• 한국의류학회지
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• 제46권6호
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• pp.963-986
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• 2022

This article surveys the fashion forecasting industry in Korean domestic markets. With the rise of new media and devices with high technology, the paradigm of fashion trends forecasting systems has dramatically changed. New perspectives of trend forecasting are required to understand the trend flow and consumer behavior of the MZ generation. The research questions are as follows: 1) Major trend forecasting companies studied the development of their strategies and new forecasting methods. 2) The consumers' needs in the domestic market were analyzed. The influence of the trend companies' forecasting on the market was investigated. The results are as follows: 1) International trend forecasting significantly affected the domestic market. The concordance rate between consumers' online searches about fashion trends was approximately 70.14%. The match rate by category is as follows: The highest rate, 85.06% is from pattern and print, color is 83.92%, the item is 80.39%, and style is 54.32%. 2) Specialized information such as the Pantone color chart is being widely consumed, leading to a trend among the masses. 3) The Korean-specific socio-cultural background has an impact on domestic trends.

• 패션비즈니스
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• 제15권6호
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• pp.176-203
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• 2011

In today's intensifying global competition, Korean fashion industry is relying on only qualitative data for feasibility study of future projects and developmental plan. This study was conducted in order to support establishment of a scientific and rational management system that reflects market demand. First, fashion market size was limited to the total amount of expenditure for fashion clothing products directly purchased by Koreans for wear during 6 months in spring and summer and 6 months in autumn and winter. Fashion market forecasting model was developed using statistical forecasting method proposed by previous research. Specifically, time series model was selected, which is a verified statistical forecasting method that can predict future demand when data from the past is available. The time series for empirical analysis was fashion market sizes for 8 segmented markets at 22 time points, obtained twice each year by the author from 1998 to 2008. Targets of the demand forecasting model were 21 research models: total of 7 markets (excluding outerwear market which is sensitive to seasonal index), including 6 segmented markets (men's formal wear, women's formal wear, casual wear, sportswear, underwear, and children's wear) and the total market, and these markets were divided in time into the first half, the second half, and the whole year. To develop demand forecasting model, time series of the 21 research targets were used to develop univariate time series models using 9 types of exponential smoothing methods. The forecasting models predicted the demands in most fashion markets to grow, but demand for women's formal wear market was forecasted to decrease. Decrease in demand for women's formal wear market has been pronounced since 2002 when casualization of fashion market intensified, and this trend was analyzed to continue affecting the demand in the future.

• 산업경영시스템학회지
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• 제35권1호
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• pp.66-78
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• 2012

This paper proposes a computation model of the quantity supplied to optimize inventory costs for the fast fashion. The model is based on a forecasting, a store and production capacity, an assortment planning and quick response model for fast fashion retailers, respectively. It is critical to develop a standardized business process and mathematical model to respond market trends and customer requirements in the fast fashion industry. Thus, we define a product supply model that consists of forecasting, assortment plan, store capacity plan based on the visual merchandising, and production capacity plan considering quick response of the fast fashion retailers. For the forecasting, the decomposition method and multiple regression model are applied. In order to optimize inventory costs. A heuristic algorithm for the quantity supplied is designed based on the assortment plan, store capacity plan and production capacity plan. It is shown that the heuristic algorithm produces a feasible solution which outperforms the average inventory cost of a global fast fashion company.

• 복식
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• 제31권
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• pp.33-46
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• 1997

The purpose of this study was to investigate color planning method for apparel fashion de-sign and to present the method of analysis of green color. Theoretical backgrouds of color planning for fashion design were scrutinized by documentary studies Fashion color planning has been developed through 4 steps: analysis of color environment analysis of color psy-chology presentation of coordination appli-cation to fashion design. Green color environment consisted of mar-ket informations and forecast informations The former were collected by color samples which were used for women's apparel of national brands from '93 spring/summer to '96 spring/summer and the latter were analyzed by fashion forecasting books. Green color psy-chology was investigated through the docu-mentary studiess. image of green color and these expressed in fashion were revealed through documentary studies. The results of this study were as follow: 1. 117 green color samples were collected from domestic womens brand. The character-istic of samples were the yellow green in hue and pale light bright in tone. forecast infor-mation was collected through fashion forecasting books from abroad and adaption of forecast information was investigated by mak-ing a comparison forecasting information be-tween market information. In consequence national market colors reflected the forecast information in concurrence with the character-istic colors of national women's apparel. 2. Affirmative images of green were nature youth health and abundance and negative images were extraordinary misfortune wind-fall. in these images nature youth and health were mostly used in fashion.

• 한국의류산업학회지
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• 제10권6호
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• pp.926-935
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• 2008

The field of textile and fashion is regard to be sensitive to trend, however, the professional fashion information planning company for trend forecasting has not settled down in Korea. This study was designed to propose systemizing for fashion trend information planning in domestic fashion information service market. The empirical research was conducted by analysing in-depth interview data and news-scrap contents about each fashion information planning company. The result are as follows; First, fashion information service showed a little difference according to the type of fashion information companies, but they provided not only general fashion trends but also external market environmental information, survey-based consumer information and various segmented market research reports including academic information. Second, the fashion information planning process is largely divided into 3 stages; trend analysis, trend forecasting, trend application. The trend application step is the stage which connects the fashion information service industry to the fashion business. Thirdly, as a result of the competitive power evaluation for fashion information planning, the domestic fashion information planning companies came to reveal the fact that the possibility of carrying out and information analysis power were weak, however, how to present trend information had a relatively competitive. Consequently, this study is expected to play a role in understanding the importance of fashion trend information, and further ahead it would be helpful to organize the curriculum of fashion information planning subject in order to educate the future fashion executives.

• 한국의류산업학회지
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• 제22권5호
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• pp.551-560
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• 2020

Due to the nature of fashion design that responds quickly and sensitively to changes, accurate forecasting for upcoming fashion trends is an important factor in the performance of fashion product planning. This study analyzed the major phenomena of fashion trends by introducing text mining and a big data analysis method. The research questions were as follows. What is the key term of the 2010SS~2019FW fashion trend? What are the terms that are highly relevant to the key trend term by year? Which terms relevant to the key trend term has shown high frequency in news articles during the same period? Data were collected through the 2010SS~2019FW Pre-Trend data from the leading trend information company in Korea and 45,038 articles searched by "fashion+material" from the News Big Data System. Frequency, correlation coefficient, coefficient of variation and mapping were performed using R-3.5.1. Results showed that the fashion trend information were reflected in the consumer market. The term with the highest frequency in 2010SS~2019FW fashion trend information was material. In trend information, the terms most relevant to material were comfort, compact, look, casual, blend, functional, cotton, processing, metal and functional by year. In the news article, functional, comfort, sports, leather, casual, eco-friendly, classic, padding, culture, and high-quality showed the high frequency. Functional was the only fashion material term derived every year for 10 years. This study helps expand the scope and methods of fashion design research as well as improves the information analysis and forecasting capabilities of the fashion industry.

• 복식
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• 제18권
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• pp.321-337
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• 1992

Fashions are constantly subject to change, so that forecasting trends in fashion is very difficult and the forecasting is very important. The reason is that forecasting is identifying a hot trend for the next days' business and projecting the future. The purpose of this study is to suggest the realistic forecasting theory identify fashion trends at present, further forecast fashion trends to 1995. For this study, historical models (th historical resurrection model, the historical continuity model) and the art movement model among the behavioral science models which was suggested in 1986 by Geoge B.Sproles were selected. According to this study, was exhibited. This curve was resulted from relation between 1980s fashion trends and the behavioral science models of fashion. Fashion trends to 1995 through will be followings; 1. Body Conscious look as one of the characteristics of modern fashion will bi continued throughout 1990s' fashion trends. 2. The attraction of Mini style was started from the middle of 1980s, recently gets near micro mini and super shouts, These are representative of the historical continuity model. 3. Mini look as revivals of '60s in early 1990s fashion trends. This phenomenon identifies that "Fashion is repetition" 4. When Mini look and super shorts reach, will not progress any more. In this time, will bi seen transfer of style be using classic style. Tat is modern classic will be appeared. also this condition is same from late 1960s to early 1970s. In view of the historical base, the action of the varieted pants will be prominent. 5. Fashion trends which passed through this process will transfer from young look to elegant look. In this time, designers will retrospect '30s and '50s fashion trends, and then will design modern feminine look. 6. Ethnic look, the fashion trend after that condition will be accelated feminine look. This look with the feminine look will reveal rich, colorful, elegance feminine image. 7. In 1980s, activity and function in clothes were demanded. The clothes which are considered these condition will be demanded continuously. 8. The variety of fashion will appear as mixmode and new coordinate look in a clothes simultaneously in fashion of '90s. And these looks will creat mixed beauty. 9. Pop art, op art, graphic art will be not only development of textile but also movement of fashion soul in 1990s. The fashion behavior will be continuously scientificated.

• 한국의류학회지
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• 제46권5호
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• pp.868-889
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• 2022

Fashion companies are using a big data approach as a key strategic analysis to predict and forecast sales. This study investigated the effectiveness of the past sales, web search volume, information amount, brand promotion, and the advertising endorser on the sales forecasting model. The study conducted the autoregressive distributed lag (ARDL) time series model using the internal and external social big data of a national fashion brand. Results indicated that the brand's past sales, search volume, promotion, and amount of advertising endorser information amount significantly affected the sales forecast, whereas the brand's advertising endorser search volume and information amount did not significantly influence the sales forecast. Moreover, the brand's promotion had the highest correlation with sales forecasting. This study adds to information-searching behavior theory by measuring consumers' brand involvement. Last, this study provides digital marketers with implications for developing profitable marketing strategies on the basis of consumers' interest in the brand and advertising endorser.

• 패션비즈니스
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• 제18권6호
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• pp.86-99
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• 2014

The purpose of this study is to analyze women apparel's colors in the Seoul, Beijing, and Tokyo collections and examine the color characteristics of three collections through comparison with trend colors suggested by Carlin, a color forecasting group. A literature review and an empirical study were used for methodology. The literature review examined the status and characteristics of the three collections, a fashion color forecast, and F/W 2014-15 trend colors by Carlin based on previous researches and literature data on fashion color. The empirical study extracted and analyzed 2014-15 F/W women's ready-to-wear collections in Seoul, Tokyo, and Beijing and compared the result with trend colors by Carlin. First, the colors of women's apparel were analyzed in the Seoul, Beijing, and Tokyo collections. All three collections commonly used achromatic colors and the percentage of Bk, Gy, Wh, R, and B colors was high. All three collections used achromatic colors frequently for the main color and sub colors. For accent colors, while the application of achromatic colors was high in the Seoul collection, the application of chromatic colors was high in the Tokyo and Beijing collections. Second, women's apparel colors in the Seoul, Beijing, and Tokyo collections were compared with trend colors suggested by Carlin. All three collections highly reflected Bk, Wh, and R (Carlin's forecasting color of 'Splendor') and B (forecasting color of 'Boreal'). However, the reflection of metallic colors suggested as a keyword of 'Brave New World' and Pk color of 'Sensitive' and 'Boreal' were a bit low.

• 한국의류산업학회지
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• 제23권4호
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• pp.480-490
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• 2021

Sales forecasting is crucial for many retail operations. For apparel retailers, accurate sales forecast for the next season is critical to properly manage inventory and plan their supply chains. The challenge in this increases because apparel products are always new for the next season, have numerous variations, short life cycles, long lead times, and seasonal trends. In this study, a sales forecasting model is proposed for apparel products using machine learning techniques. The sales data pertaining to outerwear items for four years were collected from a Korean sports brand and filtered with outliers. Subsequently, the data were standardized by removing the effects of exogenous variables. The sales patterns of outerwear items were clustered by applying K-means clustering, and outerwear attributes associated with the specific sales-pattern type were determined by using a decision tree classifier. Six types of sales pattern clusters were derived and classified using a hybrid model of clustering and decision tree algorithm, and finally, the relationship between outerwear attributes and sales patterns was revealed. Each sales pattern can be used to predict stock-keeping-unit-level sales based on item attributes.