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

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  • 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
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    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. 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.
    3. Hosseinzadeh, Aryan & Algomaiah, Majeed & Kluger, Robert & Li, Zhixia, 2021. "Spatial analysis of shared e-scooter trips," Journal of Transport Geography, Elsevier, vol. 92(C).
    4. Button, Kenneth & Frye, Hailey & Reaves, David, 2020. "Economic regulation and E-scooter networks in the USA," Research in Transportation Economics, Elsevier, vol. 84(C).
    5. 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.
    6. 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.
    7. Boeing, Geoff, 2017. "OSMnx: New Methods for Acquiring, Constructing, Analyzing, and Visualizing Complex Street Networks," SocArXiv q86sd, Center for Open Science.
    8. 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.
    9. 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.
    10. 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.
    11. 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.
    12. 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.
    13. 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).
    14. 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.
    15. 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.
    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).
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