skip to main content
research-article

Part-Time Ride-Sharing: Recognizing the Context in which Drivers Ride-Share and its Impact on Platform Use

Published:05 December 2019Publication History
Skip Abstract Section

Abstract

Ride-sharing companies have been reshaping the structure and practice of ride-hailing work. At the same time, studies have been showing mixed driver experiences on the platform while many of the drivers are working part-time. In this research, we seek to understand why drivers on this platform are working part-time, how this impacts their view of the platform, and what this means for more accurately evaluating the design of these platforms. To investigate this question, we focused on situating ride-sharing in the lives and constellation of gigs that drivers maintain. We collected 53 survey responses and conducted 10 semi-structured interviews with drivers to probe these questions. We found that the extent that drivers categorize themselves as part-time is less about the number of hours worked and more about how dependent they are on ride-sharing income. The level of this dependency seemed to heavily influence how they interacted with the platform and their attitudes towards difficulties faced. It seemed to us that in some ways that the design or functioning of the platform almost pushed users towards working part-time. We discuss the importance of taking these different types of workers and their situations into consideration when evaluating the design and usability of these platforms.

References

  1. 2018. How Much Do Uber Drivers ACTUALLY Earn? [Find Out Here]. (Apr 2018). https://www.ridester.com/ how-much-do-uber-drivers-make/Google ScholarGoogle Scholar
  2. Syed Ishtiaque Ahmed, Nicola J. Bidwell, Himanshu Zade, Srihari H. Muralidhar, Anupama Dhareshwar, Baneen Karachiwala, Cedrick N. Tandong, and Jacki O'Neill. 2016. Peer-to-peer in the Workplace. In Proceedings of the 2016 CHI Conference (CHI '16). ACM Press, New York, New York, USA, 5063--5075.Google ScholarGoogle ScholarDigital LibraryDigital Library
  3. Antonio Aloisi. 2015. Commoditized workers: Case study research on labor law issues arising from a set of ondemand/ gig economy platforms. Comp. Lab. L. & Pol'y J. 37 (2015), 653.Google ScholarGoogle Scholar
  4. Elena Bardasi and Janet C Gornick. 2008. Working for less? Women's part-time wage penalties across countries. Feminist economics 14, 1 (2008), 37--72.Google ScholarGoogle Scholar
  5. Janine Berg and Hannah Johnston. 2018. Too Good to Be True? A Comment on Hall and Krueger's Analysis of the Labor Market for Uber's Driver-Partners. ILR Review (2018), 0019793918798593.Google ScholarGoogle Scholar
  6. Hans-Peter Blossfeld and Catherine Hakim. 1997. Between equalization and marginalization: women working part-time in Europe. Oxford University Press.Google ScholarGoogle Scholar
  7. Le Chen, Alan Mislove, and Christo Wilson. 2015. Peeking Beneath the Hood of Uber. In Proceedings of the 2015 Internet Measurement Conference (IMC '15). ACM, New York, NY, USA, 495--508.Google ScholarGoogle ScholarDigital LibraryDigital Library
  8. Gail Cornwall. 2018. Are Uber's drive-at-home dads the new "piecework" button-sewing moms? (Apr 2018). https: //work.qz.com/1214581/are-ubers-drive-at-home-dads-the-new-piecework-new-button-sewing-moms/Google ScholarGoogle Scholar
  9. Gerald F Davis. 2016. The vanishing American corporation: Navigating the hazards of a new economy. Berrett-Koehler Publishers.Google ScholarGoogle Scholar
  10. Colette Fagan, Helen Norman, Mark Smith, and María C González Menéndez. 2014. In search of good quality part-time employment. ILO Geneva.Google ScholarGoogle Scholar
  11. Gerald Friedman. 2014. Workers without employers: shadow corporations and the rise of the gig economy. Review of Keynesian Economics 2, 2 (2014), 171--188.Google ScholarGoogle ScholarCross RefCross Ref
  12. Harold Garfinkel. 1967. Studies in ethnomethodology. (1967).Google ScholarGoogle Scholar
  13. Mareike Glöss, Moira McGregor, and Barry Brown. 2016. Designing for Labour: Uber and the On-Demand Mobile Workforce. In Proceedings of the 2016 CHI Conference. ACM Press, New York, New York, USA, 1632--1643.Google ScholarGoogle ScholarDigital LibraryDigital Library
  14. Greg Goldberg. 2018. Antisocial Media: Anxious Labor in the Digital Economy. NYU Press.Google ScholarGoogle ScholarCross RefCross Ref
  15. Jonathan V Hall and Alan B Krueger. 2016. An analysis of the labor market for Uber's driver-partners in the United States. Technical Report. National Bureau of Economic Research.Google ScholarGoogle Scholar
  16. Jonathan V. Hall and Alan B. Krueger. 2018. An Analysis of the Labor Market for Uber's Driver- Partners in the United States. ILR Review 71, 3 (2018), 705--732. https://doi.org/10.1177/0019793917717222 arXiv:https://doi.org/10.1177/0019793917717222Google ScholarGoogle ScholarCross RefCross Ref
  17. Benjamin Hanrahan, Ma Ning, and Yuan Chien Wen. 2017. The Roots of Bias on Uber. In Proceedings of 15th European Conference on Computer-Supported Cooperative Work-Exploratory Papers. European Society for Socially Embedded Technologies (EUSSET).Google ScholarGoogle Scholar
  18. Benjamin V Hanrahan and John M Carroll. 2017. Technologies atWork. The Wiley Blackwell handbook of the psychology of the internet at work 7696 (2017), 39.Google ScholarGoogle Scholar
  19. Inés Hardoy and Pål Schøne. 2004. The part-time wage gap: how large is it really? Institute for Social Research (2004).Google ScholarGoogle Scholar
  20. Barry T Hirsch. 2005. Why do part-time workers earn less? The role of worker and job skills. ILR Review 58, 4 (2005), 525--551.Google ScholarGoogle ScholarCross RefCross Ref
  21. Wonolo Inc. 2018. Data on the Gig Economy and How it is Transforming the Workforce. (Jul 2018). https: //www.wonolo.com/blog/data-gig-economy-transforming-workforce/Google ScholarGoogle Scholar
  22. Emily Isaac. 2014. Disruptive innovation: Risk-shifting and precarity in the age of Uber. Berkeley Roundtable on the International Economy,[University of California, Berkeley].Google ScholarGoogle Scholar
  23. Maria Jepsen, Sile Padraigin O'DORCHAI, and Robert Plasman. 2005. The wage penalty induced by part-time work: the case of Belgium. (2005).Google ScholarGoogle Scholar
  24. Vaishnav Kameswaran, Lindsey Cameron, and Tawanna R Dillahunt. 2018. Support for social and cultural capital development in real-time ridesharing services. In Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems. ACM, 342.Google ScholarGoogle ScholarDigital LibraryDigital Library
  25. Joseph Kasera, Jacki O'Neill, and Nicola J. Bidwell. 2016. Sociality, Tempo & Flow: Learning from Namibian Ridesharing. In Proceedings of the First African Conference on Human Computer Interaction - AfriCHI'16. ACM Press, New York, New York, USA, 36--47.Google ScholarGoogle Scholar
  26. Aniket Kittur, Jeffrey V Nickerson, Michael Bernstein, Elizabeth Gerber, Aaron Shaw, John Zimmerman, Matt Lease, and John Horton. 2013. The future of crowd work. In Proceedings of the 2013 CSCW Conference. ACM, New York, NY, USA, 1301--1318.Google ScholarGoogle ScholarDigital LibraryDigital Library
  27. Tamara Kneese, Alex Rosenblat, and danah boyd. 2014. Understanding Fair Labor Practices in a Networked Age. SSRN Electronic Journal (2014). http://www.ssrn.com/abstract=2536619Google ScholarGoogle Scholar
  28. Neha Kumar, Nassim Jafarinaimi, and Mehrab Bin Morshed. 2018. Uber in Bangladesh: The Tangled Web of Mobility and Justice. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (2018), 98.Google ScholarGoogle ScholarDigital LibraryDigital Library
  29. Min Kyung Lee, Daniel Kusbit, Evan Metsky, and Laura Dabbish. 2015. Working with Machines: The Impact of Algorithmic and Data-Driven Management on Human Workers. In Proceedings of the 2015 CHI Conference. ACM, 1603--1612.Google ScholarGoogle ScholarDigital LibraryDigital Library
  30. Ning F. Ma, Chien Wen Yuan, Moojan Ghafurian, and Benjamin V. Hanrahan. 2018. Using Stakeholder Theory to Examine Drivers' Stakes in Uber. In Proceedings of the 2018 CHI Conference. ACM.Google ScholarGoogle Scholar
  31. David Martin, Sheelagh Carpendale, Neha Gupta, Tobias Hoßfeld, Babak Naderi, Judith Redi, Ernestasia Siahaan, and Ina Wechsung. 2017. Understanding the Crowd: Ethical and Practical Matters in the Academic Use of Crowdsourcing. In Evaluation in the Crowd. Crowdsourcing and Human-Centered Experiments. Springer, 27--69.Google ScholarGoogle Scholar
  32. David Martin, Benjamin V Hanrahan, Jacki O'Neill, and Neha Gupta. 2014. Being a Turker. In Proceedings of the 2014 CSCW Conference. ACM, 224--235.Google ScholarGoogle ScholarDigital LibraryDigital Library
  33. TJ McCue. 2018. 57 Million U.S. Workers Are Part Of The Gig Economy. (Aug 2018). https://www.forbes.com/sites/ tjmccue/2018/08/31/57-million-u-s-workers-are-part-of-the-gig-economy/#c909a6e71186Google ScholarGoogle Scholar
  34. Moira Mcgregor, Barry Brown, Mareike Glöss, and Airi Lampinen. 2017. On-Demand Taxi Driving: Labour Conditions, Surveillance, and Exclusion. http://ipp.oii.ox.ac.uk/sites/ipp/files/documents/McGregor_Uber%2520paper%2520Sept% 25201%2520PDF.pdf. (2017). Last Accessed: 2017-05--19.Google ScholarGoogle Scholar
  35. Madeline Nightingale. 2019. Looking beyond Average Earnings: Why Are Male and Female Part-Time Employees in the UK More Likely to Be Low Paid Than Their Full-Time Counterparts? Work, Employment and Society (2019), 0950017018796471.Google ScholarGoogle Scholar
  36. Noopur Raval and Paul Dourish. 2016. Standing Out from the Crowd: Emotional Labor, Body Labor, and Temporal Labor in Ridesharing. In Proceedings of the 2016 CSCW Conference. ACM, 97--107.Google ScholarGoogle ScholarDigital LibraryDigital Library
  37. Lisa Rayle, Susan Shaheen, Nelson Chan, Danielle Dai, and Robert Cervero. 2014. App-based, on-demand ride services: Comparing taxi and ridesourcing trips and user characteristics in san francisco university of california transportation center (uctc). Technical Report. UCTC-FR-2014-08.Google ScholarGoogle Scholar
  38. Brishen Rogers. 2015. The Social Costs of Uber. The University of Chicago Law Review Dialogue 82, 85 (2015), 85--102.Google ScholarGoogle Scholar
  39. Alex Rosenblat. 2016. Uber's Shift-y Work - Uber Screeds - Medium. (Feb 2016). https://medium.com/uber-screeds/ uber-s-shift-y-work-2665dbb58701Google ScholarGoogle Scholar
  40. Alex Rosenblat. 2018. Uberland: how algorithms are rewriting the rules of work. Univ of California Press.Google ScholarGoogle Scholar
  41. Alex Rosenblat, Karen EC Levy, Solon Barocas, and Tim Hwang. 2016. Discriminating Tastes: Customer Ratings as Vehicles for Bias. Available at SSRN: https://ssrn.com/abstract=2858946. (2016).Google ScholarGoogle Scholar
  42. Alex Rosenblat and Luke Stark. 2016. Algorithmic Labor and Information Asymmetries: A Case Study of Uber's Drivers. International Journal of Communication 10 (2016), 3758--3784.Google ScholarGoogle Scholar
  43. Trebor Scholz. 2012. Digital labor: The Internet as playground and factory. Routledge.Google ScholarGoogle Scholar
  44. Jacob Thebault-Spieker, Loren G. Terveen, and Brent Hecht. 2015. Avoiding the South Side and the Suburbs. In Proceedings of the 2015 CSCW Conference. ACM Press, New York, New York, USA, 265--275.Google ScholarGoogle ScholarDigital LibraryDigital Library
  45. Piret Tõnurist, Dimitris Pavlopoulos, et al. 2014. Part-time wage-gap in Germany: Evidence across the wage distribution. (2014).Google ScholarGoogle Scholar
  46. David Weil. 2014. The fissured workplace. Harvard University Press.Google ScholarGoogle Scholar

Index Terms

  1. Part-Time Ride-Sharing: Recognizing the Context in which Drivers Ride-Share and its Impact on Platform Use

        Recommendations

        Comments

        Login options

        Check if you have access through your login credentials or your institution to get full access on this article.

        Sign in

        Full Access

        • Published in

          cover image Proceedings of the ACM on Human-Computer Interaction
          Proceedings of the ACM on Human-Computer Interaction  Volume 3, Issue GROUP
          GROUP
          December 2019
          425 pages
          EISSN:2573-0142
          DOI:10.1145/3375021
          Issue’s Table of Contents

          Copyright © 2019 ACM

          Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

          Publisher

          Association for Computing Machinery

          New York, NY, United States

          Publication History

          • Published: 5 December 2019
          Published in pacmhci Volume 3, Issue GROUP

          Permissions

          Request permissions about this article.

          Request Permissions

          Check for updates

          Qualifiers

          • research-article

        PDF Format

        View or Download as a PDF file.

        PDF

        eReader

        View online with eReader.

        eReader