A Bayesian Approach for Modeling and Analysis of Call Center Arrivals

Dec 10, 2013·
Xiaowei Zhang
Xiaowei Zhang
· 0 min read
DOI
Abstract
The Poisson process has been widely used in the literature to model call center arrivals. In recent years, however, there have been empirical studies suggesting the call arrival process has significant non-Poisson characteristics. In this paper, we introduce a new doubly stochastic Poisson model for call center arrivals and develop a Bayesian approach for the parameter estimation via the Markov chain Monte Carlo method. The model can well capture the call arrival process as illustrated by a case study.
Type
Publication
Proceedings of the 2013 Winter Simulation Conference, 713–723
publications
Doubly Stochastic Poisson Process Bayesian Arrival Data Overdispersion Markov Chain Monte Carlo
Xiaowei Zhang
Authors
Xiaowei Zhang
I am an Associate Professor at HKUST, jointly appointed in the Department of Industrial Engineering and Decision Analytics and the Department of Economics, and the Academic Director of the MSc in FinTech program. I serve as an Associate Editor for several leading journals in the field, including Management Science, Operations Research, Navel Research Logistics, and Queueing Systems.