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A new clustering methodology for the analysis of sorted or categorized stimuli

dc.contributor.authorDeSarbo, Wayne S.en_US
dc.contributor.authorJedidi, Kamelen_US
dc.contributor.authorJohnson, Michael Daviden_US
dc.date.accessioned2006-09-11T18:34:15Z
dc.date.available2006-09-11T18:34:15Z
dc.date.issued1991-08en_US
dc.identifier.citationDesarbo, Wayne S.; Jedidi, Kamel; Johnson, Michael D.; (1991). "A new clustering methodology for the analysis of sorted or categorized stimuli." Marketing Letters 2(3): 267-279. <http://hdl.handle.net/2027.42/47082>en_US
dc.identifier.issn0923-0645en_US
dc.identifier.issn1573-059Xen_US
dc.identifier.urihttps://hdl.handle.net/2027.42/47082
dc.description.abstractThis paper introduces a new stochastic clustering methodology devised for the analysis of categorized or sorted data. The methodology reveals consumers' common category knowledge as well as individual differences in using this knowledge for classifying brands in a designated product class. A small study involving the categorization of 28 brands of U.S. automobiles is presented where the results of the proposed methodology are compared with those obtained from KMEANS clustering. Finally, directions for future research are discussed.en_US
dc.format.extent854216 bytes
dc.format.extent3115 bytes
dc.format.mimetypeapplication/pdf
dc.format.mimetypetext/plain
dc.language.isoen_US
dc.publisherKluwer Academic Publishers; Springer Science+Business Mediaen_US
dc.subject.otherEconomics / Management Scienceen_US
dc.subject.otherMarketingen_US
dc.subject.otherCluster Analysisen_US
dc.subject.otherCategorizationen_US
dc.subject.otherSorting Tasksen_US
dc.subject.otherMaximum Likelihood Estimationen_US
dc.titleA new clustering methodology for the analysis of sorted or categorized stimulien_US
dc.typeArticleen_US
dc.subject.hlbsecondlevelSoutheast Asian and Pacific Languages and Culturesen_US
dc.subject.hlbsecondlevelManagementen_US
dc.subject.hlbsecondlevelWest European Studiesen_US
dc.subject.hlbsecondlevelMarketingen_US
dc.subject.hlbsecondlevelEconomicsen_US
dc.subject.hlbtoplevelHumanitiesen_US
dc.subject.hlbtoplevelSocial Sciencesen_US
dc.subject.hlbtoplevelBusinessen_US
dc.description.peerreviewedPeer Revieweden_US
dc.contributor.affiliationumSchool of Business Administration, The University of Michigan, 48109-1234, Ann Arbor, MI, USAen_US
dc.contributor.affiliationumUniversity of Michigan, Ann Arbor, USAen_US
dc.contributor.affiliationotherColumbia University, Manhatta, USAen_US
dc.contributor.affiliationumcampusAnn Arboren_US
dc.description.bitstreamurlhttp://deepblue.lib.umich.edu/bitstream/2027.42/47082/1/11002_2004_Article_BF00554131.pdfen_US
dc.identifier.doihttp://dx.doi.org/10.1007/BF00554131en_US
dc.identifier.sourceMarketing Lettersen_US
dc.owningcollnameInterdisciplinary and Peer-Reviewed


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