Service Systems with Dependent Service and Patience Times

Department of Organisation Management    2018-01-18

Service Systems with Dependent Service and Patience Times

Speaker: Allen Wu Chenguang, PhD candidate, Industrial Engineering and Management Science, Northwestern University

Host: Wei Lai, PhD of ACEM

Time: Jan 22, 2018, Monday, 10:00-11:30

Venue: A303 Antai College Building


Motivated by recent empirical evidence, we consider a large service system in which the patience time of each customer depends on his service requirement. Our goal is to study the impact of such dependence on key performance measures, such as expected waiting times and average queue length, as well as on optimal capacity decisions. Since the dependence structure renders exact analysis intractable, we employ a stationary fluid approximation that is based on the entire joint distribution of the service and patience times. Our results show that even moderate dependence has significant impacts on system performance, so considering the patience and service times to be independent when they are in fact dependent is futile. We further demonstrate that Pearson’s correlation coefficient, which is commonly used to measure and rank dependence, is an insufficient statistic, and that the entire joint distribution is required for comparative statics. Thus, we propose a novel framework, incorporating the fluid model with bivariate dependence orders and copulas, to study the impacts of the aforementioned dependence. We then demonstrate how that framework can be applied to facilitate revenue optimization when staffing and abandonment costs are incurred. Finally, the effectiveness of the fluid-based approximations and optimal-staffing prescriptions is demonstrated via simulations.


Allen Wu is a PhD candidate at Industrial Engineering and Management Science, Northwestern University, United States. He received his bachelor degree in math from Shanghai Jiao Tong University, China. His research interests include service operations, consumer behavior, revenue management and applied probability. His recent research focuses on modeling and analyzing fundamental dependencies in service systems. His research has appeared on leading journal Management Science.