Labor Welfare in On-Demand Service Platforms

41 Pages Posted: 17 Jan 2018

See all articles by Saif Benjaafar

Saif Benjaafar

University of Minnesota - Minneapolis - Industrial & System Engineering

Jian-Ya Ding

Tsinghua University - Department of Automation

Guangwen Kong

University of Minnesota - Minneapolis - Industrial & System Engineering

Terry Taylor

University of California, Berkeley - Haas School of Business

Date Written: January 16, 2018

Abstract

We study labor welfare in on-demand service platforms that rely on agents who decide whether and how much to work. Such platforms benefit from having access to a large supply of agents, as the availability of more agents implies lower labor cost and shorter customer delays. It has been argued by some labor advocates that this comes at the expense of agents who see, as a consequence of the expansion of labor supply, lower wages and less work. In this paper, we examine the extent to which the interest of platforms in increasing labor supply is indeed at odds with those of agents. Using an equilibrium model that accounts for the interaction between labor supply and demand, we show that factors that affect labor supply, such as labor pool size, delay cost, and variability in the agents’ opportunity cost, may have a non-monotonic effect on labor welfare. In particular, we identify two regimes, depending on the level of congestion in the system, one in which an expansion of labor supply improves labor welfare and makes agents busier and one in which an expansion of labor supply harms labor welfare and makes agents less busy. We compare these results to those obtained in a setting where customers are not sensitive to delay and to settings where agents must commit to working a specified amount time and are compensated at a fixed wage rate.

Keywords: On-Demand Service Platforms, Labor Welfare, Equilibrium Models, Sharing Economy

Suggested Citation

Benjaafar, Saif and Ding, Jian-Ya and Kong, Guangwen and Taylor, Terry, Labor Welfare in On-Demand Service Platforms (January 16, 2018). Available at SSRN: https://ssrn.com/abstract=3102736

Saif Benjaafar

University of Minnesota - Minneapolis - Industrial & System Engineering ( email )

111 Church Street S.E.
Minneapolis, MN 55455
United States

Jian-Ya Ding

Tsinghua University - Department of Automation ( email )

Beijing, 100084
China

Guangwen Kong (Contact Author)

University of Minnesota - Minneapolis - Industrial & System Engineering ( email )

111 Church Street S.E.
Minneapolis, MN 55455
United States

Terry Taylor

University of California, Berkeley - Haas School of Business ( email )

545 Student Services Building, #1900
2220 Piedmont Avenue
Berkeley, CA 94720
United States

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