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http://dx.doi.org/10.5850/JKSCT.2020.44.6.1053

Sales Pattern and Related Product Attributes of T-shirts  

Chae, Jin Mie (School of Global Fashion Industry, Hansung University)
Kim, Eun Hie (Oracle Korea)
Publication Information
Journal of the Korean Society of Clothing and Textiles / v.44, no.6, 2020 , pp. 1053-1069 More about this Journal
Abstract
This study examined the sales pattern relationship with respect to product attributes to propose sales forecasting for fashion products. We analyzed 537 SKU sales data of T-shirts in the domestic sports brand using SAS program. The sales pattern of fashion products fluctuated and were influenced by exogenous factors; therefore, we removed the influence of exogenous factors found to be price discounts and holiday effects as a result of regression analysis. In addition, it was difficult to predict sales using the sales patterns of the same product since fashion products were released as new products every year. Therefore, the forecasting model was proposed using sales patterns of related product attributes when attributes were considered descriptive variables. We classified sales patterns using K-means clustering in order to explain the relationship between sales patterns and product attributes along with creating a decision tree classifier using attributes as input and sales patterns as output. As a result, the sales patterns of T-shirts were clustered into six types that featured the characteristic shape of peak and slope. It was also associated with the combination of product attributes and their values in regards to the proposed sales pattern prediction model.
Keywords
Sales pattern; Product attributes; Exogenous factor; K-means clustering; Decision tree classifier;
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