IDEAS home Printed from https://ideas.repec.org/a/kap/transp/v52y2025i2d10.1007_s11116-023-10425-w.html
   My bibliography  Save this article

What stay-at-home orders reveal about dependence on transportation network companies

Author

Listed:
  • Lily Hanig

    (Carnegie Mellon University)

  • Destenie Nock

    (Carnegie Mellon University
    Carnegie Mellon University)

  • Corey D. Harper

    (Carnegie Mellon University
    Carnegie Mellon University)

Abstract

Transportation Network Companies (TNC) such as Uber and Lyft set out to provide transportation not fulfilled by private vehicles or public transit. The social value of TNCs for essential trips (i.e., necessary trips that cannot be fulfilled by another mode of transportation) is difficult to discern in normal conditions. The COVID-19 stay-at-home order is used as a natural experiment to investigate the heterogeneous ability to avoid TNCs by income areas of trip origins. We measure the sensitivity of different populations’ ability to respond to policies and to avoid TNC trips (e.g., early stay-at-home orders) using a difference-in-difference style regression. Previous studies have indicated that under normal conditions TNCs primarily serve high-income areas, indicating that TNCs may not be improving transportation equity but instead serve as an additional mode of transportation for passengers with multiple options. We fill a gap in the literature by evaluating the role TNCs play in serving unavoidable and essential trips. We find that high-income community areas showed greater sensitivity to the stay-at-home order with a 56% greater decrease in TNC ridership during the stay-at-home order compared to low-income community areas. Specifically, TNC trips from high-income areas decreased by 80%. This indicates that although riders from high-income community areas might make up the majority of trips in normal conditions, low-income community areas are less able to adapt to stay-at-home orders because of a higher degree of non-flexible and essential jobs or less access to TNC alternatives like private vehicles and public transit.

Suggested Citation

  • Lily Hanig & Destenie Nock & Corey D. Harper, 2025. "What stay-at-home orders reveal about dependence on transportation network companies," Transportation, Springer, vol. 52(2), pages 381-412, April.
  • Handle: RePEc:kap:transp:v:52:y:2025:i:2:d:10.1007_s11116-023-10425-w
    DOI: 10.1007/s11116-023-10425-w
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11116-023-10425-w
    File Function: Abstract
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1007/s11116-023-10425-w?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

    for a different version of it.

    References listed on IDEAS

    as
    1. Li, Sen & Tavafoghi, Hamidreza & Poolla, Kameshwar & Varaiya, Pravin, 2019. "Regulating TNCs: Should Uber and Lyft set their own rules?," Transportation Research Part B: Methodological, Elsevier, vol. 129(C), pages 193-225.
    2. Rebecca Brough & Matthew Freedman & David C. Phillips, 2021. "Understanding socioeconomic disparities in travel behavior during the COVID‐19 pandemic," Journal of Regional Science, Wiley Blackwell, vol. 61(4), pages 753-774, September.
    3. Mi Diao & Hui Kong & Jinhua Zhao, 2021. "Impacts of transportation network companies on urban mobility," Nature Sustainability, Nature, vol. 4(6), pages 494-500, June.
    4. Rick Grahn & Corey D. Harper & Chris Hendrickson & Zhen Qian & H. Scott Matthews, 2020. "Socioeconomic and usage characteristics of transportation network company (TNC) riders," Transportation, Springer, vol. 47(6), pages 3047-3067, December.
    5. Nelson Erik & Sadowsky Nicole, 2019. "Estimating the Impact of Ride-Hailing App Company Entry on Public Transportation Use in Major US Urban Areas," The B.E. Journal of Economic Analysis & Policy, De Gruyter, vol. 19(1), pages 1-21, January.
    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).
    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. Soria, Jason & Stathopoulos, Amanda, 2021. "Investigating socio-spatial differences between solo ridehailing and pooled rides in diverse communities," Journal of Transport Geography, Elsevier, vol. 95(C).
    2. Ke, Jintao & Li, Xinwei & Yang, Hai & Yin, Yafeng, 2021. "Pareto-efficient solutions and regulations of congested ride-sourcing markets with heterogeneous demand and supply," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 154(C).
    3. Yuan Liang & Bingjie Yu & Xiaojian Zhang & Yi Lu & Linchuan Yang, 2022. "The Short-term Impact of Congestion Taxes on Ridesourcing Demand and Traffic Congestion: Evidence from Chicago," Papers 2207.01793, arXiv.org, revised Feb 2023.
    4. Zhang, Kenan & Nie, Yu (Marco), 2022. "Mitigating traffic congestion induced by transportation network companies: A policy analysis," Transportation Research Part A: Policy and Practice, Elsevier, vol. 159(C), pages 96-118.
    5. Huang, Guan & Liang, Yuebing & Zhao, Zhan, 2023. "Understanding market competition between transportation network companies using big data," Transportation Research Part A: Policy and Practice, Elsevier, vol. 178(C).
    6. Adam Millard-Ball & Liwei Liu & Whitney Hansen & Drew Cooper & Joe Castiglione, 2023. "Where ridehail drivers go between trips," Transportation, Springer, vol. 50(5), pages 1959-1981, October.
    7. Yiyuan Wang & Qing Shen, 2024. "A latent class analysis to understand riders’ adoption of on-demand mobility services as a complement to transit," Transportation, Springer, vol. 51(3), pages 1043-1061, June.
    8. Khatun, Farzana & Saphores, Jean-Daniel, 2023. "Covid-19, intentions to change modes, and how they materialized - Results from a random survey of Californians," Transportation Research Part A: Policy and Practice, Elsevier, vol. 178(C).
    9. Li, Xinwei & Ke, Jintao & Yang, Hai & Wang, Hai & Zhou, Yaqian, 2024. "An aggregate matching and pick-up model for mobility-on-demand services," Transportation Research Part B: Methodological, Elsevier, vol. 190(C).
    10. Meredith-Karam, Patrick & Kong, Hui & Wang, Shenhao & Zhao, Jinhua, 2021. "The relationship between ridehailing and public transit in Chicago: A comparison before and after COVID-19," Journal of Transport Geography, Elsevier, vol. 97(C).
    11. Loa, Patrick & Hossain, Sanjana & Liu, Yicong & Nurul Habib, Khandker, 2022. "How has the COVID-19 pandemic affected the use of ride-sourcing services? An empirical evidence-based investigation for the Greater Toronto Area," Transportation Research Part A: Policy and Practice, Elsevier, vol. 155(C), pages 46-62.
    12. Liang, Yuan & Yu, Bingjie & Zhang, Xiaojian & Lu, Yi & Yang, Linchuan, 2023. "The short-term impact of congestion taxes on ridesourcing demand and traffic congestion: Evidence from Chicago," Transportation Research Part A: Policy and Practice, Elsevier, vol. 172(C).
    13. García-Herrera, Alisson & Basso, Leonardo J. & Tirachini, Alejandro, 2024. "Microeconomic analysis of ridesourcing market regulation policies," Transportation Research Part A: Policy and Practice, Elsevier, vol. 186(C).
    14. Lou, Jiehong & Shen, Xingchi & Niemeier, Deb, 2020. "Are stay-at-home orders more difficult to follow for low-income groups?," Journal of Transport Geography, Elsevier, vol. 89(C).
    15. Wang, Senlei & Correia, Gonçalo Homem de Almeida & Lin, Hai Xiang, 2022. "Modeling the competition between multiple Automated Mobility on-Demand operators: An agent-based approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 605(C).
    16. Alipour, Jean-Victor & Fadinger, Harald & Schymik, Jan, 2021. "My home is my castle – The benefits of working from home during a pandemic crisis," Journal of Public Economics, Elsevier, vol. 196(C).
    17. Zhong, Yuanguang & Lan, Yibo & Chen, Zhi & Yang, Jiazi, 2023. "On-demand ride-hailing platforms with heterogeneous quality-sensitive customers: Dedicated system or pooling system?," Transportation Research Part B: Methodological, Elsevier, vol. 173(C), pages 247-266.
    18. Kwan Ok Lee & Hyojung Lee, 2022. "Public responses to COVID‐19 case disclosure and their spatial implications," Journal of Regional Science, Wiley Blackwell, vol. 62(3), pages 732-756, June.
    19. Sen Li & Kameshwar Poolla & Pravin Varaiya, 2020. "Impact of Congestion Charge and Minimum Wage on TNCs: A Case Study for San Francisco," Papers 2003.02550, arXiv.org, revised Feb 2021.
    20. André de Palma & Lucas Javaudin & Patrick Stokkink & Léandre Tarpin-Pitre, 2021. "Modelling Ridesharing in a Large Network with Dynamic Congestion," THEMA Working Papers 2021-16, THEMA (THéorie Economique, Modélisation et Applications), Université de Cergy-Pontoise.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    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:kap:transp:v:52:y:2025:i:2:d:10.1007_s11116-023-10425-w. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.