• Fashion & Textile Research Journal
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• v.4 no.2
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• pp.107-110
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• 2002

• Journal of the Korean Society of Clothing and Textiles
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• v.48 no.5
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• pp.931-955
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• 2024

International trade in the clothing industry has contributed significantly to South Korea's economic development. This study examines the interplay between textile and clothing exports, imports, and gross domestic product (GDP) growth from a macroeconomic perspective using a model with vector autoregressive with exogenous variables (VARX). The findings indicate that GDP growth negatively impacts textile and clothing exports but is positively correlated with imports. Furthermore, GDP growth from one and two years prior negatively affects current exports while positively influencing imports. Macroeconomic indicators, including the consumer price index, private consumption index, and producer price index, significantly impact the textile and clothing trades. By contrast, the won/dollar exchange rate and the Bank of Korea's base interest rate do not appear to exert any substantial effect. An unexpected impulse from GDP growth strongly affects the status of textile and clothing imports. Predictions for the future indicate stable GDP growth over the next five years, with high volatility anticipated in the clothing industry's trade balance. This study applies endogenous growth theory to the global clothing trade, yielding theoretical insights, and offers empirical guidance for government agencies wishing to support domestic clothing trade firms.

• Fashion & Textile Research Journal
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• v.23 no.3
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• pp.380-389
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• 2021

This study aimed to reveal the perceptions and trends of digital fashion technology through an informational approach. A big data analysis was conducted after collecting the text shown in a web environment from April 2019 to April 2021. Key words were derived through text mining analysis and network analysis, and the structure of perception of digital fashion technology was identified. Using textoms, we collected 8144 texts after data refinement, conducted a frequency of emergence and central component analysis, and visualized the results with word cloud and N-gram. The frequency of appearance also generated matrices with the top 70 words, and a structural equivalent analysis was performed. The results were presented with network visualizations and dendrograms. Fashion, digital, and technology were the most frequently mentioned topics, and the frequencies of platform, digital transformation, and start-ups were also high. Through clustering, four clusters of marketing were formed using fashion, digital technology, startups, and augmented reality/virtual reality technology. Future research on startups and smart factories with technologies based on stable platforms is needed. The results of this study contribute to increasing the fashion industry's knowledge on digital fashion technology and can be used as a foundational study for the development of research on related topics.

• Fashion & Textile Research Journal
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• v.18 no.1
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• pp.48-62
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• 2016

Consumers have come to demand high quality, affordable prices, and innovative product designs of the outdoor wear market due to their well-being and leisure oriented lifestyle. A new system of business in outdoor wear has emerged in the process through which corporations have endeavored to satisfy such consumer needs. Outdoor wear brands have utilized social network services (SNS) such as Facebook and Twitter as means of marketing and have built close relations with consumers based on communication through these media. Recently, explosively escalating SNS data are referred to as social big data, and now that every consumer online is a commentator, reviewer, and publisher, the outdoor wear market and all of its brands have to stop talking and start listening to how they are perceived. Therefore, this study employs Social $Metrics^{TM}$, a social big data analysis solution by Daumsoft, Inc., to verify changes in the allusions related to outdoor wear market found on SNS. This study aims to identify changes in consumer perceptions of outdoor wear based on changes in outdoor wear search words and trends in positive and negative public opinion found in SNS social big data. In addition, products of interest, the major brands mentioned, the attributes taken into consideration during purchases of products, and consumers' psychology were categorized and analyzed by means of keywords related to outdoor wear brands found on SNS. The results of this study will provide fundamental resources for outdoor wear brands' market entry and brand strategy implementation in the future.

• Management & Information Systems Review
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• v.37 no.2
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• pp.87-108
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• 2018

This article explores the international trade flow of Bangladesh's ready-made garments (RMG). We first suggest the brief history and an international structure of trade among countries by using the trade volume. Then we implemented a gravity model regression with the sample of 38 major partner countries in order to investigate the potential export market for the RMG industry. The fixed effect and random effect model for the panel data during the period of 1990 to 2011 are estimated. Our result shows that Bangladesh's RMG exports are affected positively by the size of economy, inflation, exchange rate, foreign direct investment(FDI) and trade openness. On the other hand, the distance between trading partners are related negatively with the trade volume. We used the estimated coefficients from the panel regression in order to predict RMG export potential of Bangladesh. This might show which country is the promising export market for Bangladesh RMG industry. We found that Bangladesh has the highest potential of RMG export with Japan and USA, which seem to have considerable room for export growth if trade barriers and constraints are removed. We added some policy implications for encouraging the RMG export of Bangladesh by using the results from the analysis.

• Journal of the Korean Society of Clothing and Textiles
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• v.47 no.3
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• pp.511-530
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• 2023

This study aims to analyze middle-aged men's frontal body shape asymmetry by measuring the left and right body dimensions and angles of 388 middle-aged men aged 40 to 59 using 3D body scan data and comparing the measured values. The study also compares the measured values of width, height, and angle and their relationships using Size Korea's anthropometric measurement and posture index of the New York Posture Rating Scale. The results confirm that the asymmetric shape characteristics of the upper and lower body appear differently. In addition, the asymmetrical characteristics between the upper and lower body differed, indicating that the close parts of the body affect each other. Similar to the difference in the left and right frontal body shapes and the average angle distribution, the asymmetrical upper and lower body characteristics also are found to be dissimilar when the correlations are examined. In contrast, there is no asymmetry in the width, height, and angle considering the age and BMI groups. Finally, the study classifies three body types and identifies their asymmetric characteristics. Overall, this study contributes primary data for further research on pattern production for asymmetric and unique body types and the development of customized apparel products.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2020.07a
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• pp.637-642
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• 2020

패션산업은 매년 1 조원씩 성장(연평균 2.1%)하며 많은 연구자들의 관심을 받고 있다. 전통적인 패션산업은 점차 디지털화되어 선진적인 컴퓨터 비전 기술을 적용해 소비자들에게 더 좋은 쇼핑 서비스를 제공하고 있다. 본 논문에서는 2014 년부터 2019 년 사이에 구축된 대표적인 패션 데이터셋을 연도별로 정리하고 각 데이터셋에 포함된 주석(annotation)의 특징을 정리했다. 또한 데이터셋이 패션 상품 검출(Fashion detection), 패션 이미지 생성(Fashion image generation), 가상 피팅(Virtual try-on) 그리고 패션 의류 분할(Fashion Clothing segmentation) 등 연구에서의 활용될 수 있는 여부에 대해 분석했다.

• Journal of the Korean Society of Clothing and Textiles
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• v.47 no.5
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• pp.779-803
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• 2023

The growth of digital news media and the stock price index has resulted in economic fluctuations in the fashion industry. This study examines the impact of fashion industry news and macroeconomic changes on the Textile & Wearing Apparel KOSPI over the past five years. An auto-regressive integrated moving average exogenous time series model was conducted using the fashion industry stock market index, the news topic index, and macro-economic indicators. The results indicated the topics of "Cosmetic business expansion" and "Digital innovation" impacted the Textile & Wearing Apparel KOSPI after one week, and the topics of "Pop-up store," "Entry into the Chinese fashion market," and "Fashion week and trade show" affected it after two weeks. Moreover, the topics of "Cosmetic business expansion" and "Entry into the Chinese fashion market" were statistically significant in the macroeconomic environment. Regarding the effect relation of Textile & Wearing Apparel KOSPI, "Cosmetic business expansion," "Entry into the Chinese fashion market," and consumer price fluctuation showed negative effects, while the private consumption change rate, producer price fluctuation, and unemployment change rate had positive effects. This study analyzes the impact of media framing on fashion industry business cycles and provides practical insights into managing stock market risk for fashion companies.

• 한국데이터정보과학회:학술대회논문집
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• 2006.04a
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• pp.253-265
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• 2006

This study aims to figure out the relation between the demographic characteristics and job satisfaction of those who work at fashion companies. The subject of this study is those who work at fashion companies beyond the small and medium sized businesses and designer brand employees in Busan. We used SPSS/WIN 10.0 to analyze the data for this study. The job satisfaction was found to increase in proportion to the satisfaction with the job itself, the senior of official, wage and colleagues, which increases along with the level of post. The job satisfaction was found to be proportional to the level of work specialization, satisfaction with the company and welfare. The job satisfaction and the performance would improve if the work environment for employees is made better by making their works more diverse and discretionary to ensure a successful growth of fashion companies.

• Fashion & Textile Research Journal
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• v.22 no.5
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• pp.639-649
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• 2020

This study investigates consumer opinions of clothing care and provides fundamental data to decision-making for oncoming development of clothing care system. Textom, a web-matrix program, was used to analyze big data collected from Naver and Daum with a keyword of "clothing care" from March 2019 to February 2020. A total of 22, 187 texts were shown from the big data collection. Collected big data were analyzed using text-mining, network, and CONCOR analysis. The results of this study were as follows. First, many keywords related to clothing care were shown from the result of frequency analysis such as style, Dryer, LG Electronics, Product, Customer, Clothing, and Styler. Consumers were well recognizing and having an interest in recent information related to the clothing care system. Second, various keywords such as product, function, brand, and performance, were linked to each other which were fundamentally related to the clothing care. The interest in products of the clothing care system were linked to product brands that were also naturally linked to consumer interest. Third, the keywords in the network showed similar attributes from the result of CONCOR analysis that were classified into 4 groups such as the characteristics of purchase, product, performance, and interest. Lastly, positive emotions including goodwill, interest, and joy on the clothing care system were strongly expressed from the result of the sentimental analysis.