Delay Information in Virtual Queues: A Large-Scale Field Experiment on a Ride-Sharing Platform

Abstract

The growing adoption of virtual queues in the service and retail industries has been greatly accelerated in recent times. In collaboration with a major ride-sharing platform, we study how the wait time information (WTI) – both its initial magnitude and its subsequent progress over time - impacts customers' abandonment behavior in virtual queues. The study was conducted through a randomized field experiment that included 1,425,745 rides: one-third of the rides received a neutral WTI, one-third received an optimistic WTI shorter than the neutral WTI (hence less frequent updates), and one-third received a pessimistic WTI (hence more frequent updates). The underlying wait time did not vary across the three groups. We find that both the magnitude of the initial WTI and the update frequency of the WTI have a significant impact on customer abandonment. Specifically, when adjusting the initial WTI by 1 minute, it did not impact customer abandonment. This is because the magnitude effect of the initial WTI is cancelled out by the opposite update-frequency effect. However, when adjusting the WTI by more than 1 minute, the magnitude effect dominates: when comparing the pessimistic WTI of 4 minutes with the neutral initial WTI of 2 minutes, 5 minutes with 3 minutes, and 8 minutes with 5 minutes, customers' likelihood to abandon increases by 6.2%, 14.1%, and 19.6%, respectively. Similar but opposite effects are found when comparing the optimistic WTI with the neutral WTI. We discuss how firms can use our findings and insights to design and operate better virtual queues.

Keywords: Virtual Queues, Wait Time Information, Customer Abandonment, Field Experiment, Ridesharing Platforms