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Project outcome classification with imprecise criteria information
Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
2013 (English)In: International Journal of Applied Decision Sciences, ISSN 1755-8085, Vol. 6, no 4, 372-387 p.Article in journal (Refereed) Published
Abstract [en]

A case in which managers have to make project outcome classification decisions with uncertainty in independently related criteria values is considered in this paper. A multi-criteria decision model is developed in this paper by selecting methods which delved into data analysis to help managers make informed classification decisions. Uncertainty in the criteria values is resolved using linear programming which enables managers to know the profit outcome of their projects for efficient resource allocation. The classification scheme from the linear programming process is used as predefined classification inputs for use in the Utilities Additives Discriminants(UTADIS) method, which further produces a classification model. The analysis presented a no misclassification error in the predefined classifications from the linear programming and the classifications in the UTADIS method, thus further boosting the confidence managers can entrust in the resulting classification model.

Place, publisher, year, edition, pages
2013. Vol. 6, no 4, 372-387 p.
Keyword [en]
multi-criteria, classification, project outcomes, imprecision, linear programming
National Category
Economics and Business Information Systems, Social aspects
Research subject
Computer and Systems Sciences
URN: urn:nbn:se:su:diva-92552DOI: 10.1504/IJADS.2013.056867OAI: diva2:639774
Available from: 2013-08-09 Created: 2013-08-09 Last updated: 2014-02-10Bibliographically approved

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Laryea, Rueben
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