File Download

There are no files associated with this item.

  Links for fulltext
     (May Require Subscription)
Supplementary

Conference Paper: Forecasting and dynamic updating of uncertain arrival rates to a call center

TitleForecasting and dynamic updating of uncertain arrival rates to a call center
Authors
Issue Date2007
Citation
2007 IEEE International Conference on Service Operations and Logistics, and Informatics, SOLI, 2007 How to Cite?
AbstractMotivated by queueing models and recent empirical studies of call centers, we model call arrival processes as inhomogeneous Poisson processes. Our primary interest lies on forecasting the unobserved intraday call rate profile using the historical call volume data. We develop methods for both interday forecasting and dynamic intraday updating of call arrival rates. Such forecasts are of great importance for effective call center workforce management. Our methods combine the data-driven approach in Shen and Huang (2007) [9] with the model-driven approach in Weinberg et al. (2007) [10]. A Poisson factor model is first formulated to achieve dimension reduction. We then describe how the estimated model can be used to provide interday forecasting as well as intraday updating. Our methods show very promising results in an application to real call center data. © 2007 IEEE.
Persistent Identifierhttp://hdl.handle.net/10722/219588

 

DC FieldValueLanguage
dc.contributor.authorShen, Haipeng-
dc.contributor.authorHuang, Jianhua Z.-
dc.contributor.authorLee, Chihoon-
dc.date.accessioned2015-09-23T02:57:28Z-
dc.date.available2015-09-23T02:57:28Z-
dc.date.issued2007-
dc.identifier.citation2007 IEEE International Conference on Service Operations and Logistics, and Informatics, SOLI, 2007-
dc.identifier.urihttp://hdl.handle.net/10722/219588-
dc.description.abstractMotivated by queueing models and recent empirical studies of call centers, we model call arrival processes as inhomogeneous Poisson processes. Our primary interest lies on forecasting the unobserved intraday call rate profile using the historical call volume data. We develop methods for both interday forecasting and dynamic intraday updating of call arrival rates. Such forecasts are of great importance for effective call center workforce management. Our methods combine the data-driven approach in Shen and Huang (2007) [9] with the model-driven approach in Weinberg et al. (2007) [10]. A Poisson factor model is first formulated to achieve dimension reduction. We then describe how the estimated model can be used to provide interday forecasting as well as intraday updating. Our methods show very promising results in an application to real call center data. © 2007 IEEE.-
dc.languageeng-
dc.relation.ispartof2007 IEEE International Conference on Service Operations and Logistics, and Informatics, SOLI-
dc.titleForecasting and dynamic updating of uncertain arrival rates to a call center-
dc.typeConference_Paper-
dc.description.natureLink_to_subscribed_fulltext-
dc.identifier.doi10.1109/SOLI.2007.4383957-
dc.identifier.scopuseid_2-s2.0-51849129517-

Export via OAI-PMH Interface in XML Formats


OR


Export to Other Non-XML Formats