Matching in Ride Hailing: Wild Goose Chases and How to Solve Them

70 Pages Posted: 28 Dec 2016 Last revised: 11 May 2021

See all articles by Juan Camilo Castillo

Juan Camilo Castillo

University of Pennsylvania - Department of Economics

Daniel T. Knoepfle

Uber Technologies Inc.

E. Glen Weyl

Microsoft ; RadicalxChange Foundation

Date Written: May 10, 2021

Abstract

We show that ride-hailing markets are prone to a matching failure ("wild goose chases") in which high demand sets off a harmful feedback cycle of few idle drivers, high pickup times, and low earnings, drastically reducing welfare. After characterizing these failures theoretically and showing empirical evidence of their relevance, we analyze how platforms can avoid them. Two solutions control demand spikes with prices: (1) a uniform high price and (2) high "surge" pricing during high-demand times while keeping prices low at other times. Some adjustments to the matching algorithm can also avoid the problem, but surge pricing Pareto-dominates them in our empirical setting.

Keywords: Ride Hailing, Market Design, Matching, First Dispatch, Surge Pricing

JEL Classification: D47, L91, R41

Suggested Citation

Castillo, Juan Camilo and Knoepfle, Daniel T. and Weyl, Eric Glen, Matching in Ride Hailing: Wild Goose Chases and How to Solve Them (May 10, 2021). Available at SSRN: https://ssrn.com/abstract=2890666 or http://dx.doi.org/10.2139/ssrn.2890666

Juan Camilo Castillo (Contact Author)

University of Pennsylvania - Department of Economics ( email )

Ronald O. Perelman Center for Political Science
133 South 36th Street
Philadelphia, PA 19104-6297
United States

HOME PAGE: http://www.jc-castillo.net

Daniel T. Knoepfle

Uber Technologies Inc. ( email )

1455 Market St
San Francisco, CA 94103-1331
United States

Eric Glen Weyl

Microsoft ( email )

306 Park Ave
Apt 3
Hoboken, NJ 07030
United States
8579984513 (Phone)

HOME PAGE: http://www.glenweyl.com

RadicalxChange Foundation ( email )

HOME PAGE: http://www.radicalxchange.org

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