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Identifying market segments in beef: Breed, slaughter weight and ageing time implications

dc.contributor.authorDíez Peláez, Jorge 
dc.contributor.authorCoz Velasco, Juan José del 
dc.contributor.authorBahamonde Rionda, Antonio 
dc.contributor.authorSañudo, Carlos
dc.contributor.authorOlleta, J. L.
dc.contributor.authorMacie, S.
dc.contributor.authorCampo, M. M.
dc.contributor.authorPanea, Begoña
dc.contributor.authorAlbertí, P.
dc.date.accessioned2015-04-14T09:09:28Z
dc.date.available2015-04-14T09:09:28Z
dc.date.issued2006
dc.identifier.citationMeat Science, 74(4), p. 667–675 (2006); doi:10.1016/j.meatsci.2006.05.017
dc.identifier.issn0309-1740
dc.identifier.urihttp://hdl.handle.net/10651/30621
dc.description.abstractIn this paper we propose a method to learn the reasons why groups of consumers prefer some beef products to others. We emphasise the role of groups since, from a practical point of view, they may represent market segments that demand different products. Our method starts representing people’s preferences in a metric space; there we are able to define a kernel based similarity function that allows a clustering algorithm to identify significant groups of consumers with homogeneous likes. Finally, in each cluster, we developed, with a support vector machine (SVM), a function that explains the preferences of those consumers grouped in the cluster. The method was applied to a real case of consumers of beef that tasted beef from seven Spanish breeds, slaughtered at two different weights and aged for three different ageing periods. Two different clusters of consumers were identified for acceptability and tenderness, but not for flavour. Those clusters ranked two very different breeds (Asturiana and Retinta) in opposite order. In acceptability, ageing period was appreciated in a different way. However, in tenderness most consumers preferred long ageing periods and heavier to lighter animals
dc.format.extentp. 667-675spa
dc.language.isoengspa
dc.publisherElsevier
dc.relation.ispartofMeat Science, 74(4)spa
dc.rights© 2006 Elsevier
dc.subjectConsumers preferences
dc.subjectClustering
dc.subjectMachine learning
dc.subjectArtificial intelligence
dc.titleIdentifying market segments in beef: Breed, slaughter weight and ageing time implicationsspa
dc.typeinfo:eu-repo/semantics/article
dc.identifier.doi10.1016/j.meatsci.2006.05.017
dc.type.dcmitextspa
dc.relation.publisherversionhttp://dx.doi.org/10.1016/j.meatsci.2006.05.017


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