Operations Research 2025
Abstract Submission

2281. Ride-hailing networks with strategic drivers: The effects of driver wage policies and network characteristics on performance

Invited abstract in session TD-11: Applications, stream Pricing and Revenue Management.

Thursday, 14:30-16:00
Room: U2-200

Authors (first author is the speaker)

1. Uta Mohring
Eindhoven University of Technology
2. Philipp Afèche
Rotman School of Management, University of Toronto
3. Andre Augusto Cire
Department of Management, University of Toronto Scarborough

Abstract

When matching riders with drivers over a spatial network, ride-hailing platforms face spatial demand imbalances, which require driver repositioning to serve the total rider demand, and strategic drivers, who decide whether to participate in the platform and if so, whether and where to reposition. We study the effects of driver wage policies on drivers' decisions and the resulting equilibrium under decentralized repositioning and evaluate their effectiveness in achieving the centralized performance benchmark.
We consider a stationary fluid model of a ride-hailing network in a game-theoretic framework with riders, drivers, and the platform. We characterize the steady-state system equilibrium under decentralized repositioning for various driver wage policies as well as how the effectiveness of driver wage policies depends on the interplay of demand imbalances, wage flexibility, and the congestion-sensitivity and spatial relations of travel times. More precisely: (i) We identify necessary and sufficient travel time conditions for equilibrium existence. (ii) We show that origin-dependent wage rates are sufficient to achieve the centrally optimal capacity level and platform profit while more limited wage flexibility yields idle driver inefficiencies. (iii) Our results indicate that decentralized repositioning yields an efficiency loss as the centrally optimal repositioning rates can generally not be implemented under decentralized repositioning, even with full wage flexibility.
Our results provide novel insights into how key network operational and financial characteristics affect the efficiency loss of decentralized repositioning and managerial guidelines for the design of driver wage policies under decentralized repositioning.

Keywords

Status: accepted

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