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dc.contributor.authorBecker, Denis
dc.contributor.authorGaivoronski, Alexei A.
dc.contributor.authorNesse, Per Jonny
dc.date.accessioned2019-03-13T09:34:03Z
dc.date.available2019-03-13T09:34:03Z
dc.date.created2018-09-18T14:08:20Z
dc.date.issued2018
dc.identifier.citationTransactions on Emerging Telecommunications Technologies. 2018, 30 (1), .nb_NO
dc.identifier.issn1124-318X
dc.identifier.urihttp://hdl.handle.net/11250/2589811
dc.description.abstractThis paper represents a model that supports the choice of efficient service portfolios at a cloud service broker. Among the many types of different cloud service brokers, we focus on a firm that offers service bundles that are composed from different services of different internet software providers. The necessary integration, aggregation, and customization of services can be time consuming and costly. Whenever the cloud broker can choose from many service combinations, but has limited human resources with critical time to market, it is essential to prioritize some of the service bundles, markets, services, and internet software providers. The purpose of this paper is to facilitate this kind of decision. Moreover, both the time and resources required for creating service offerings and the customers' demand for these service bundles are subject to uncertainty. Because of this uncertainty, a cloud broker needs to be guided to potential service portfolios that give the best trade‐off between risk and profitability. Our model helps the decision maker to identify efficient service portfolios, ie, service portfolios that for a given risk have the highest profitability or for a given profitability have the lowest risk. Our paper shows the application of this model to a cloud broker that mediates mainly software as a service bundled with mobile subscriptions for telephony (calling and messaging) and internet access. The model is inspired by the ideas from financial portfolio optimization and product‐mix decisions under scarce resources. The model corresponds to a linear stochastic optimization problem with an objective function that balances risk and profitability.nb_NO
dc.language.isoengnb_NO
dc.publisherWileynb_NO
dc.titleOptimization-based profitability management tool for cloud brokernb_NO
dc.typeJournal articlenb_NO
dc.typePeer reviewednb_NO
dc.description.versionacceptedVersionnb_NO
dc.source.pagenumber15nb_NO
dc.source.volume30nb_NO
dc.source.journalTransactions on Emerging Telecommunications Technologiesnb_NO
dc.source.issue1nb_NO
dc.identifier.doi10.1002/ett.3514
dc.identifier.cristin1610626
dc.description.localcodeLocked until 16.9.2019 due to copyright restrictions. This is the peer reviewed version of an article, which has been published in final form at [https://doi.org/10.1002/ett.3514]. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Self-Archiving.nb_NO
cristin.unitcode194,60,10,0
cristin.unitcode194,60,25,0
cristin.unitnameNTNU Handelshøyskolen
cristin.unitnameInstitutt for industriell økonomi og teknologiledelse
cristin.ispublishedtrue
cristin.fulltextoriginal
cristin.fulltextpostprint
cristin.qualitycode1


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