Surge Pricing and Short-term Wage Elasticity of Labor Supply in Real-Time Ridesharing Markets

Forthcoming in MIS Quarterly

55 Pages Posted: 14 Jun 2018 Last revised: 24 Feb 2021

See all articles by Shu He

Shu He

University of Connecticut - Department of Operations & Information Management

Liangfei Qiu

University of Florida - Warrington College of Business Administration

Xusen Cheng

Renmin University of China

Date Written: February 23, 2021

Abstract

The prominence of real-time ridesharing services, such as Uber and Lyft, has dramatically changed the landscape of traditional industries. This study provides a comprehensive analysis of the short-term wage elasticity of labor supply in real-time ridesharing markets using data from a major ridesharing platform in China. By exploiting an exogenous shock from uneven driving restrictions as an instrumental variable, we find a negative labor supply elasticity for ridesharing drivers, suggesting that drivers tend to drive less during days with a higher average hourly wage. Specifically, a percent increase in hourly wage will lead to a 0.931 percent decrease in daily working hours. This surprising finding is consistent with the behavioral income-targeting model based on the theory of reference-dependent preferences: Drivers have heuristic daily targets for total earnings and are more motivated to supply labor when they are below their income target than when they are above it. Therefore, they work less on days when earnings per hour are high and quit the market once their income target is reached. In addition, we find that taxi drivers are more rational and have positive labor supply elasticity, which implies that drivers are more rational when they have repeated opportunities for learning. Estimating labor supply elasticity is critical to understanding the economic efficiency of various surge pricing algorithms and driver subsidization programs for ridesharing platforms and policymakers. Our research suggests that a uniform price surging or driver subsidization approach for all ridesharing drivers may not incentivize the labor supply of drivers effectively.

Keywords: Labor supply elasticity, Ridesharing, Income target, Reference-dependent preferences

Suggested Citation

He, Shu and Qiu, Liangfei and Cheng, Xusen, Surge Pricing and Short-term Wage Elasticity of Labor Supply in Real-Time Ridesharing Markets (February 23, 2021). Forthcoming in MIS Quarterly, Available at SSRN: https://ssrn.com/abstract=3186162

Shu He

University of Connecticut - Department of Operations & Information Management ( email )

368 Fairfield Road
Storrs, CT 06269-2041
United States

Liangfei Qiu

University of Florida - Warrington College of Business Administration ( email )

Gainesville, FL 32611
United States

HOME PAGE: http://sites.google.com/site/qiuliangfei/

Xusen Cheng (Contact Author)

Renmin University of China ( email )

59, Zhongguancun South Street
Haidian District
Beijing, Beijing 100872
China

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