• Journal of the Korea Fashion and Costume Design Association
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• v.25 no.1
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• pp.83-96
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• 2023

The purpose of this study is to compare and analyze the perception of retro fashion and new-tro fashion using big data. TEXTOM allowed the collection of big data on the words 'retro fashion' and 'new-tro fashion', which was refined afterwards. As for the data collection period, Jan. 1, 2019 to Nov. 30, 2022 was set. A top 50 list of words were extracted from this data based on appearance frequency. The extracted words were processed through Network centrality analysis and CONCOR analysis using Ucinet 6. The results are as follows. 1) In retro fashion, the appearance frequency of 'style' was the highest, followed by 'sensibility', 'color', 'trend', 'fashion', and 'brand'. These words came up with high TF-IDF values. Network centrality analysis discovered that 'color', 'style', 'trend', 'sensibility', and 'design' had high level of connectivity with other words. CONCOR analysis showed a total of four significant groups; trends, styles, looks, and photos. 2) In new-tro fashion, the appearance frequency of 'retro' was the highest, followed by 'trend', 'generation', 'style', 'brand', and 'fashion'. These words also came up with high TF-IDF values. Network centrality analysis found that 'retro', 'trend', 'generation', and 'brand' had high level of connectivity with other words. CONCOR analysis showed a total of four significant groups; style, brand, clothing, and trend. 3) New-tro fashion is included in retro fashion in that it reproduces the styles of the past. However, it is taken completely differently from generation to generation. Unlike the older generations, millennials actively accept newly created clothes and brands based on the past styles. They perceive it as a fashion that reveals their own unique tastes and tastes.

• Fashion & Textile Research Journal
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• v.12 no.4
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• pp.431-438
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• 2010

This study analyzes how the environmental values of fashion consumers influence the purchase satisfaction and repurchase intention of eco-friendly fashion products. The survey was conducted from June $1^{st}$ to $30^{th}$ in 2009, and 343 responses were used in the data analysis. The statistical analysis methods were frequency analysis, factor analysis, reliability analysis, and multiple regression analysis. The results show that the environmental values is classified by environment conservative value, economical value, social altruistic value, and egocentric value. The social altruistic value of fashion consumers affects purchase satisfaction of eco-friendly fashion products. The social altruistic value, environment conservative value, and egocentric value affect the repurchase intention of eco-friendly fashion products.

• Journal of the Korea Fashion and Costume Design Association
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• v.16 no.2
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• pp.111-126
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• 2014

The purpose of this study is to identify the antecedents of the attitudes toward purchasing fast fashion brands. As antecedents, fashion consciousness, eco-fashion consumption decision, ongoing search behavior, and shopping enjoyment were considered. It was hypothesized that fashion consciousness influence the attitudes toward purchasing fast fashion brands both directly and indirectly through eco-fashion consumption decision, ongoing search behavior, and shopping enjoyment. Data were gathered by surveying university students in Seoul, using convenience sampling. Three hundred five questionnaires were used in the statistical analysis, exploratory factor analysis using SPSS and confirmatory factor analysis and path analysis using AMOS. The hypothesized relationship test proved that fashion consciousness influences the attitudes toward purchasing fast fashion brands both directly and indirectly through ongoing search behavior and shopping enjoyment. In addition, eco-fashion consumption decision influence directly influences the attitudes toward purchasing fast fashion brands. The results suggest some effective marketing strategies for marketers in the fast fashion industry.

• Fashion & Textile Research Journal
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• v.3 no.5
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• pp.415-422
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• 2001

Focusing on working with fashion show as fashion model in South Korea, this study was develop a fashion model typology based on specific model characteristics related demographics and body, job satisfaction/dissatisfaction factors. The survey was done through questionnaire and 194 fashion models were used in the data analysis. The statistical analysis used in this study were frequency, ${\chi}^2$-test, cluster Analysis, MANOVA. ANOVA and Duncan multiple range test. The results of this study were as follows: 1) The majority of sample were as follows: unmarried, college graduate and undergraduate, resident in the Seoul, 20 to 24 yrs old female with 175-177 cm, 52-54 kg, B-W-H (33-24-35 inch). 2) The types of fashion model were classified into 4 types: showing type, lack of professionalism type, matured professionalism type, dissatisfaction with job-environment type. The model segments were profiled on levels of various job related attitude factors, job satisfaction/dissatisfaction, model education, working condition, human relation, regulation discrimination, fashion show stage level, the job of model, body & clothing, and promising job. 3) There were significant differences found between their sex, academic background, guarantee, and in all factors in their job related attitude factors, job satisfaction/dissatisfaction, model education, working condition, human relation, regulation discrimination, fashion show stage level, the job of model, body & clothing, style promising job.

• Journal of the Korea Fashion and Costume Design Association
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• v.17 no.3
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• pp.149-158
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• 2015

More weight is given today to the role and capacity of fashion shopmasters who stand in direct contact with customers at department stores. The present study examines relationship between the stress factors and the job satisfaction by fashion shopmasters. The questionnaires was prepared 300 fashion shopmasters who work at fashion brand shops for ladies' formal and casual dress in department stores located in Chungcheong provincial areas from Aug. 5 to 23, 2013. Out of the distributed questionnaires, 270 were returned and 256 were put to the final analysis after excluding those that were replied unfaithfully. The second stage was to collected data underwent frequency analysis, factor analysis, reliability analysis and regression analysis to determine the effects of variables by using SPSS 18.0. Fashion shop masters are therefore requested to have exact understanding to their role as retail sales professionals, fashion advisers and experts of fashion shop management, to become well aware of their job in detail, to apply such knowledge to their practical job performance and to make personal efforts to promote their status as fashion shop masters.

• Journal of Fashion Business
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• v.27 no.3
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• pp.132-149
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• 2023

This study aims to analyze Instagram hashtags based on big data to investigate changes in consumer trends and perceptions of vegan fashion, and to derive strategies for revitalizing vegan fashion brands based on derived results. Among social media, Instagram was selected as a collection channel, and Instagram hashtags for 'Vegan Fashion' were collected from July 1, 2021 to December 31, 2021. After conducting semantic network analysis with the Ucinet 6 program based on the collected data, the CONCOR analysis on vegan fashion showed the following four clusters: 'Veganism practiced with fashion', 'Bag type of vegan fashion brand', 'Sharing vegan fashion', and 'Diversification of eco-friendly products'. Analysis results showed that the Instagram hashtag for vegan fashion confirmed the MZ generation's increased interest in vegan fashion and their thoughts to recommend and share frequently used items or brand products to people around them. CONCOR analysis of vegan fashion brands showed the following four groups: 'Differentiating the material of vegan bags', 'Eco-friendly products of vegan fashion brands', 'Interest in vegan shoes', and 'Donation campaign of vegan fashion brands'. CONCOR analysis on Meaningout showed the following four clusters: 'MZ Generation's Meaningout Start-up', 'Recommendation Platform for Skin Products', 'Value Consumption Trend for Eco-friendly Clothing', and 'Interest in Eco-friendly Packaging'. The results of this study on vegan fashion, a practical eco-friendly movement that can require changes in social responsibility and perception as issues that directly affect animals, the environment, and humans, are expected to provide basic data to help domestic vegan fashion brands develop marketing strategies.

• Journal of the Korean Society of Clothing and Textiles
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• v.19 no.1
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• pp.129-141
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• 1995

The Purpose of this study was to investigate the preference of fashion style, the clothing attitude and the preferred fashion style based on sex-role attitude. Sample.; in this study were 305 white collar adult male in Seoul, Korea. The stimuli consisted of 16 color photographs made by identical manipulations of 4 independent variables (jacket, pants, vest, neck-tie) consisting of two levels each (classic and fashion style). For analyzing data, frequency analysis, percent, mean, standard deviation, ANOVA, $X^2$ test, Duncan test, and Cronbach's u were used The results are as follows. 1. According to the preference analysis of the fashion style, white collar adult male prefer to wear clothing style than fashion in all clothing style, except for rolled-up pants. 2. According to the fashion interest (I) based on the preference analysis of the fashion style, the fashion oriented group had high fashion interest (I) in jacket, pants, and neck-tie. 3. According to the clothing attitude based on the preference analysis of the fashion style; for jacket, the fashion oriented group had high fashion interest, but had no relation with status symbols consciousness, clothing conformity, individuality; for vest, the fashion oriented group had high fashion interest (II) and individuality, but had no relation with status symbols 4. According to the clothing attitude based on the sex-role attitude, the group of masculine and feminine had high score in fashion interest (II), status symbols consciousness, and individuality

• Fashion & Textile Research Journal
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• v.23 no.6
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• pp.799-809
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• 2021

This study aimed to grasp the perceptions and trends in fashion platforms and fashion smart factories using big data analysis. As a research method, big data analysis, fashion platform, and smart factory were identified through literature and prior studies, and text mining analysis and network analysis were performed after collecting text from the web environment between April 2019 and April 2021. After data purification with Textom, the words of fashion platform (1,0591 pieces) and fashion smart factory (9750 pieces) were used for analysis. Key words were derived, the frequency of appearance was calculated, and the results were visualized in word cloud and N-gram. The top 70 words by frequency of appearance were used to generate a matrix, structural equivalence analysis was performed, and the results were displayed using network visualization and dendrograms. The collected data revealed that smart factory had high social issues, but consumer interest and academic research were insufficient, and the amount and frequency of related words on the fashion platform were both high. As a result of structural equalization analysis, it was found that fashion platforms with strong connectivity between clusters are creating new competitiveness with service platforms that add sharing, manufacturing, and curation functions, and fashion smart factories can expect future value to grow together, according to digital technology innovation and platforms. This study can serve as a foundation for future research topics related to fashion platforms and smart factories.

• Journal of Fashion Business
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• v.16 no.4
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• pp.64-74
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• 2012

The purpose of this study would be to find out the relationship of social as a sign of fashion image and the followership. This study is classified into theoretical and experimental research. Following are the summary of the results revealed through the experimental study. First, The relationship of oneself pursuit of fashion image types and leader's favourite fashion image types for regression analysis result indicated significant difference. Second, The factor analysis of followership are used, developed by Colangeol is asking. The results of factor analysis are four types classification as to Active Participation, Convergence objective, Team Spirit, Critical Thinking. Third, The relationship of types of fashion images and factor variance of followership indicated a difference in Active Participation factors. But The relationship of types of leader's fashion images and factor variance of followership indicated a difference in Convergence objective factors. Analysis of the fashion image based on the conceptual properties of followership is to understand the characteristics of followers, and the leader's image based on research for building materials will be provided.

• Journal of Fashion Business
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• v.9 no.2
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• pp.160-173
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• 2005

Fashion is hard to expect owing to the rapid change in accordance with consumer taste and environment, and has a tendency toward variety and individuality. Especially street fashion d 21st century is not being regarded as one of the subcultures but is playing an important role as a fountainhead d fashion trend. Therefore, Searching and analyzing street fashions helps us to understand the popular fashions d the next season and also it is important in understanding the consumer fashion sense and commercial area. So, we need to understand fashion styles quantitatively and qualitatively by providing visual data and dividing images. The purpose of this study is to design for street fashion on design analysis using web which can update quantitative and qualitative data. through the on site investigation d street fashion, and put the information onto a database.