Spatial Pricing in Ride-Sharing Networks

Kostas Bimpikis (), Ozan Candogan () and Daniela Saban ()
Additional contact information
Kostas Bimpikis: Graduate School of Business, Stanford University, Palo Alto, California 94305
Ozan Candogan: Booth School of Business, Chicago University, Chicago, Illinois 60637
Daniela Saban: Graduate School of Business, Stanford University, Palo Alto, California 94305

Operations Research, 2019, vol. 67, issue 3, 744-769

Abstract: Motivated by the prevalence of ride-sharing platforms, in “Spatial Pricing in Ride-Sharing Networks,” Bimpikis, Candogan, and Saban explore the impact of the demand pattern for rides across a network’s locations on a platform’s optimal pricing and compensation policy, profits, and consumer surplus. They explicitly account for the pricing problem’s spatial dimension and the fact that the drivers endogenously determine whether and where to provide service. Their first contribution is to develop a tractable model to study a platform operating on a network of locations that may differ in both the size of their potential demand and the destination preferences of riders. Second, they provide a characterization of the platform’s optimal policy and identify “balancedness” of the demand pattern as a property that captures the profit potential of a given network. Finally, they discuss the benefits and limitations of a number of alternative pricing and compensation schemes.

Keywords: ride sharing; revenue management; network flows; spatial price discrimination (search for similar items in EconPapers)
Date: 2019
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Citations: View citations in EconPapers (86)

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