Delay Information in Virtual Queues: A Large-Scale Field Experiment on a Ride-Sharing Platform
26 Pages Posted: 9 Sep 2020 Last revised: 11 Sep 2020
Date Written: September 5, 2020
The growing adoption of virtual queues in the service and retail industries has been greatly accelerated by COVID-19 due to the requirement of social distancing. In collaboration with a major ride-sharing platform, we study how the wait time information (WTI) given by the service provider impacts customers' abandonment behavior in virtual queues; the study was conducted through a large-scale randomized field experiment that included 1,425,745 rides: one-third of the rides received a neutral WTI, one-third received a more optimistic WTI shorter than the neutral WTI (hence less frequent updates), and one-third received a pessimistic WTI (hence more frequent updates). We find 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. We show that this may be 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 becomes dominant: 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
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