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Socioeconomic and usage characteristics of transportation network company (TNC) riders

Author

Listed:
  • Rick Grahn

    (Carnegie Mellon University)

  • Corey D. Harper

    (Booz Allen Hamilton)

  • Chris Hendrickson

    (Carnegie Mellon University)

  • Zhen Qian

    (Carnegie Mellon University)

  • H. Scott Matthews

    (Carnegie Mellon University)

Abstract

The widespread adoption of smartphones followed by an emergence of transportation network companies (TNC) have influenced the way individuals travel. The authors use the 2017 National Household Travel Survey to explore socioeconomic, frequency of use, and spatial characteristics associated with TNC users. The results indicate that TNC riders tend to be younger, earn higher incomes, have higher levels of education, and are more likely to reside in urban areas compared to the aggregate United States population. Of the TNC users, 60% hailed a ride three times or less in the previous month, indicating that TNC services are primarily used for special occasions. TNC users use public transit at higher rates and own fewer vehicles compared to the aggregate United States population. In fact, the TNC user population reported similar frequencies of use for both TNC services and public transit during the previous month. Approximately 40% of TNC users reside in regions with population densities greater than 10, 000 persons per square mile compared to only 15% for non-TNC users. Lastly, reported use of public transit for TNC users living in large cities (> 1 million) with access to heavy rail was almost three times greater when compared to similar sized cities without heavy rail. The average monthly frequency of TNC use was also elevated when heavy rail was present.

Suggested Citation

  • 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.
  • Handle: RePEc:kap:transp:v:47:y:2020:i:6:d:10.1007_s11116-019-09989-3
    DOI: 10.1007/s11116-019-09989-3
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    References listed on IDEAS

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    1. Felipe F. Dias & Patrícia S. Lavieri & Venu M. Garikapati & Sebastian Astroza & Ram M. Pendyala & Chandra R. Bhat, 2017. "A behavioral choice model of the use of car-sharing and ride-sourcing services," Transportation, Springer, vol. 44(6), pages 1307-1323, November.
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    Cited by:

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    4. Post, Alison PhD & Ratan, Ishana & Hill, Mary & Huang, Amy & Soga, Kenichi PhD & Zhao, Bingyu PhD, 2021. "Benchmarking “Smart City” Technology Adoption in California: An Innovative Web Platform for Exploring New Data and Tracking Adoption," Institute of Transportation Studies, Research Reports, Working Papers, Proceedings qt5mt4m51n, Institute of Transportation Studies, UC Berkeley.
    5. Rick Grahn & Sean Qian & Chris Hendrickson, 2023. "Optimizing first- and last-mile public transit services leveraging transportation network companies (TNC)," Transportation, Springer, vol. 50(5), pages 2049-2076, October.
    6. 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.
    7. Kumar, Akshay & Gupta, Akshay & Parida, Manoranjan & Chauhan, Vivek, 2022. "Service quality assessment of ride-sourcing services: A distinction between ride-hailing and ride-sharing services," Transport Policy, Elsevier, vol. 127(C), pages 61-79.
    8. Hasnine, Md Sami & Hawkins, Jason & Habib, Khandker Nurul, 2021. "Effects of built environment and weather on demands for transportation network company trips," Transportation Research Part A: Policy and Practice, Elsevier, vol. 150(C), pages 171-185.
    9. Zhang, Zhaolin & Zhai, Guocong & Xie, Kun & Xiao, Feng, 2022. "Exploring the nonlinear effects of ridesharing on public transit usage: A case study of San Diego," Journal of Transport Geography, Elsevier, vol. 104(C).
    10. Lee, Yongsung & Circella, Giovanni & Chen, Grace & Kim, Ilsu & Mokhtarian, Patricia L., 2024. "If Pooling with a Discount were Available for the Last Solo-Ridehailing Trip, How Much Additional Travel Time Would Users Have Accepted and for Which Types of Trips?," Institute of Transportation Studies, Working Paper Series qt1dc3v8ms, Institute of Transportation Studies, UC Davis.
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    12. 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.

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