Abstract
The Poisson process has been an integral part of many models for the arrival process to a telephone call centers. However, several publications in recent years suggest the presence of a significant ‘‘overdisperson’’ relative to the Poisson process in real-life call center arrival data. In this paper, we study the overdispersion in the context of ‘‘heavy traffic’’ and identify a critical factor that characterizes the stochastic variability of the arrivals to their averages. We refer to such a factor as the scaling parameter and it potentially has a profound impact on the design of staffing rules. We propose an new model to capture the scaling parameter in this paper.
Xiaowei Zhang
Associate Professor
My research research focuses on methodological advances in stochastic simulation and optimization, decision analytics, and reinforcement learning, with applications in service operations management, financial technology, and digital economy.