• Journal of the Korean Society of Clothing and Textiles
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• v.31 no.6 s.165
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• pp.942-954
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• 2007

The purpose of this research is to examine the level of SCM activity, marketing capability, and firm performance for apparel firms, and to investigate the effect of SCM activities and marketing capabilities for firm performance improvement. This study surveyed domestic apparel manufacturing brands that distribute products nationwide. The data was collected through questionnaires sent to managers or executives in large and middle manufacturing corporations among Korea's listed and registered corporations. The data collection has been carried out from November 10 until December 11, 2006. The questionnaires were transmitted by individual visit, fax, and mail. A total of 98 completed responses were returned, three incomplete responses were discarded. The results were as follows: First, SCM activity was classified into 3 dimensions: structural, logistical, and technological factor. Three dimensions of marketing capability were identified with differentiation, cost-leadership, and operational factor. Firm performance was classified into three dimensions: financial, productivity, and customer satisfaction factor. Second, result of analyzing effects of SCM activities for firm performance improvement, it was found that the improvement of technological activities affected acquirement of financial, productivity, and customer satisfaction performs. Structural activities affected factor of productivity performs. Third, result of analyzing effects of marketing capabilities for firm performance improvement, improvement of differentiation capabilities affected acquirement of financial, customer satisfaction performs. And the improvement of operational capability affected acquirement of financial performs and improvement of cost-leadership capability affected factor of productivity performs.

• Journal of Korean Home Economics Education Association
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• v.33 no.3
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• pp.129-142
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• 2021

The purpose of this study was to provide educational data on teaching clothing culture by examining the effects of clothing lifestyle on attitudes toward teachers' clothing for 270 secondary school pre-service teachers. For data analysis, factor analysis, Cronbach's α reliability coefficients, t-tests, one-way analysis of variance, Duncan's multiple comparison verification, and multiple regression analysis were performed using SPSS 24.0 program. As a result of the study, first, the clothing lifestyle of secondary school pre-service teachers was classified as fashion trend orientation, clothing importance orientation, attractive appearance orientation, and economic orientation factors. In addition, the attitude toward teacher's clothes was classified into activity, fashionability, and modesty factors. Second, there was a statistically significant difference in the attitudes toward clothing lifestyle and teacher clothing of secondary school pre-service teachers according to gender and year in college, which are demographic variables. Third, it was found that the clothing lifestyle of secondary school pre-service teachers, who are Generation Z, had an effect on the attitude toward teacher clothes. In conclusion, this study proposes that school administrators and teachers should depart from the former stereotypes about teacher clothes and to encourage a culture in which teachers can dress and perform their role of teaching according to individual's changing lifestyles.

• Journal of the Korea Fashion and Costume Design Association
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• v.21 no.3
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• pp.13-24
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• 2019

Adolescence is a transitional stage of physical development which occurs during the period from puberty to adulthood. Going through this period, various parts of an adolescent's body grow at different rates, leading to different body shapes and proportions when compared to adults. Therefore, this study aimed to investigate the body sizes and shapes of junior high school boys from ages 13-15 based on body measurement items that are used as the basis for school uniform designs including jackets, shirts, and pants. For this, the study sought the basic data needed to develop body shapes and school uniform patterns for junior high school boys using the data from the 6th Size Korea Survey (2010). Specifically, it provided basic data for the development of school uniform patterns that fit well through the classification of bodies into particular types. After extracting body shape componen a cluster analysis using ANOVA was performed. According to the factor analysis conducted to determine body shape components, 5 factors were obtained as follows: Factor 1: bulk and horizontal size, Factor 2: body height and length, Factor 3: shoulder shape and length, Factor 4: characteristics of horizontal size, Factor 5: shape of the upper body with a variance of 82.62%. To classify junior high school boys' body shape was determined using various characteristics, and a cluster analysis was performed with the variables obtained by the factor analysis. For this, body shapes were classified into 3 different types: Type 1 accounted for 33.4%, with a total of 463 subjects. This type was a tall, long body individual with the smallest bulk and size. Type 2 accounted for 22.7%, with a total of 315 subjects. This type was large in bulk and horizontal size, but the lowest in height and length. Type 3 accounted for 43.9%, with a total of 610 subjects. This type was close to average in terms of horizontal size, length, and height. To develop well-fitting school uniforms for junior high school students, there should be further studies on changes in body shape and their associated causes. The study results will be available as basic data for comparing branded school uniform patterns for junior high school boys and developing school uniform patterns based on body shape, using 3D virtual clothing simulations.

• Journal of Convergence for Information Technology
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• v.11 no.7
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• pp.164-171
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• 2021

This study analyzed the post-exercise cardiopulmonary function, maximal oxygen uptake, heart rate and recovery time through smoker's short - term smoking cessation and trunk stabilization exercise for 72 hours. We analyzed the effect of trunk stabilization exercise on the cardiopulmonary function of smokers and non-smokers. As a result, it was found that both smokers and non-smokers groups showed significant changes in pulmonary function (FVC, SVV, MVV), maximal oxygen uptake, recovery time Difference. This suggests that the trunk stabilization exercise may have a positive effect on the cardiopulmonary function of short-term non-smokers as well as non-smokers for a short period of time, and a more stable and effective method for preventing and improving the reduction of cardiorespiratory function

• The Korean Journal of Archival Studies
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• no.73
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• pp.47-79
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• 2022

NFT is literally a 'non-fungible token', a digital file that records specific virtual assets on a blockchain. Events such as ownership of the asset and transaction history are recorded on the blockchain through the token transaction, so counterfeiting and falsification are impossible. Therefore, NFT is used as a tool that can uniquely represent a specific virtual asset. The main purpose of this paper is to examine the characteristics of NFT from a records management point of view and to find ways to use them, and focuses on digital records that have the characteristics of assets as digital works. For this purpose, we first examine the basic concept of NFT and the principle of ownership and proof of value as an asset for digital works. In addition, it was confirmed how the advantages of NFT were applied through NFT use cases in various fields, and in particular, areas related to audio-visual records such as art, music, sports, and fashion were focused on. Furthermore, by comparing the characteristics of digital records with those of NFT, factors applicable to electronic records were identified. Finally, the types of digital records that are expected to be effective in the application of NFT were identified, and the possibility of their use and discussion points for introduction in records management are presented.

• The Journal of the Convergence on Culture Technology
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• v.7 no.4
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• pp.397-404
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• 2021

The web-based crowdfunding platform provides small-cap companies the opportunity to reduce financial risks and to reliably produce new products through pre-orders. Meanwhile, crowdfunding projects are also helping companies as a channel to test new products before mass production. Despite these advantages, from the point of view of businesses and consumers, it is true that web-based crowdfunding platforms have limitations in the retail environment. For example, the limited social elements of a web-based platform are somewhat in conflict with the basic characteristics of crowdfunding projects - which inevitably demand high social influences for the success. As such, understanding the mechanisms of social factors of crowdfunding platforms from the consumers' perspective is important. Therefore, in this study, we empirically tested the effect of social factors of crowdfunding platform on consumer participation and evaluation. Based on the Social Influence Theory and Social Presence Theory, we developed a conceptual framework where the social group size and social presence of other backers were the independent variables and the purchaser's intention to participate as the dependent variable. In the results, the size of the social group size and the perceived social presence have a significant positive effect on purchaser's participation intent. In addition, the social presence had a greater influence on the purchaser's intention to participate than the size of the sponsor's social group. We believe that our findings contribute to the extant literature by empirically demonstrating the valid effect of social factors of crowdfunding platforms on consumer evaluations.

• Journal of Service Research and Studies
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• v.12 no.2
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• pp.80-93
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• 2022

This study is a study on a methodology that can extract various factors that affect purchase and use of products/services from the consumer's point of view through previous studies, and analyze the types and tendencies of consumers according to age and gender. To this end, we quantify factors in terms of general personal propensity, consumption influence, consumption decision, etc. to check the consistency of data, and based on these studies, we conduct research to suggest and prove data analysis methodologies of consumer types that are meaningful from the perspectives of startups and SMEs. did As a result, it was confirmed through cross-validation that there is a correlation between the three main factors assumed for data analysis from the consumer's point of view, the general tendency, the general consumption tendency, and the factors influencing the consumption decision. verified. This study presented a data analysis methodology and a framework for consumer data analysis from the consumer's point of view. In the current data analysis trend, where digital infrastructure develops exponentially and seeks ways to project individual preferences, this data analysis perspective can be a valid insight.

• Smart Media Journal
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• v.12 no.7
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• pp.43-51
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• 2023

As online transactions increase, the image of clothing has a great influence on consumer purchasing decisions. The importance of image information for clothing materials has been emphasized, and it is important for the fashion industry to analyze clothing images and grasp the materials used. Textile materials used for clothing are difficult to identify with the naked eye, and much time and cost are consumed in sorting. This study aims to classify the materials of textiles from clothing images based on deep learning algorithms. Classifying materials can help reduce clothing production costs, increase the efficiency of the manufacturing process, and contribute to the service of recommending products of specific materials to consumers. We used machine vision-based deep learning algorithms ResNet and Vision Transformer to classify clothing images. A total of 760,949 images were collected and preprocessed to detect abnormal images. Finally, a total of 167,299 clothing images, 19 textile labels and 20 fabric labels were used. We used ResNet and Vision Transformer to classify clothing materials and compared the performance of the algorithms with the Top-k Accuracy Score metric. As a result of comparing the performance, the Vision Transformer algorithm outperforms ResNet.

• The Journal of the Convergence on Culture Technology
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• v.9 no.4
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• pp.727-737
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• 2023

This study aimed to provide basic data for the design and R&D of golf wear intended for 64 people in their 40s, 50s, and 60s by identifying the needs for golfers through a survey of golf wear purchasing conditions and preferences. The findings shows that purchases are made at permanent discount stores, and information about products are discovered through TV and Internet advertisements. Golf wear is purchased once or twice a year, with annual expenditures ranging from KRW 500,000 to less than 1 million, with single purchases ranging from KRW 200,000 to less than 500,000. When purchasing golf wear, design was considered first, with women preferring white garment, while men preferred black and gray ones. Men tended to prefer a PK collar button fastening style, while women preferred a knit style with a round neckline. Women preferred semi-fitted and fitted styles, while men preferred semi-fitted and loose-fitting styles, showing significant differences. When considering the production of golf wear, the younger the age of the consumer, the more the results indicated that the design needed to look younger, so it is the necessary to design golf wear that reflects the functional need of golfer while prioritizing designs for various ages.

• Journal of Intelligence and Information Systems
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• v.29 no.4
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• pp.325-345
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• 2023

In the rapidly evolving domain of e-commerce, our study presents a cohesive approach to enhance customer satisfaction prediction from online reviews, aligning methodological innovation with practical insights. We integrate the RFE-SHAP feature selection with LDA topic modeling to streamline predictive analytics in e-commerce. This integration facilitates the identification of key features-specifically, narrowing down from an initial set of 28 to an optimal subset of 14 features for the Random Forest algorithm. Our approach strategically mitigates the common issue of overfitting in models with an excess of features, leading to an improved accuracy rate of 84% in our Random Forest model. Central to our analysis is the understanding that certain aspects in review content, such as quality, fit, and durability, play a pivotal role in influencing customer satisfaction, especially in the clothing sector. We delve into explaining how each of these selected features impacts customer satisfaction, providing a comprehensive view of the elements most appreciated by customers. Our research makes significant contributions in two key areas. First, it enhances predictive modeling within the realm of e-commerce analytics by introducing a streamlined, feature-centric approach. This refinement in methodology not only bolsters the accuracy of customer satisfaction predictions but also sets a new standard for handling feature selection in predictive models. Second, the study provides actionable insights for e-commerce platforms, especially those in the clothing sector. By highlighting which aspects of customer reviews-like quality, fit, and durability-most influence satisfaction, we offer a strategic direction for businesses to tailor their products and services.