Ride-Hailing Networks with Strategic Drivers: The Impact of Platform Control Capabilities on Performance

61 Pages Posted: 12 Feb 2018 Last revised: 12 Dec 2022

See all articles by Philipp Afeche

Philipp Afeche

University of Toronto - Rotman School of Management

Zhe Liu

Imperial College Business School

Costis Maglaras

Columbia University - Columbia Business School, Decision Risk and Operations

Date Written: December 11, 2022

Abstract

Problem Definition: Motivated by ride-hailing platforms such as Uber, Lyft and Didi, we study the problem of matching riders with self-interested drivers over a spatial network. We focus on the performance impact of two operational platform controls—demand-side admission control and supply-side repositioning control—considering the interplay with two practically important challenges: (i) spatial demand imbalances prevail for extended periods of time; and (ii) self-interested drivers strategically decide whether to join the network, and if so, whether to reposition when not serving riders.

Methodology/Results: We develop and analyze the steady-state behavior of a novel game-theoretic fluid model of a two-location, four-route loss network. First, we fully characterize and compare the steady-state system equilibria under three control regimes, from minimal control to centralized control. Second, we provide insights on how and why platform control impacts equilibrium performance, notably with new findings on the role of admission control: the platform may find it optimal to strategically reject demand at the low-demand location even if drivers are in excess supply, to induce repositioning to the high-demand location. We provide necessary and sufficient conditions for this policy. Third, we derive upper bounds on the platform's and drivers' benefits due to increased platform control; these are more significant under moderate capacity and significant cross-location demand imbalance.

Managerial Implications: Our results contribute important guidelines on the optimal operations of ride-hailing networks. Our model can also inform the design of driver compensation structures that support more centralized network control.

Keywords: ride-hailing, control, network, matching, strategic drivers, demand imbalance

Suggested Citation

Afeche, Philipp and Liu, Zhe and Maglaras, Costis, Ride-Hailing Networks with Strategic Drivers: The Impact of Platform Control Capabilities on Performance (December 11, 2022). Rotman School of Management Working Paper No. 3120544, Columbia Business School Research Paper No. 18-19, Available at SSRN: https://ssrn.com/abstract=3120544 or http://dx.doi.org/10.2139/ssrn.3120544

Philipp Afeche

University of Toronto - Rotman School of Management ( email )

105 St. George Street
Toronto, Ontario M5S 3E6 M5S1S4
Canada
416-978-1591 (Phone)

HOME PAGE: http://www.rotman.utoronto.ca/facbios/viewFac.asp?facultyID=philipp.afeche

Zhe Liu (Contact Author)

Imperial College Business School ( email )

Imperial College London
South Kensington Campus
London, SW7 2AZ
United Kingdom

Costis Maglaras

Columbia University - Columbia Business School, Decision Risk and Operations ( email )

New York, NY
United States

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