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Please use this identifier to cite or link to this item: http://purl.umn.edu/253725

Title: Statistical and Economic Evaluation of Time Series Models for Forecasting Arrivals at Call Centers
Authors: Bastianin, Andrea
Galeotti, Marzio
Manera, Matteo
Authors (Email): Bastianin, Andrea (andrea.bastianin@unimi.it)
Keywords: ARIMA
Call Center Arrivals
Loss Function
Seasonality
Telecommunications Forecasting
JEL Codes: C22
C25
C53
D81
M15
Issue Date: 2017-03-03
Series/Report no.: ET
6.2017
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.
URI: http://purl.umn.edu/253725
Institution/Association: Fondazione Eni Enrico Mattei (FEEM)>ET: Economic Theory
Total Pages: 30
Collections:ET: Economic Theory

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