IDEAS home Printed from https://ideas.repec.org/a/pal/buseco/v56y2021i4d10.1057_s11369-021-00237-0.html
   My bibliography  Save this article

Labor market outcomes under digital platform business models in the sharing economy: the case of the taxi services industry

Author

Listed:
  • Sanae Tashiro

    (Rhode Island College)

  • Stephen Choi

    (California State University Fresno)

Abstract

This research investigates the effects of ride-sharing online platforms on the taxi and limousine industry. It also compares and contrasts labor market outcomes between conventional taxi drivers and Uber drivers during the Covid-19 pandemic. The empirical study finds that Uber’s online platform has an inconsequential impact on labor supply and earnings among conventional taxi drivers. It suggests that taxi drivers under the traditional employment system behave differently from Uber drivers under an online business platform in the sharing economy, which is further construed by a standard theory that illustrates the operations of the sharing economy.

Suggested Citation

  • Sanae Tashiro & Stephen Choi, 2021. "Labor market outcomes under digital platform business models in the sharing economy: the case of the taxi services industry," Business Economics, Palgrave Macmillan;National Association for Business Economics, vol. 56(4), pages 240-251, October.
    • Handle: RePEc:pal:buseco:v:56:y:2021:i:4:d:10.1057_s11369-021-00237-0
    DOI: 10.1057/s11369-021-00237-0
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1057/s11369-021-00237-0
    File Function: Abstract
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1057/s11369-021-00237-0?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 search for a different version of it.

    References listed on IDEAS

    as
    1. Berger, Thor & Chen, Chinchih & Frey, Carl Benedikt, 2018. "Drivers of disruption? Estimating the Uber effect," European Economic Review, Elsevier, vol. 110(C), pages 197-210.
    2. Koszegi, Botond & Rabin, Matthew, 2004. "A Model of Reference-Dependent Preferences," Department of Economics, Working Paper Series qt0w82b6nm, Department of Economics, Institute for Business and Economic Research, UC Berkeley.
    3. Colin Camerer & Linda Babcock & George Loewenstein & Richard Thaler, 1997. "Labor Supply of New York City Cabdrivers: One Day at a Time," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 112(2), pages 407-441.
    4. Yuan K. Chou, 2002. "Testing Alternative Models Of Labour Supply: Evidence From Taxi Drivers In Singapore," The Singapore Economic Review (SER), World Scientific Publishing Co. Pte. Ltd., vol. 47(01), pages 17-47.
    5. Sanae Tashiro, 2017. "Non-Regular Female Workers in Japan’s Prolonged Economic Recession: Evidence from the Japanese Panel Survey of Consumers," Australian Journal of Labour Economics (AJLE), Bankwest Curtin Economics Centre (BCEC), Curtin Business School, vol. 20(1), pages 23-56.
    6. Vincent P. Crawford & Juanjuan Meng, 2011. "New York City Cab Drivers' Labor Supply Revisited: Reference-Dependent Preferences with Rational-Expectations Targets for Hours and Income," American Economic Review, American Economic Association, vol. 101(5), pages 1912-1932, August.
    7. Judd Cramer & Alan B. Krueger, 2016. "Disruptive Change in the Taxi Business: The Case of Uber," American Economic Review, American Economic Association, vol. 106(5), pages 177-182, May.
    8. Henry S. Farber, 2008. "Reference-Dependent Preferences and Labor Supply: The Case of New York City Taxi Drivers," American Economic Review, American Economic Association, vol. 98(3), pages 1069-1082, June.
    9. Botond Kőszegi & Matthew Rabin, 2006. "A Model of Reference-Dependent Preferences," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 121(4), pages 1133-1165.
    10. Botond Koszegi & Matthew Rabin, 2007. "Reference-Dependent Risk Attitudes," American Economic Review, American Economic Association, vol. 97(4), pages 1047-1073, September.
    11. Amos Tversky & Daniel Kahneman, 1991. "Loss Aversion in Riskless Choice: A Reference-Dependent Model," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 106(4), pages 1039-1061.
    12. Hawlitschek, Florian & Teubner, Timm & Weinhardt, Christof, 2016. "Trust in the Sharing Economy," Die Unternehmung - Swiss Journal of Business Research and Practice, Nomos Verlagsgesellschaft mbH & Co. KG, vol. 70(1), pages 26-44.
    13. McDonald, John F & Moffitt, Robert A, 1980. "The Uses of Tobit Analysis," The Review of Economics and Statistics, MIT Press, vol. 62(2), pages 318-321, May.
    14. Juho Hamari & Mimmi Sjöklint & Antti Ukkonen, 2016. "The sharing economy: Why people participate in collaborative consumption," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 67(9), pages 2047-2059, September.
    15. Janine Berg & Hannah Johnston, 2019. "Too Good to Be True? A Comment on Hall and Krueger’s Analysis of the Labor Market for Uber’s Driver-Partners," ILR Review, Cornell University, ILR School, vol. 72(1), pages 39-68, January.
    16. Henry S. Farber, 2005. "Is Tomorrow Another Day? The Labor Supply of New York City Cabdrivers," Journal of Political Economy, University of Chicago Press, vol. 113(1), pages 46-82, February.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Da, Yuwen & Gou, Qinglong & Liang, Chao, 2023. "Will self-gifting of streamers hurt unions? Analyzing the union’s compensation mechanism for a live streaming supply chain," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 177(C).
    2. Muntaser Mohamed Nuttah & Paolo Roma & Giovanna Lo Nigro & Giovanni Perrone, 2024. "The Short- and Long-Term Impacts of COVID-19 Pandemic on the Sharing Economy: Distinguishing Between “Symptomatic” and “Asymptomatic” Platforms," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 15(2), pages 9238-9287, June.

    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. Brodeur, Abel & Nield, Kerry, 2018. "An empirical analysis of taxi, Lyft and Uber rides: Evidence from weather shocks in NYC," Journal of Economic Behavior & Organization, Elsevier, vol. 152(C), pages 1-16.
    2. Martin, Vincent, 2017. "When to quit: Narrow bracketing and reference dependence in taxi drivers," Journal of Economic Behavior & Organization, Elsevier, vol. 144(C), pages 166-187.
    3. Weiqiang Tan & Jian Zhang, 2021. "Good Days, Bad Days: Stock Market Fluctuation and Taxi Tipping Decisions," Management Science, INFORMS, vol. 67(6), pages 3965-3984, June.
    4. Lü, Yiqing & Zhao, Bin & Zhu, Ning, 2024. "Unveiling investors' substitution behavior: Stock trading decisions in response to housing market dynamics," Journal of Corporate Finance, Elsevier, vol. 86(C).
    5. Alex Markle & George Wu & Rebecca White & Aaron Sackett, 2018. "Goals as reference points in marathon running: A novel test of reference dependence," Journal of Risk and Uncertainty, Springer, vol. 56(1), pages 19-50, February.
    6. Sloof, Randolph & van Praag, C. Mirjam, 2010. "The effect of noise in a performance measure on work motivation: A real effort laboratory experiment," Labour Economics, Elsevier, vol. 17(5), pages 751-765, October.
    7. Vincent P. Crawford & Juanjuan Meng, 2011. "New York City Cab Drivers' Labor Supply Revisited: Reference-Dependent Preferences with Rational-Expectations Targets for Hours and Income," American Economic Review, American Economic Association, vol. 101(5), pages 1912-1932, August.
    8. Timothy J. Richards, 2020. "Income Targeting and Farm Labor Supply," American Journal of Agricultural Economics, John Wiley & Sons, vol. 102(2), pages 419-438, March.
    9. Doran, Kirk, 2014. "Are long-term wage elasticities of labor supply more negative than short-term ones?," Economics Letters, Elsevier, vol. 122(2), pages 208-210.
    10. Liang Choon Wang, 2016. "The effect of high-stakes testing on suicidal ideation of teenagers with reference-dependent preferences," Journal of Population Economics, Springer;European Society for Population Economics, vol. 29(2), pages 345-364, April.
    11. Chang, Tom & Gross, Tal, 2014. "How many pears would a pear packer pack if a pear packer could pack pears at quasi-exogenously varying piece rates?," Journal of Economic Behavior & Organization, Elsevier, vol. 99(C), pages 1-17.
    12. Johannes Abeler & Armin Falk & Lorenz Goette & David Huffman, 2011. "Reference Points and Effort Provision," American Economic Review, American Economic Association, vol. 101(2), pages 470-492, April.
    13. Eil, David & Lien, Jaimie W., 2014. "Staying ahead and getting even: Risk attitudes of experienced poker players," Games and Economic Behavior, Elsevier, vol. 87(C), pages 50-69.
    14. Pramanik, Subhajit, 2021. "An Essay on Labor Supply Decisions and Reference Dependent Preferences," MPRA Paper 111499, University Library of Munich, Germany, revised 26 Dec 2021.
    15. Sun, Hao & Wang, Hai & Wan, Zhixi, 2019. "Model and analysis of labor supply for ride-sharing platforms in the presence of sample self-selection and endogeneity," Transportation Research Part B: Methodological, Elsevier, vol. 125(C), pages 76-93.
    16. Cadsby, C. Bram & Song, Fei & Zubanov, Nick, 2024. "Working more for more and working more for less: Labor supply in the gain and loss domains," Labour Economics, Elsevier, vol. 88(C).
    17. Jonathan de Quidt, 2018. "Your Loss Is My Gain: A Recruitment Experiment with Framed Incentives," Journal of the European Economic Association, European Economic Association, vol. 16(2), pages 522-559.
    18. Eric J. Allen & Patricia M. Dechow & Devin G. Pope & George Wu, 2017. "Reference-Dependent Preferences: Evidence from Marathon Runners," Management Science, INFORMS, vol. 63(6), pages 1657-1672, June.
    19. Johannes Abeler & Armin Falk & Lorenz Goette & David Huffman, 2011. "Reference Points and Effort Provision," American Economic Review, American Economic Association, vol. 101(2), pages 470-492, April.
    20. Dohmen, Thomas, 2014. "Behavioral labor economics: Advances and future directions," Labour Economics, Elsevier, vol. 30(C), pages 71-85.

    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:pal:buseco:v:56:y:2021:i:4:d:10.1057_s11369-021-00237-0. 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.palgrave-journals.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.