromobility as a first- and last-mile transit solution? Spatiotemporal insights from a novel dataset," Journal of Transport Geography, Elsevier, vol. 114(C).
    12. Tyndall, Justin, 2022. "Complementarity of dockless mircomobility and rail transit," Journal of Transport Geography, Elsevier, vol. 103(C).
    13. Samira Dibaj & Aryan Hosseinzadeh & Miloš N. Mladenović & Robert Kluger, 2021. "Where Have Shared E-Scooters Taken Us So Far? A Review of Mobility Patterns, Usage Frequency, and Personas," Sustainability, MDPI, vol. 13(21), pages 1-27, October.
    14. Alberica Domitilla Bozzi & Anne Aguilera, 2021. "Shared E-Scooters: A Review of Uses, Health and Environmental Impacts, and Policy Implications of a New Micro-Mobility Service," Sustainability, MDPI, vol. 13(16), pages 1-17, August.
    15. Monika Hamerska & Monika Ziółko & Patryk Stawiarski, 2022. "A Sustainable Transport System—The MMQUAL Model of Shared Micromobility Service Quality Assessment," Sustainability, MDPI, vol. 14(7), pages 1-18, March.
    16. 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).
    17. Foissaud, Nicolas & Gioldasis, Christos & Tamura, Shun & Christoforou, Zoi & Farhi, Nadir, 2022. "Free-floating e-scooter usage in urban areas: A spatiotemporal analysis," Journal of Transport Geography, Elsevier, vol. 100(C).
    18. Yang, Hongtai & Zheng, Rong & Li, Xuan & Huo, Jinghai & Yang, Linchuan & Zhu, Tong, 2022. "Nonlinear and threshold effects of the built environment on e-scooter sharing ridership," Journal of Transport Geography, Elsevier, vol. 104(C).
    19. Shah, Nitesh R. & Guo, Jing & Han, Lee D. & Cherry, Christopher R., 2023. "Why do people take e-scooter trips? Insights on temporal and spatial usage patterns of detailed trip data," Transportation Research Part A: Policy and Practice, Elsevier, vol. 173(C).
    20. Liu, Hung-Chi & Lin, Jen-Jia, 2022. "Associations of built environments with spatiotemporal patterns of shared scooter use: A comparison with shared bike use," Transport Policy, Elsevier, vol. 126(C), pages 107-119.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:transa:v:178:y:2023:i:c:s0965856423002987. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/547/description#description .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.