Please use this identifier to cite or link to this item: https://doi.org/10.1057/palgrave.jors.2602100
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dc.titleA differentiated service scheme to optimize website revenues
dc.contributor.authorOu, J.
dc.contributor.authorParlar, M.
dc.contributor.authorSharafali, M.
dc.date.accessioned2013-10-09T03:26:37Z
dc.date.available2013-10-09T03:26:37Z
dc.date.issued2006
dc.identifier.citationOu, J., Parlar, M., Sharafali, M. (2006). A differentiated service scheme to optimize website revenues. Journal of the Operational Research Society 57 (11) : 1323-1340. ScholarBank@NUS Repository. https://doi.org/10.1057/palgrave.jors.2602100
dc.identifier.issn01605682
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/44091
dc.description.abstractWe consider a website host server with web quality of service (QoS) capabilities to offer differentiated services. A quantitative modelling framework is set up to analyse the economic benefits of differentiated services and to build optimization models for managing the website host's connection bandwidth to the Internet (which is assumed to be the bottleneck factor determining the QoS). Three models are formulated corresponding to three operational scenarios to provide differentiated services. The first is for the marketing manager to classify visit requests as premium or basic when the information technology (IT) manager has already reserved bandwidths for the two classes, and the second is for the IT manager to allocate the total available bandwidth to each class when the marketing manager has already designated which visit requests are premium and which are basic. The third is for the joint optimization of request classification and bandwidth allocation when centralized coordination is possible. Analytic results are obtained for a special case that corresponds to very impatient customers requesting large amounts of data. Qualitative insights gained and numerical results obtained strongly support the implementation of differentiated services. More interestingly, the decentralized models that use simple and rough-cut rules yield solutions almost as good as the joint optimization model. © 2006 Operational Research Society Ltd. All rights reserved.
dc.description.urihttp://libproxy1.nus.edu.sg/login?url=http://dx.doi.org/10.1057/palgrave.jors.2602100
dc.sourceScopus
dc.subjectBandwidth allocation
dc.subjectNon-convex optimization
dc.subjectOR modelling
dc.subjectQuality of service
dc.subjectQueueing theory
dc.typeArticle
dc.contributor.departmentDECISION SCIENCES
dc.description.doi10.1057/palgrave.jors.2602100
dc.description.sourcetitleJournal of the Operational Research Society
dc.description.volume57
dc.description.issue11
dc.description.page1323-1340
dc.description.codenJORSD
dc.identifier.isiut000241588500007
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