Flexible Labor Supply Behavior on Ride-Sourcing Platforms

Posted: 12 Jun 2019

See all articles by Hao Sun

Hao Sun

Tsinghua University - School of Economics and Management

Hai Wang

Carnegie Mellon University - Heinz College of Information Systems and Public Policy; Singapore Management University - School of Information Systems

Zhixi Wan

The University of Hong Kong - Faculty of Business and Economics

Date Written: March 21, 2019

Abstract

With the popularization of ride-sharing services, drivers working as freelancers on ride-sourcing platforms can design their schedules flexibly. They make decisions regarding whether to participate in work, and if so, how many hours to work. Understanding flexible labor supply behaviour is critical for the platform to manage service capacity. It also helps to evaluate the effects of platform incentives on service capacity and driver welfare. We propose a labor supply model to describe how freelance drivers rationally optimize their labor supply decisions on the platform. Specifically, we model drivers’ participation decision at the extensive margin and hours worked decision at the intensive margin, with an objective to maximize their utility from income and leisure time. We analyze the effects of drivers’ heterogeneity in terms of their other income, idle time, and participation cost. The analytical results show that both the participation decision and the working-hours decision depend on all these drivers’ types, and participating drivers’ working-hour elasticity may be negative under some conditions. With data-driven estimated parameters using inverse optimization, we also propose a framework to design the multi-dimensional incentives on ride-sourcing platforms.

Suggested Citation

Sun, Hao and Wang, Hai and Wan, Zhixi, Flexible Labor Supply Behavior on Ride-Sourcing Platforms (March 21, 2019). Available at SSRN: https://ssrn.com/abstract=3357365

Hao Sun

Tsinghua University - School of Economics and Management ( email )

China

Hai Wang (Contact Author)

Carnegie Mellon University - Heinz College of Information Systems and Public Policy ( email )

5000 Forbes Avenue
Pittsburgh, PA 15213-3890
United States

Singapore Management University - School of Information Systems ( email )

School of Information Systems
80 Stamford Road
Singapore 178902, 178899
Singapore

Zhixi Wan

The University of Hong Kong - Faculty of Business and Economics ( email )

Pokfulam Road
Hong Kong
China

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