Wednesday, March 18, 2020
Mining Building, Room 128
170 College St.
Speaker: Prof. Ruba Ibrahim, School of Management, University College London
Title: A General Framework to Compare Announcement Accuracy: Static vs LES-based Announcement
Abstract: Service providers often share delay information, in the form of delay announcements, with their customers. In practice, simple delay announcements, such as average waiting times or a weighted average of previously delayed customers, are often used. Our goal in this paper is to gain insight into when such announcements perform well. Specifically, we compare the accuracies of two announcements: (i) a static announcement which does not exploit real-time information about the state of the system, and (ii) a dynamic announcement, specifically the last-to-enter-service (LES) announcement, which equals the delay of the last customer to have entered service at the time of the announcement. We propose a novel correlation-based approach which is theoretically appealing because it allows for a comparison of the accuracies of announcements across different queueing models, including multi-class models with a priority service discipline. It is also practically useful because estimating correlations is much easier than fitting an entire queueing model. Using a combination of queueing-theoretic analysis, real-life data analysis, and simulation, we analyze the performance of static and dynamic announcements, and derive an appropriate weighted average of the two which we demonstrate has a superior performance using both simulation and data from a call center.
(Joint work with Achal Bassamboo, Kellogg School of Management, Northwestern University).
Bio: Rouba Ibrahim is an associate professor at the School of Management of University College London, London, U.K. Her research and teaching interests focus on service operations using both queueing theoretic and data-analytic techniques. She is an Associate Editor of Management Science, Operations Research, M&SOM, and IISE Transactions. She holds a PhD degree in Operations Research from Columbia University, a Master’s degree in Applied Mathematics from the State University of New York at Stony Brook, and a BSc in Mathematics from the American University of Beirut.