@article{Bastianin:253725,
      recid = {253725},
      author = {Bastianin, Andrea and Galeotti, Marzio and Manera, Matteo},
      title = {Statistical and Economic Evaluation of Time Series Models  for Forecasting Arrivals at Call Centers},
      address = {2017-03-03},
      number = {843-2016-55944},
      series = {ET},
      pages = {30},
      month = {Mar},
      year = {2017},
      abstract = {Call centers' managers are interested in obtaining  accurate forecasts of call arrivals because these are a key  input in staffing and scheduling decisions. Therefore their  ability to achieve an optimal balance between service  quality and operating costs ultimately hinges on forecast  accuracy. We present a strategy to model selection in call  centers which is based on three pillars: (i) a flexible  loss function; (ii) statistical evaluation of forecast  accuracy; (iii) economic evaluation of forecast performance  using money metrics. We implement fourteen time series  models and seven forecast combination schemes on three  series of call arrivals. We show that second moment  modeling is important when forecasting call arrivals. From  the point of view of a call center manager, our results  indicate that outsourcing the development of a forecasting  model is worth its cost, since the simple Seasonal Random  Walk model is always outperformed by other, relatively more  sophisticated, specifications.},
      url = {http://ageconsearch.umn.edu/record/253725},
      doi = {https://doi.org/10.22004/ag.econ.253725},
}