Modeling Daily Arrivals to a Telephone Call Center

Athanassios N. Avramidis (), Alexandre Deslauriers and Pierre L'Ecuyer
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Athanassios N. Avramidis: GERAD and Département d'Informatique et de Recherche Opérationnelle, Université de Montréal, C.P. 6128, succursale Centre-ville, Montréal, Québec, H3C 3J7 Canada
Alexandre Deslauriers: GERAD and Département d'Informatique et de Recherche Opérationnelle, Université de Montréal, C.P. 6128, succursale Centre-ville, Montréal, Québec, H3C 3J7 Canada
Pierre L'Ecuyer: GERAD and Département d'Informatique et de Recherche Opérationnelle, Université de Montréal, C.P. 6128, succursale Centre-ville, Montréal, Québec, H3C 3J7 Canada

Management Science, 2004, vol. 50, issue 7, 896-908

Abstract: We develop stochastic models of time-dependent arrivals, with focus on the application to call centers. Our models reproduce three essential features of call center arrivals observed in recent empirical studies: a variance larger than the mean for the number of arrivals in any given time interval, a time-varying arrival intensity over the course of a day, and nonzero correlation between the arrival counts in different periods within the same day. For each of the new models, we characterize the joint distribution of the vector of arrival counts, with particular focus on characterizing how the new models are more flexible than standard or previously proposed models. We report empirical results from a study on arrival data from a real-life call center, including the essential features of the arrival process, the goodness of fit of the estimated models, and the sensitivity of various simulated performance measures of the call center to the choice of arrival process model.

Keywords: call center; arrival process; multivariate distribution; doubly stochastic Poisson process; input modeling; correlation (search for similar items in EconPapers)
Date: 2004
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Citations: View citations in EconPapers (52)

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Persistent link: https://EconPapers.repec.org/RePEc:inm:ormnsc:v:50:y:2004:i:7:p:896-908

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