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dc.creatorDecker,Reinhold
dc.creatorScholz,Sören W
dc.date2009-12-01
dc.date.accessioned2019-04-25T12:41:25Z
dc.date.available2019-04-25T12:41:25Z
dc.identifierhttps://scielo.conicyt.cl/scielo.php?script=sci_arttext&pid=S0718-18762009000300005
dc.identifier.urihttp://revistaschilenas.uchile.cl/handle/2250/61085
dc.descriptionToday, more and more companies are providing web-based product configuration systems in order to better meet individual customer preferences. In many cases, pre-defined product specifications are additionally offered to facilitate the corresponding choice decisions. Against this background, we present a Poisson regression approach for analyzing customer preferences and a genetic algorithm for determining preference-based default products. The basis for this is transaction data, as they are automatically generated when configuring a product online. The potentials of the suggested methodology are demonstrated by means of two case studies referring to different product categories.
dc.formattext/html
dc.languageen
dc.publisherUniversidad de Talca
dc.relation10.4067/S0718-18762009000300005
dc.rightsinfo:eu-repo/semantics/openAccess
dc.sourceJournal of theoretical and applied electronic commerce research v.4 n.3 2009
dc.subjectCustomization
dc.subjectGenetic Algorithm
dc.subjectPoisson Regression
dc.subjectPreference Analysis
dc.subjectProduct Configuration
dc.subjectWeb Usage Data
dc.titlePreference Analysis and Default Optimization in Web-based Product Configuration Systems


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