Equilibrium analysis for on-demand food delivery markets

Jintao Ke, Ce Wang, Xinwei Li, Qiong Tian and Hai-Jun Huang ()

Transportation Research Part E: Logistics and Transportation Review, 2024, vol. 184, issue C

Abstract: With the popularity of smartphones and the mobile internet, on-demand food and grocery delivery services have experienced rapid development in recent years. A food delivery platform dispatches crowd-sourced drivers to pick up meals at merchants, e.g., restaurants and grocery supermarkets, and then deliver the meals to customers. Apart from setting the delivery price paid by customers and the wage offered to drivers, the platform can also adjust the number of customers’ orders assigned to one driver in each batch (denoted as assignment factor) to affect the market equilibrium and achieve certain objectives. This paper develops a mathematical model to characterize the equilibrium state of an on-demand food delivery market, and investigate the platform’s optimal operating strategies in terms of the delivery price, wage and assignment factor for maximizing the platform profit or social welfare. In particular, we consider two market scenarios depending on whether the meals are ready before the drivers arrive at the merchants’ locations to pick them up. It is interesting to find that the platform will choose a strategy that leads to the scenario in which the meals are ready as the drivers arrive at the merchants. This work provides several managerial insights into the development of appropriate operational strategies for profit maximization and social welfare enhancement.

Keywords: Food delivery service; On-demand equilibrium; Revenue management; Pareto-efficient frontier (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1016/j.tre.2024.103467

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