Modeling and forecasting call center arrivals: A literature survey and a case study

Rouba Ibrahim, Han Ye, L’Ecuyer, Pierre and Haipeng Shen

International Journal of Forecasting, 2016, vol. 32, issue 3, 865-874

Abstract: The effective management of call centers is a challenging task, mainly because managers consistently face considerable uncertainty. One important source of this uncertainty is the call arrival rate, which is typically time-varying, stochastic, dependent across time periods and call types, and often affected by external events. The accurate modeling and forecasting of future call arrival volumes is a complicated issue which is critical for making important operational decisions, such as staffing and scheduling, in the call center. In this paper, we review the existing literature on modeling and forecasting call arrivals. We also discuss the key issues for the building of good statistical arrival models. In addition, we evaluate the forecasting accuracy of selected models in an empirical study with real-life call center data. We conclude with a summary of possible future research directions in this important field.

Keywords: Call center arrivals; Forecasting; Time series; Doubly stochastic Poisson; Fixed-effects; Mixed-effects; ARIMA; Exponential smoothing; Bayesian; Dimension reduction; Dependence; Seasonality; Marketing events (search for similar items in EconPapers)
Date: 2016
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (21)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S016920701500151X
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:intfor:v:32:y:2016:i:3:p:865-874

DOI: 10.1016/j.ijforecast.2015.11.012

Access Statistics for this article

International Journal of Forecasting is currently edited by R. J. Hyndman

More articles in International Journal of Forecasting from Elsevier
Bibliographic data for series maintained by Catherine Liu ().