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dc.creatorMamonov,Stanislav
dc.creatorTriantoro,Tamilla
dc.date2018-05-01
dc.date.accessioned2019-04-25T12:42:04Z
dc.date.available2019-04-25T12:42:04Z
dc.identifierhttps://scielo.conicyt.cl/scielo.php?script=sci_arttext&pid=S0718-18762018000200103
dc.identifier.urihttp://revistaschilenas.uchile.cl/handle/2250/61315
dc.descriptionAbstract : Diamonds belong to a unique product category whose perceived value is largely dependent on socially constructed beliefs. To explore the degree to which the physical properties of a diamond can be used to predict the diamond price, we perform data mining on a large dataset of loose diamonds scraped from an online diamond retailer. We find that diamond weight, color and clarity are the key characteristics that influence diamond prices. The data mining results also suggest a high degree of subjectivity in diamond pricing that may reflect price obfuscation strategies employed by diamond retailers.
dc.formattext/html
dc.languageen
dc.publisherUniversidad de Talca
dc.relation10.4067/S0718-18762018000200103
dc.rightsinfo:eu-repo/semantics/openAccess
dc.sourceJournal of theoretical and applied electronic commerce research v.13 n.2 2018
dc.subjectSearch costs
dc.subjectPrice obfuscation
dc.subjectDiamond retail
dc.subjectData mining
dc.subjectPricing
dc.subjectRevenue management
dc.titleSubjectivity of Diamond Prices in Online Retail: Insights from a Data Mining Study


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