Subjectivity of diamond prices in online retail: Insights from a data mining study

Stanislav Mamonov, Tamilla Triantoro

Research output: Contribution to journalArticle

Abstract

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.

Original languageEnglish
Pages (from-to)15-28
Number of pages14
JournalJournal of Theoretical and Applied Electronic Commerce Research
Volume13
Issue number2
DOIs
StatePublished - May 2018

Fingerprint

Data mining
Diamonds
Diamond
Retail
Subjectivity
Physical properties
Color
Costs

Keywords

  • Data mining
  • Diamond retail
  • Price obfuscation
  • Pricing
  • Revenue management
  • Search costs

Cite this

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abstract = "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.",
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Subjectivity of diamond prices in online retail : Insights from a data mining study. / Mamonov, Stanislav; Triantoro, Tamilla.

In: Journal of Theoretical and Applied Electronic Commerce Research, Vol. 13, No. 2, 05.2018, p. 15-28.

Research output: Contribution to journalArticle

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AB - 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.

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