Title :
A Bayesian approach for modeling and analysis of call center arrivals
Author_Institution :
Dept. of Ind. Eng. & Logistics Manage., Hong Kong Univ. of Sci. & Technol., Hong Kong, China
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.
Keywords :
Monte Carlo methods; call centres; parameter estimation; stochastic processes; Bayesian approach; Markov chain Monte Carlo method; Poisson process; call arrival process; call center arrivals; parameter estimation; stochastic Poisson model; Analytical models; Approximation methods; Bayes methods; Markov processes; Random variables; Uncertainty;
Conference_Titel :
Simulation Conference (WSC), 2013 Winter
Conference_Location :
Washington, DC
Print_ISBN :
978-1-4799-2077-8
DOI :
10.1109/WSC.2013.6721464