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Prediction of Product Life Cycle Using Data Mining Algorithms : A Case Study of Clothing Industry

데이터마이닝 알고리즘을 이용한 제품수명주기 예측 : 의류산업 적용사례

  • Lee, Seulki (School of Industrial Management Engineering, Korea University) ;
  • Kang, Ji Hoon (School of Industrial Management Engineering, Korea University) ;
  • Lee, Hankyu (School of Industrial Management Engineering, Korea University) ;
  • Joo, Tae Woo (School of Industrial Management Engineering, Korea University) ;
  • Oh, Shawn (Fashion Business of Samsung Everland Inc.) ;
  • Park, Sungwook (Fashion Business of Samsung Everland Inc.) ;
  • Kim, Seoung Bum (School of Industrial Management Engineering, Korea University)
  • 이슬기 (고려대학교 산업경영공학과) ;
  • 강지훈 (고려대학교 산업경영공학과) ;
  • 이한규 (고려대학교 산업경영공학과) ;
  • 주태우 (고려대학교 산업경영공학과) ;
  • 오시연 (삼성에버랜드 패션사업부) ;
  • 박성욱 (삼성에버랜드 패션사업부) ;
  • 김성범 (고려대학교 산업경영공학과)
  • Received : 2014.01.06
  • Accepted : 2014.05.17
  • Published : 2014.06.15

Abstract

Demand forecasting plays a key role in overall business activities such as production planning, distribution management, and inventory management. Especially, for a fast-changing environment of the clothing industry, logical forecasting techniques are required. In this study, we propose a procedure to predict product life cycle using data mining algorithms. The proposed procedure involves three steps : extracting key variables from profiles, clustering, and classification. The effectiveness and applicability of the proposed procedure were demonstrated through a real data from a leading clothing company in Korea.

Acknowledgement

Supported by : 한국연구재단, 지식경제부

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