Multi-criteria analysis using latent class cluster ranking: An investigation into corporate resiliency

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dc.citation.epage13en_US
dc.citation.spage1en_US
dc.citation.volumeNumber148en_US
dc.contributor.authorMistry, J.en_US
dc.contributor.authorSarkis, J.en_US
dc.contributor.authorDhavale, D. G.en_US
dc.date.accessioned2016-02-08T10:58:30Z
dc.date.available2016-02-08T10:58:30Z
dc.date.issued2014en_US
dc.departmentDepartment of Managementen_US
dc.description.abstractIn this paper, we introduce a multi-stage multiple criteria latent class model within a Bayesian framework that can be used to evaluate and rank-order objects based on multiple performance criteria. The latent variable extraction in our methodology relies on Bayesian analysis and Monte Carlo simulation, which uses a Gibbs sampler. Ranking of clusters of objects is completed using the extracted latent variables. We apply the methodology to evaluate the resiliency of e-commerce companies using balanced scorecard performance dimensions. Cross-validation of the latent class model confirms a superior fit for classifying the e-commerce companies. Specifically, using the methodology we determine the ability of different perspectives of the balanced scorecard method to predict the continued viability and eventual survival of e-commerce companies. The novel methodology may also be useful for performance evaluation and decision making in other contexts. In general, this methodology is useful where a ranking of elements within a set, based on multiple objectives, is desired. A significant advantage of this methodology is that it develops weighting scheme for the multiple objective based on intrinsic characteristics of the set with minimal subjective input from decision makers. © 2013 Elsevier B.V.en_US
dc.identifier.doi10.1016/j.ijpe.2013.10.006en_US
dc.identifier.issn0925-5273
dc.identifier.urihttp://hdl.handle.net/11693/26339
dc.language.isoEnglishen_US
dc.publisherElsevieren_US
dc.relation.isversionofhttps://doi.org/10.1016/j.ijpe.2013.10.006en_US
dc.source.titleInternational Journal of Production Economicsen_US
dc.subjectBalanced scorecarden_US
dc.subjectE-businessen_US
dc.subjectGibbs sampleren_US
dc.subjectLatent class modelen_US
dc.subjectMonte Carlo simulationen_US
dc.subjectMultiple criteria decision makingen_US
dc.subjectPerformance measurementen_US
dc.subjectBalanced scorecardsen_US
dc.subjecteBusinessen_US
dc.subjectGibbs samplersen_US
dc.subjectLatent class modelen_US
dc.subjectMultiple criteria decision makingen_US
dc.subjectPerformance measurementsen_US
dc.subjectDecision makingen_US
dc.subjectEquivalence classesen_US
dc.subjectIndustryen_US
dc.subjectMonte Carlo methodsen_US
dc.subjectElectronic commerceen_US
dc.titleMulti-criteria analysis using latent class cluster ranking: An investigation into corporate resiliencyen_US
dc.typeArticleen_US

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