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 language | English |
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Pages (from-to) | 15-28 |
Number of pages | 14 |
Journal | Journal of Theoretical and Applied Electronic Commerce Research |
Volume | 13 |
Issue number | 2 |
DOIs | |
State | Published - May 2018 |
Keywords
- Data mining
- Diamond retail
- Price obfuscation
- Pricing
- Revenue management
- Search costs