A stochastic generalized Nash equilibrium model for platforms competition in the ride-hail market

Filippo Fabiani*, Barbara Franci

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference article in proceedingAcademicpeer-review

Abstract

The inherent uncertainties in the ride-hailing market complicate the pricing strategies of on-demand platforms that compete each other to offer a mobility service while striving to maximize their profit. Looking at this problem as a stochastic generalized Nash equilibrium problem (SGNEP), we design a distributed, stochastic equilibrium seeking algorithm with Tikhonov regularization to find an optimal pricing strategy. The proposed iterative scheme does not require a potentially infinite number of samples of the random variable to perform the stochastic approximation, thus making it appealing from a practical perspective. Moreover, we show that the algorithm returns a Nash equilibrium under mere monotonicity assumptions and a careful choice of the step size sequence, obtained by exploiting the specific structure of the SGNEP at hand.
Original languageEnglish
Title of host publication2022 IEEE 61st Conference on Decision and Control (CDC)
Pages4455-4460
Number of pages6
DOIs
Publication statusPublished - 2022
Event2022 IEEE 61st Conference on Decision and Control - Cancun, Mexico
Duration: 6 Dec 20229 Dec 2022

Conference

Conference2022 IEEE 61st Conference on Decision and Control
Abbreviated titleCDC 2022
Country/TerritoryMexico
CityCancun
Period6/12/229/12/22

Fingerprint

Dive into the research topics of 'A stochastic generalized Nash equilibrium model for platforms competition in the ride-hail market'. Together they form a unique fingerprint.

Cite this