Forecasting Call Center Arrivals: Fixed-Effects, Mixed-Effects, and Bivariate Models

• 成果类型: Article
• 署名作者: Ibrahim, Rouba; L'Ecuyer, Pierre
• 署名单位: University of London; University College London; Universite de Montreal
• 刊物名称: M&SOM-MANUFACTURING & SERVICE OPERATIONS MANAGEMENT
• ISSN/ISSBN: 1523-4614
• DOI: 10.1287/msom.1120.0405
• 发表日期: 2013
• 页码: 72-85
• 关键词: Forecasting; arrival process; dynamic updating; correlation; Call centers

摘要

We consider different statistical models for the call arrival process in telephone call centers. We evaluate the forecasting accuracy of those models by describing results from an empirical study analyzing real-life call center data. We test forecasting accuracy using different lead times, ranging from weeks to hours in advance, to mimic real-life challenges faced by call center managers. The models considered are (i) a benchmark fixed-effects model that does not exploit any dependence structures in the data; (ii) a mixed-effects model that takes into account both interday (day-to-day) and intraday (within-day) correlations; and (iii) two new bivariate mixed-effects models, for the joint distribution of the arrival counts to two separate queues, that exploit correlations between different call types. Our study shows the importance of accounting for different correlation structures in the data.