- Volume 40 Issue 3
DOI QR Code
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
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.
Supported by : 한국연구재단, 지식경제부
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