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An empirical Bayes approach to quantifying the impact of transportation network companies (TNCs) operations on travel demand

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  • Choi, Yunkyung
  • Guhathakurta, Subhrajit
  • Pande, Anurag

Abstract

Assessing the impacts of new and disruptive technologies on the transportation system is crucial for planners and policymakers. This study offers an innovative method for estimating the impact of transportation network company (TNC, e.g., Uber and Lyft) operations on travel demand. Among various measures of travel demand, vehicle‐miles traveled (VMT) is tested due to its broad applications in evaluating changes in transportation policy. The evaluation is based on counterfactual theory, which compares VMT estimates after the TNCs introduction to a region to what the VMT would have been without the TNCs. The latter of the two is a counterfactual, and this study develops and demonstrates the empirical Bayes (EB) approach for obtaining counterfactual VMT estimates. The EB approach is widely used to estimate crash frequency after a particular traffic safety treatment is applied to a roadway location. We reinterpret the traffic safety treatment as being akin to the introduction of TNCs in the Atlanta region and the estimation of crash frequency as analogous to the resulting change in VMT. Since the crash experience of a roadway site may be affected by several factors, like the VMT of a region, a robust counterfactual estimate is necessary for conducting a before-after study. A counterfactual VMT estimate is obtained by combining two VMT estimates from 1) the cross‐sectional analysis for Atlanta and its regional peers and 2) the time-series analysis based on the longitudinal trend from the Atlanta region. We measure the difference between the counterfactual VMT estimate and the reported VMT estimate as an indicator of TNC impact. We find that the VMT estimates in a counterfactual scenario without TNCs are lower than the actual VMT estimates between 2012 and 2018. We estimate that the TNCs may be accounting for extra 0.6 percent average annual growth in VMT. The findings may support future TNC-related planning and policymaking. We expect the approach to be useful in estimating the effects of other disruptions, such as connected and autonomous vehicles (CAVs) introduction and lasting impact of the pandemic, on VMT.

Suggested Citation

  • Choi, Yunkyung & Guhathakurta, Subhrajit & Pande, Anurag, 2022. "An empirical Bayes approach to quantifying the impact of transportation network companies (TNCs) operations on travel demand," Transportation Research Part A: Policy and Practice, Elsevier, vol. 161(C), pages 269-283.
    • Handle: RePEc:eee:transa:v:161:y:2022:i:c:p:269-283
    DOI: 10.1016/j.tra.2022.04.008
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    1. Mark R. Stevens, 2017. "Does Compact Development Make People Drive Less?," Journal of the American Planning Association, Taylor & Francis Journals, vol. 83(1), pages 7-18, January.
    2. Cohen, Adam & Shaheen, Susan PhD, 2018. "Planning for Shared Mobility," Institute of Transportation Studies, Research Reports, Working Papers, Proceedings qt0dk3h89p, Institute of Transportation Studies, UC Berkeley.
    3. Reid Ewing & Robert Cervero, 2010. "Travel and the Built Environment," Journal of the American Planning Association, Taylor & Francis Journals, vol. 76(3), pages 265-294.
    4. Golob, Thomas F., 2003. "Structural equation modeling for travel behavior research," Transportation Research Part B: Methodological, Elsevier, vol. 37(1), pages 1-25, January.
    5. Kelly J. Clifton, 2017. "Getting From Here to There: Comment on “Does Compact Development Make People Drive Less?”," Journal of the American Planning Association, Taylor & Francis Journals, vol. 83(2), pages 148-151, April.
    6. 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.
    7. Clewlow, Regina R. & Mishra, Gouri S., 2017. "Disruptive Transportation: The Adoption, Utilization, and Impacts of Ride-Hailing in the United States," Institute of Transportation Studies, Working Paper Series qt82w2z91j, Institute of Transportation Studies, UC Davis.
    8. Shaheen, Susan PhD & Cohen, Adam & Chan, Nelson & Bansal, Apaar, 2020. "Chapter 13 - Sharing strategies: carsharing, shared micromobility (bikesharing and scooter sharing), transportation network companies, microtransit, and other innovative mobility modes," Institute of Transportation Studies, Research Reports, Working Papers, Proceedings qt0z9711dw, Institute of Transportation Studies, UC Berkeley.
    9. Malalgoda, Narendra & Lim, Siew Hoon, 2019. "Do transportation network companies reduce public transit use in the U.S.?," Transportation Research Part A: Policy and Practice, Elsevier, vol. 130(C), pages 351-372.
    10. Rodier, Caroline & Alemi, Farzad & Smith, Dylan, 2016. "Dynamic Ridesharing: Exploration of Potential for Reduction in Vehicle Miles Traveled," Institute of Transportation Studies, Working Paper Series qt6r6139g8, Institute of Transportation Studies, UC Davis.
    11. Agatz, Niels A.H. & Erera, Alan L. & Savelsbergh, Martin W.P. & Wang, Xing, 2011. "Dynamic ride-sharing: A simulation study in metro Atlanta," Transportation Research Part B: Methodological, Elsevier, vol. 45(9), pages 1450-1464.
    12. Mark R. Stevens, 2017. "Response to Commentaries on “Does Compact Development Make People Drive Less?”," Journal of the American Planning Association, Taylor & Francis Journals, vol. 83(2), pages 151-158, April.
    13. Alejandro Henao & Wesley E. Marshall, 2019. "The impact of ride-hailing on vehicle miles traveled," Transportation, Springer, vol. 46(6), pages 2173-2194, December.
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