Driver Surge Pricing

67 Pages Posted: 6 Jun 2019 Last revised: 23 Mar 2021

See all articles by Nikhil Garg

Nikhil Garg

Stanford University

Hamid Nazerzadeh

University of Southern California - Marshall School of Business

Date Written: July 10, 2020


Ride-hailing marketplaces like Uber and Lyft use dynamic pricing, often called surge, to balance the supply of available drivers with the demand for rides.
We study driver-side payment mechanisms for such marketplaces, presenting the theoretical foundation that has informed the design of Uber's new additive driver surge mechanism.
We present a dynamic stochastic model to capture the impact of surge pricing on driver earnings and their strategies to maximize such earnings. In this setting, some time periods (surge) are more valuable than others (non-surge), and so trips of different time lengths vary in the induced driver opportunity cost.

First, we show that multiplicative surge, historically the standard on ride-hailing platforms, is not incentive compatible in a dynamic setting. We then propose a structured, incentive-compatible pricing mechanism. This closed-form mechanism has a simple form and is well-approximated by Uber's new additive surge mechanism. Finally, through both numerical analysis and real data from a ride-hailing marketplace, we show that additive surge is more incentive compatible in practice than is multiplicative surge.

Suggested Citation

Garg, Nikhil and Nazerzadeh, Hamid, Driver Surge Pricing (July 10, 2020). USC Marshall School of Business Research Paper Sponsored by iORB, No. Forthcoming, Available at SSRN: or

Nikhil Garg

Stanford University ( email )

Stanford, CA 94305
United States


Hamid Nazerzadeh (Contact Author)

University of Southern California - Marshall School of Business ( email )

Bridge Memorial Hall
Los Angeles, CA 90089
United States


Do you have a job opening that you would like to promote on SSRN?

Paper statistics

Abstract Views
PlumX Metrics