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Forecasting e-scooter substitution of direct and access trips by mode and distance

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  • Mina Lee
  • Joseph Y. J. Chow
  • Gyugeun Yoon
  • Brian Yueshuai He

Abstract

An e-scooter trip model is estimated from four U.S. cities: Portland, Austin, Chicago and New York City. A log-log regression model is estimated for e-scooter trips based on user age, population, land area, and the number of scooters. The model predicts 75K daily e-scooter trips in Manhattan for a deployment of 2000 scooters, which translates to 77 million USD in annual revenue. We propose a novel nonlinear, multifactor model to break down the number of daily trips by the alternative modes of transportation that they would likely substitute based on statistical similarity. The model parameters reveal a relationship with direct trips of bike, walk, carpool, automobile and taxi as well as access/egress trips with public transit in Manhattan. Our model estimates that e-scooters could replace 32% of carpool; 13% of bike; and 7.2% of taxi trips. The distance structure of revenue from access/egress trips is found to differ from that of other substituted trips.

Suggested Citation

  • Mina Lee & Joseph Y. J. Chow & Gyugeun Yoon & Brian Yueshuai He, 2019. "Forecasting e-scooter substitution of direct and access trips by mode and distance," Papers 1908.08127, arXiv.org, revised Apr 2021.
    • Handle: RePEc:arx:papers:1908.08127
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    References listed on IDEAS

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    Cited by:

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    2. Yunus Emre Ayözen, 2023. "Statistical Optimization of E-Scooter Micro-Mobility Utilization in Postal Service," Energies, MDPI, vol. 16(3), pages 1-25, January.
    3. Ouassim Manout & Azise Oumar Diallo & Thibault Gloriot, 2023. "Implications of pricing and fleet size strategies on shared bikes and e-scooters: a case study from Lyon, France," Working Papers hal-04017908, HAL.
    4. 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).
    5. Shiva Pourfalatoun & Jubaer Ahmed & Erika E. Miller, 2023. "Shared Electric Scooter Users and Non-Users: Perceptions on Safety, Adoption and Risk," Sustainability, MDPI, vol. 15(11), pages 1-15, June.
    6. Jurgis Zagorskas & Marija Burinskienė, 2019. "Challenges Caused by Increased Use of E-Powered Personal Mobility Vehicles in European Cities," Sustainability, MDPI, vol. 12(1), pages 1-13, December.
    7. Marco Diana & Andrea Chicco, 2023. "The effect of COVID restriction levels on shared micromobility travel patterns: A comparison between dockless bike sharing and e-scooter services," Papers 2309.16440, arXiv.org.
    8. Alexandra König & Laura Gebhardt & Kerstin Stark & Julia Schuppan, 2022. "A Multi-Perspective Assessment of the Introduction of E-Scooter Sharing in Germany," Sustainability, MDPI, vol. 14(5), pages 1-16, February.
    9. Li, Qiumeng & Fuerst, Franz & Luca, Davide, 2023. "Do shared E-bikes reduce urban carbon emissions?," LSE Research Online Documents on Economics 120310, London School of Economics and Political Science, LSE Library.
    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. Rickie Mae Gaspar & Yogi Tri Prasetyo & Klint Allen Mariñas & Satria Fadil Persada & Reny Nadlifatin, 2023. "Exploring Consumers’ Intention to Use Bikes and E-Scooters during the COVID-19 Pandemic in the Philippines: An Extended Theory of Planned Behavior Approach with a Consideration of Pro-Environmental Id," Sustainability, MDPI, vol. 15(6), pages 1-16, March.

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