EURO 2025 Leeds
Abstract Submission

600. Optimizing Service Fees and Driver Payments for Restaurant Food Delivery

Invited abstract in session MC-29: Pricing Strategies in Food & Service Platforms, stream Pricing and Revenue Management Innovations.

Monday, 12:30-14:00
Room: Maurice Keyworth 1.04

Authors (first author is the speaker)

1. Candace Yano
IEOR Dept. and Haas School of Business, University of California, Berkeley
2. Gabriel Deza
Industrial Engineering, Tel Aviv University

Abstract

We address a restaurant food delivery platform’s problem of setting customer and restaurant service fees along with compensation for delivery drivers to maximize profit. We generalize earlier models by incorporating realistic consideration of how the number and mix of participating restaurants affects the customers’ willingness to utilize the platform and their restaurant choices. Restaurants are heterogeneous in the service charge rate they are willing to pay, and drivers are heterogeneous in their reservation wage. Customer demands are affected by the number and variety of participating restaurants, the service charge rate imposed on customers, and waiting times. We seek a solution that satisfies equilibrium conditions and participation constraints in view of these interactions.

We develop a nested optimization algorithm with an embedded queueing model. Each level of the problem is solved while considering the conditionally optimal solutions of decisions at lower levels and pertinent equilibrium conditions.

We present numerical examples and characterize the platform’s optimal choices and the participants’ equilibrium behavior. We find that the platform’s profit is sensitive to the delay in assigning drivers to orders, so platforms need to carefully calibrate decisions to ensure the “best” utilization level is achieved. We also find that interesting tradeoffs arise in our problem setting that do not arise when restaurants are homogeneous or passive.

Keywords

Status: accepted

Back to the list of papers