Analysis of Transshipment in Three-Sided Meal Delivery Services via Microhubs

TL;DR

This paper proposes a transshipment strategy for three-sided meal delivery services using microhubs, modeling system performance with network queues, and demonstrates its advantages over traditional methods through analytical and empirical evaluations.

Contribution

It introduces a novel transshipment approach with microhubs for meal delivery, including analytical modeling and performance evaluation, enhancing existing delivery strategies.

Findings

Transshipment reduces vehicle miles traveled during non-peak hours.

Transshipment improves customer service during high-demand periods.

Longer customer waiting times occur during low-demand conditions with transshipment.

Abstract

This paper introduces and analyzes a novel transshipment strategy for meal delivery. In this approach, the service area is partitioned into smaller sub-areas, with deliverers assigned to operate exclusively within these sub-areas. Meanwhile, a centrally located microhub functions as a logistic depot to facilitate the batching and transfer of meal packages toward different sub-areas. We model the meal delivery system with transshipment using networked G/G/m queues and analytically approximate two critical system performance metrics -- customer waiting time and vehicle miles traveled -- to evaluate the effectiveness of the proposed strategy. The performance achieved by transshipment is benchmarked against that of the classic pickup-and-delivery strategy without transshipment, both predicted using continuous approximations. For the latter, we enhance the existing modeling by incorporating the delivery distance profiles of individual orders to better match the meal delivery context. Our comparisons indicate that meal delivery via transshipment outperforms the non-transshipping counterpart across both metrics under either high-demand or low-supply conditions, with particular advantages in servicing larger areas or handling long-distance orders. This conclusion is corroborated by a numerical experiment using empirical meal delivery data from Meituan, which suggests that an optimally configured transshipment strategy can significantly improve service performance for both customers and deliverers during peak lunch hours and in the busiest districts. While transshipment continues to reduce vehicle miles traveled by deliverers during non-peak hours, it results in longer customer waiting times compared to the benchmark without transshipment as demand decreases.