Information Visibility in Omnichannel Queues

Abstract

Omnichannel system is a common operation strategy which provides multiple ways for customers to experience the business. One feature of such system is the information heterogeneity across channels. For example, to customers, the queue length in the physical store is visible, while the queue length in the online ordering channel is invisible. We study customers’ decision making in an omnichannel system with partially observable queue. In such system, customers only observe the length of visible queue. In particular, we examine partially observable queueing models with two types of disciplines: (1) FCFS; (2) visible-class priority. With fully observable system as a benchmark, we disentangle the performance difference between any partially observable system and the benchmark system into three effects: trick, shift and scare-away. We find that when market sizes under fully and partially observable systems are comparable, partially observable system generates higher throughput if customers are not scared away by invisibility. Surprisingly, even with less information, partially observable system can have higher social welfare when the invisible arrival rate is high. In that case, the customers are scared away and the system becomes less congested.