Please use this identifier to cite or link to this item: https://hdl.handle.net/2445/217181
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dc.contributor.authorNestic, Snezana-
dc.contributor.authorAleksic, Aleksandar-
dc.contributor.authorGil Lafuente, Jaime-
dc.contributor.authorCvetic, Tijana-
dc.contributor.authorDuric, Goran-
dc.date.accessioned2024-12-18T11:53:47Z-
dc.date.available2024-12-18T11:53:47Z-
dc.date.issued2022-02-16-
dc.identifier.issn1024-123X-
dc.identifier.urihttps://hdl.handle.net/2445/217181-
dc.description.abstractAs the only constant in business is change, business transformation is essential for adopting new perspectives and business trends. One of the keys to performing successful business transformation is to be fully aware of the current components of the business model. +is research aims to allocate the business model components (BMCs) to defined business model components groups (BMCGs) by developing a new approach that integrates fuzzy sets and heuristic algorithms. +e allocation results enable a comprehensive analysis of business model frameworks and give a good connection to research in the domain of strategic management and business process modeling. For allocation, the decision-makers (DMs) are employing the linguistic terms modeled by the fuzzy sets theory. +e considered problem is stated as an integer programming model where the optimal solution is given by a B&B algorithm. +e model is tested on a sample of forty experts from four different economic sectors.-
dc.format.extent12 p.-
dc.format.mimetypeapplication/pdf-
dc.language.isoeng-
dc.publisherHindawi-
dc.relation.isformatofReproducció del document publicat a: https://doi.org/10.1155/2022/2958519-
dc.relation.ispartofMathematical Problems in Engineering, 2022, vol. 2022, num.2958519, p. 1-12-
dc.relation.urihttps://doi.org/10.1155/2022/2958519-
dc.rightscc-by (c) Nestic, S. et al., 2022-
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/-
dc.sourceArticles publicats en revistes (Empresa)-
dc.subject.classificationAssignació d'actius-
dc.subject.classificationIncertesa-
dc.subject.classificationPresa de decisions (Estadística)-
dc.subject.otherAsset allocation-
dc.subject.otherUncertainty-
dc.subject.otherStatistical decision-
dc.titleThe Allocation of Business Model Components under Presence of Uncertainties by the Branch-and-Bound Method-
dc.typeinfo:eu-repo/semantics/article-
dc.typeinfo:eu-repo/semantics/publishedVersion-
dc.identifier.idgrec721977-
dc.date.updated2024-12-18T11:53:47Z-
dc.rights.accessRightsinfo:eu-repo/semantics/openAccess-
Appears in Collections:Articles publicats en revistes (Empresa)

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