Order Stacking in On-Demand Delivery Platforms

Abstract

On-demand delivery platforms—such as restaurant delivery services—can "stack" orders, assigning orders from multiple customers to a single driver. While this typically reduces operating costs, it also impacts customers, drivers, and service providers (e.g., restaurants) by increasing delivery times and affecting their utility from participating in the platform. To investigate the implications of order stacking, we develop a model with delay-sensitive customers that endogenizes the decisions of all platform stakeholders. We first find that for an on-demand delivery market to be economically viable, order stacking should not be excessive because stacking may lead to unacceptable delays for customers. Second, it is optimal for the platform to stack some orders as long as customer valuations for the service are not too small; we derive the platform's optimal stacking level and discuss how it depends on various market conditions. Third, customers prefer more order stacking than any other market participant, including the platform, because with order stacking the platform offers a lower price to customers, which ultimately increases both the number of customers participating and their individual utility from the service. Fourth, unless the time to drop off orders is negligible or the number of available drivers is very small, the platform can earn more profits by offering direct (non-stacked) deliveries for customers that live far from the service provider. Consequently, if implemented correctly, order stacking may benefit customers and platforms alike.

Keywords: on-demand services, delivery platforms, sharing economy, order stacking, pricing