A Bayesian Approach for Modeling and Analysis of Call Center Arrivals

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.

Publication
Proceedings of the 2013 Winter Simulation Conference, 713–723
doubly stochastic Poisson process Bayesian arrival data overdispersion Markov chain Monte Carlo
Xiaowei Zhang

My research interests include AI simulation, reinforcement learning, and stochastic optimization with applications in business operations, finance, and digital economy.