The Value of Pooling in Last-Mile Delivery

Last-mile delivery services have become ubiquitous in the recent past. Delivery services for food (eg., DoorDash, Grubhub, Uber Eats) and groceries (eg., Instacart, Cornershop) earned a combined revenue of $25B in 2020, and are expected to exceed $72B in revenues by 2025. The COVID-19 pandemic accelerated the growth of such services by making their value proposition even more attractive. The lower risk of contact coupled with the convenience of ordering from the comfort of their homes led to widespread customer adoption. Even so, most last-mile delivery services are not profitable. The high cost of delivery is cited as the major cause of losses. Thus, analyzing the factors influencing delivery costs is crucial for understanding the long-term viability of these services. The pooling of orders is a critical source of efficiency in last-mile delivery. We propose a queuing-based spatial model for the delivery process to analyze the value created by pooling. We demonstrate how the trade-off between delivery times and the cost of delivery, mediated by the extent of pooling, dictates which services will be economically viable. Our simulation study of a typical grocery delivery service in Los Angeles, California suggests that delivery times of less than 1 hour are unprofitable for most regions in the US. We find that driver wages account for 90% of the delivery cost. We also discuss the potential impact of technological innovations such as automated delivery and labor regulations on the profitability of last-mile delivery services.