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dc.contributor.authorAhmed, Anwar H.
dc.contributor.authorBwisa, Henry M
dc.contributor.authorOtieno, Romanus Odhiambo
dc.date.accessioned2018-11-20T16:00:52Z
dc.date.accessioned2020-02-07T08:38:40Z
dc.date.available2018-11-20T16:00:52Z
dc.date.available2020-02-07T08:38:40Z
dc.date.issued2012
dc.identifier.citationAhmed, A. H., Bwisa, H. M., & Otieno, R. O. (2012). Business Selection using Multi-Criteria Decision Analysis. Int. J. Bus. Commer, 1(5), 64-81.en_US
dc.identifier.urihttps://www.researchgate.net/profile/Romanus_Otieno/publication/268272126_Business_Selection_using_Multi-Criteria_Decision_Analysis/links/5625037308aed8dd19495910.pdf
dc.identifier.urihttp://repository.must.ac.ke/handle/123456789/1293
dc.description.abstractOne of the major challenges facing an entrepreneur in business prioritization entails coming-up with a reliable model that will rank the available opportunities (what type of business to be invested?). Usually, investors have multiple and conflicting criteria to base their selection decision. In this paper we first review some of the criteria used to select business type. We then propose the use of multi-criteria decision analysis (MCDA) models that involves a single decision maker (the potential investor). Specifically, we propose the use of three deterministic families of models i.e. the WSM, WPM and AHP. The models are illustrated with prototypes of the real problem. Later, we propose ways of deriving and estimating the model parameters. Subsequently, we provide a statistical framework of enumerating business types within a catchment area through the use of fallback principal. In our conclusion, we outline the research gaps, propose a modeling framework for the MCDA business selection tool, and give a snap-shot of the menu driven screen for the model.en_US
dc.language.isoenen_US
dc.publisherInternational Journal of Business and Commerceen_US
dc.subjectBusiness selection, Business prioritization and Multi-criteria decision method.en_US
dc.titleBusiness Selection using Multi-Criteria Decision Analysisen_US
dc.typeArticleen_US


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