Prioritization in the Presence of Self-ordering Opportunities in Omnichannel Services

Abstract

Motivated by the popularity of mobile-order-and-pay applications, especially in fast-casual food restaurants and coffee shops, we study omnichannel service systems—where customers can employ mobile applications for self-ordering—with respect to sojourn times, throughput, and social welfare. Our models are two-stage queues with two customer classes: Walk-ins and mobiles. We identify Pareto efficient prioritization policies, highlighting trade-offs between each class’s mean sojourn times. We allow customers to make strategic joining decisions based on their anticipated delays under an information structure where walk-ins observe partial queue length information. We draw from a wide array of techniques, including steady-state, transient, busy period, hitting-time analyses, and matrix analytic methods. We showcase the significance of prioritization on the system throughput and social welfare. We demonstrate settings where a traditional service system’s (typically beneficial) transformation to an omnichannel reduces throughput. Our analysis highlights the importance of prioritization policy choice for an efficient transition to an omnichannel service system. The throughput-optimal policy choice highly depends on the operational parameters and customer patience levels; implementing a wrong policy can yield a significant loss in throughput and profitability.