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讲座:Wait Time Information in Virtual Queues

发布者:人力资源办公室    发布时间:2021-11-05

题 目:Wait Time Information in Virtual Queues

嘉 宾:Yiming Zhang, PhD candidate, University of Washington

主持人:花成  助理教授  上海交通大学安泰经济与管理学院

时 间:2021年11月6日(周六) 09:00-10:30

地 点:腾讯会议

 (校内师生如需会议号和密码,请发送电邮至xuziqing@sjtu.edu.cn获取) 

内容简介

Virtual queues are systems that allow customers to keep their places in a queue without physically standing there. In such a queue, waiting customers feel the progress of the queue only through the information displayed to them. My job talk focuses on the optimization of WTI - in terms of what delay information should be displayed and how to do that thoughtfully - for virtual queue providers to improve both the customer wait experience and the system performance.

In the first part of my job talk, we examined how WTI - both its initial magnitude and its subsequent progress - impacted customers’ abandonment behavior in virtual queues. The study involved a randomized field experiment on a major ride-sharing platform; one-third of the rides received a neutral WTI, one-third received an optimistic WTI lower than the neutral WTI (and hence less frequently updated), and one-third received a pessimistic WTI higher than the neutral WTI (and thus more frequently updated). We show that both the magnitude of the initial WTI and the update frequency of the WTI significantly impacted customer abandonment, albeit in opposite directions; a higher initial WTI increased customer abandonment (the magnitude effect) while more frequent updates decreased customer abandonment (the update-frequency effect). Their combined effect was more nuanced, and we future explored the real-time trade-off between the magnitude effect and the update- frequency effect. We show these findings to be robust to the parametric model assumption, the potential customer short-term learning, the queue position changes, etc.

In the rest of my job talk, I would focus on the granularity of WTI. When informing customers about their estimated wait, some firms provide highly granular WTI with a point estimate (e.g., “Your wait time is 4 minutes”), while others provide less granular WTI with intervals (e.g., “Your wait time is 3 - 5 minutes”). We studied how the granularity of WTI impacted customers’ abandonment and identified three factors that would impact customer’s abandonment in virtual queues.

演讲人简介

Yiming Zhang is a fifth-year PhD candidate in operations management at the Foster School of Business, University of Washington. Before joining the PhD program, he received his bachelor’s degree in Statistics from University of Science and Technology of China. His current research focuses on data-driven service operations and behavioral operations management. He works closely with the industry and studies his research questions through designing complex field experiments and analyzing large and highly granular data. Specifically, He focuses on virtual queue design through optimizing wait time information (WTI) and real-time wait compensation (RWC) provided to customers while waiting. His work on WTI is accepted by Management Science, Fast Track, and receives several awards from INFORMS and CSAMSE Annual Conferences.

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