디자인 특성에 따른 니트 패션 트렌드의 주기 분석Analysis of Fashion Design Characteristics and Cycles of Knit Fashion Trends
- Other Titles
- Analysis of Fashion Design Characteristics and Cycles of Knit Fashion Trends
- Authors
- 고순영; 박영선; 박명자
- Issue Date
- Dec-2010
- Publisher
- 복식문화학회
- Keywords
- knit fashion trend(니트 패션 트렌드); fashion cycle(패션 사이클); knitwear(니트웨어); fashion design characteristics(패션 디자인 특성); short-term prediction(단기 예측)
- Citation
- 복식문화연구, v.18, no.6, pp 1274 - 1290
- Pages
- 17
- Indexed
- KCI
- Journal Title
- 복식문화연구
- Volume
- 18
- Number
- 6
- Start Page
- 1274
- End Page
- 1290
- URI
- https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/203324
- DOI
- 10.29049/rjcc.2010.18.6.1274
- ISSN
- 1226-0401
2383-6334
- Abstract
- This study analyzed the design elements and fashion images of women's knitwear in collections of Paris, Milan, London and New York between 2003 and 2008, and examined knitwear trends in an effort to verify whether knitwear trends are repeated in certain cycles, whether they show complicated patterns in cycles and yet occur in quasi cycles, or whether they occur non-periodically in complicated forms of chaotic cycles. Trend cycle analysis results are deemed to identify the time series attribute of knit fashions. It also sought to categorize the attribute of various factors influencing knitwear trends with a view to determining relevancy between design elements, and to present the direction of predicting knitwear fashion trends and the progression of short-term knitwear trends. This study reached the following conclusion. According to design elements or fashion images, knitwear fashion trends occur in cycles, quasi cycles, non-periodical cycles. These cyclic characteristics can be used as scientific data for planning knitwear products. The study confirmed close relevancy between fashion images and fashion elements. It identified close relevancy between designs with similar fashion elements and images through coordinates by year and season, and it is possible to make short-term prediction of trend direction through the flow of coordinates. Time series data were insufficient, thereby making it difficult to perfectly verify chaos indices and giving limitations to this study. A study with more time series data will produce a more effective method of predicting and using knitwear fashion trends.
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- 서울 자연과학대학 > 서울 수학과 > 1. Journal Articles

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