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Uber service area expansion in three major American cities

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  • Gehrke, Steven R.

Abstract

Chiefly led by Uber, on-demand ride-hailing services have transformed the urban American transportation landscape in merely the past decade. Utilizing the proliferation of internet-enabled smartphones, this app-based company has provided city inhabitants with a convenient and reliable door-to-door mobility service, which has arguably improved car-based accessibility while also generating a host of negative environmental and societal externalities. While to date the utilization of Uber has largely been an urban phenomenon, the lasting success of this new mobility option likely rests within its ability to expand its services into suburban communities. Yet, given the competitive nature of the ride-hailing marketplace and genuine concerns over passenger and driver anonymity, transportation planners and urban policymakers have been stymied in their ability to access the disaggregate data sets needed to help assess whether these services are in fact extending beyond city centers and identify which factors may be contributing to any expansion into more peripheral suburban neighborhoods. By introducing a creative strategy using the privacy-related suppression processes of Uber Movement data, this study quantifies the continued expansion of Uber's ride-hailing service into outlying communities from 2016 to 2018 by employing a multilevel modeling approach to recognize the neighborhood-level socioeconomic and built environment factors most related to this service expansion in three major American cities: Boston, San Francisco, and Washington, DC.

Suggested Citation

  • Gehrke, Steven R., 2020. "Uber service area expansion in three major American cities," Journal of Transport Geography, Elsevier, vol. 86(C).
    • Handle: RePEc:eee:jotrge:v:86:y:2020:i:c:s0966692319310713
    DOI: 10.1016/j.jtrangeo.2020.102752
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    References listed on IDEAS

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    Cited by:

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    3. Steven R. Gehrke & Michael P. Huff, 2024. "Spatial equity implications and neighborhood indicators of ridehailing trip frequency and vehicle miles traveled in the phoenix metro region," Transportation, Springer, vol. 51(1), pages 271-295, February.
    4. Kłos, Marcin Jacek & Sierpiński, Grzegorz, 2023. "Siting of electric vehicle charging stations method addressing area potential and increasing their accessibility," Journal of Transport Geography, Elsevier, vol. 109(C).
    5. Misra, Aditi & Shirgaokar, Manish & Weinstein Agrawal, Asha & Dobbs, Bonnie & Wachs, Martin, 2022. "How older adults use Ride-hailing booking technology in California," Transportation Research Part A: Policy and Practice, Elsevier, vol. 155(C), pages 11-30.
    6. Barajas, Jesus M. & Brown, Anne, 2021. "Not minding the gap: Does ride-hailing serve transit deserts?," Journal of Transport Geography, Elsevier, vol. 90(C).
    7. Brown, Anne, 2021. "Not All Fees are Created Equal: Equity Implications of Ride-hail Fee Structures," OSF Preprints cpsqu, Center for Open Science.
    8. Wang, Zhiqi & Zhang, Yufeng & Jia, Bin & Gao, Ziyou, 2024. "Comparative Analysis of Usage Patterns and Underlying Determinants for Ride-hailing and Traditional Taxi Services: A Chicago Case Study," Transportation Research Part A: Policy and Practice, Elsevier, vol. 179(C).
    9. 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).

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