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

Rouba Ibrahim, Han Ye, Pierre L'Ecuyer, Haipeng Shen

Research output: Contribution to journalArticlepeer-review


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.

Original languageEnglish (US)
Pages (from-to)865-874
Number of pages10
JournalInternational Journal of Forecasting
Issue number3
StatePublished - 2016


  • Bayesian
  • Call center arrivals
  • Dependence
  • Dimension reduction
  • Doubly stochastic Poisson
  • Exponential smoothing
  • Fixed-effects
  • Forecasting
  • Marketing events
  • Mixed-effects
  • Seasonality
  • Time series

ASJC Scopus subject areas

  • Business and International Management


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