Modeling and managing an on-demand meal delivery system with order bundling

Anke Ye, Kenan Zhang, Chen, Xiqun (Michael), Michael G.H. Bell, Der-Horng Lee and Simon Hu

Transportation Research Part E: Logistics and Transportation Review, 2024, vol. 187, issue C

Abstract: This paper proposes an analytical framework for an on-demand meal delivery market that features order bundling and courier sharing among restaurants. The proposed model consists of (i) a physical model describing the delivery process with order bundling, and (ii) an aggregated market equilibrium model characterizing the demand and supply interactions, which enables us to generate managerial insights without knowing the operational details. We analyze the impacts of demand and supply levels as well as the platform’s pricing and wage strategies on the system equilibrium. We outline a regime, which effectively defines a “healthy” state, optimizing the system’s service capacity to its fullest extent. The results demonstrate that a higher maximum bundle size enables a higher throughput capacity, resulting in improved energy efficiency for the system, lower service prices for customers, increased service opportunities for couriers, and higher turnover for restaurants. In comparison to the single-order delivery mode, the bundling delivery mode mitigates a substantial surge in prices during peak service hours. However, an excessive maximum bundle size is not advised for the platform oriented either toward service quality or profit due to the increasing Click-to-Door time and reduced marginal profit.

Keywords: On-demand meal delivery services; Market equilibrium; Bundling delivery; Shared couriers (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1016/j.tre.2024.103597

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