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Are drivers cool with pool? Driver attitudes towards the shared TNC services UberPool and Lyft Shared

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Listed:
  • Morris, Eric A.
  • Zhou, Ying
  • Brown, Anne E.
  • Khan, Sakib M.
  • Derochers, John L.
  • Campbell, Harry
  • Pratt, Angela N.
  • Chowdhury, Mashrur

Abstract

The transportation network companies (TNCs) Uber and Lyft have introduced shared ride services, called “UberPool” and “Lyft Shared,” which use real-time cyber-connectivity to match travelers with similar origins and destinations so they can share discounted rides. It is hoped this will reduce the amount of vehicle miles traveled that TNCs are adding to the roads. However, previous evidence suggests that drivers and passengers have some dissatisfaction with these services. This paper uses a survey of 309 TNC drivers to examine the driver experience with providing shared rides. We find that in the aggregate drivers are considerably less satisfied with providing shared trips compared to solo trips with services such as UberX and Lyft Classic. There are a number of sources of dissatisfaction. Although some feel shared services add to their earnings, more drivers perceive their compensation for shared rides to be unfair. Further, although drivers sometimes enjoy the social interactions that Pool and Shared generate, many drivers complain that customers are often unhappy due to issues like trips taking longer than expected and friction between passengers. Finally, drivers feel serving shared trips is difficult and stressful work, due to things like routing and pick-up instructions that sometimes seem irrational and change frequently, difficult pick-ups and drop-offs, and long trips. We offer suggestions for improving driver satisfaction with Pool/Shared by raising and restructuring driver compensation, better publicizing the ways in which Pool/Shared increase driver incomes, increasing ridership through means such as better advertising of shared services and raising the price of solo travel, improving the information given to drivers, incentivizing good passenger behavior, and improving the passenger experience.

Suggested Citation

  • Morris, Eric A. & Zhou, Ying & Brown, Anne E. & Khan, Sakib M. & Derochers, John L. & Campbell, Harry & Pratt, Angela N. & Chowdhury, Mashrur, 2020. "Are drivers cool with pool? Driver attitudes towards the shared TNC services UberPool and Lyft Shared," Transport Policy, Elsevier, vol. 94(C), pages 123-138.
  • Handle: RePEc:eee:trapol:v:94:y:2020:i:c:p:123-138
    DOI: 10.1016/j.tranpol.2020.04.019
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    References listed on IDEAS

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    1. M. Keith Chen & Judith A. Chevalier & Peter E. Rossi & Emily Oehlsen, 2019. "The Value of Flexible Work: Evidence from Uber Drivers," Journal of Political Economy, University of Chicago Press, vol. 127(6), pages 2735-2794.
    2. Bharat Chandar & Uri Gneezy & John List & Ian Muir, 2019. "The Drivers of Social Preferences: Evidence from a Nationwide Tipping Field Experiment," Natural Field Experiments 00680, The Field Experiments Website.
    3. 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.
    4. Rayle, Lisa & Dai, Danielle & Chan, Nelson & Cervero, Robert & Shaheen, Susan PhD, 2016. "Just A Better Taxi? A Survey-Based Comparison of Taxis, Transit, and Ridesourcing Services in San Francisco," Institute of Transportation Studies, Research Reports, Working Papers, Proceedings qt60v8r346, Institute of Transportation Studies, UC Berkeley.
    5. 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.
    6. Furnham, Adrian & Boo, Hua Chu, 2011. "A literature review of the anchoring effect," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 40(1), pages 35-42, February.
    7. Hall, Jonathan D. & Palsson, Craig & Price, Joseph, 2018. "Is Uber a substitute or complement for public transit?," Journal of Urban Economics, Elsevier, vol. 108(C), pages 36-50.
    8. Rayle, Lisa & Dai, Danielle & Chan, Nelson & Cervero, Robert & Shaheen, Susan, 2016. "Just a better taxi? A survey-based comparison of taxis, transit, and ridesourcing services in San Francisco," Transport Policy, Elsevier, vol. 45(C), pages 168-178.
    9. Henao, Alejandro & Marshall, Wesley E., 2019. "An analysis of the individual economics of ride-hailing drivers," Transportation Research Part A: Policy and Practice, Elsevier, vol. 130(C), pages 440-451.
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    Cited by:

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    2. Chandiran, P. & Ramasubramaniam, M. & Venkatesh, V.G. & Mani, Venkatesh & Shi, Yangyan, 2023. "Can driver supply disruption alleviate driver shortages? A systems approach," Transport Policy, Elsevier, vol. 130(C), pages 116-129.

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