• Journal of the Korean Society of Clothing and Textiles
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• v.42 no.5
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• pp.871-883
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• 2018

This study tests consumer responses to online product recommendation service offered by a website. A product recommendation service refers to a filtering system that predicts and shows items that consumers would like to purchase based on their searches or pre-purchase information. The survey is conducted on 300 people in an age group between 20 and 40 years in a panel of an online survey firm. Data are analyzed using confirmatory factor analysis and structural equation modeling by AMOS 20.0. The results show that personalization quality does not have a significant effect on trust, but relationship quality and technology quality have a positive effect on trust. Three types of quality of recommendation service also have a positive effect on commitment. Trust and commitment are factors that increase service usage intentions. In addition, this study reveals the moderating effect of light users vs heavy users based on online shopping time. Light users show a negative effect of personalization quality on trust, indicating that they are likely to be uncomfortable to the service using personal information, compared to heavy users. This study also finds that trust vs commitment is an important factor increasing service usage intentions for heavy users vs light users.

• Journal of the Korean Society of Clothing and Textiles
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• v.48 no.2
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• pp.350-366
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• 2024

This study aimed to clarify the continuance intention of users of size recommendation services. The expectation-confirmation model framed the analysis of the 180 data points collected. The analysis determined the mediating effects of perceived usefulness and satisfaction on the relationship between expectation-confirmation and continuance intention. The moderated mediation effect of familiarity was also analyzed, and a path analysis was conducted using PROCESS macro. Results showed that expectation-confirmation had a significant effect on perceived usefulness, satisfaction, and continuance intention. Findings indicated that perceived usefulness affected satisfaction and continuance intention and confirmed that satisfaction affected continuance intention. In the relationship between expectation-confirmation and continuance intention, mediation analysis verified the mediation and double mediation of perceived usefulness and satisfaction. In the group with an above-average familiarity value, moderation analysis confirmed a moderating effect between perceived usefulness and satisfaction. Above-average familiarity values also confirmed that the moderating effect on continuance intention was significant.

• Journal of the Korean Home Economics Association
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• v.33 no.4
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• pp.315-327
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• 1995

The objective of this study were to classify the contents of clothing purchase motives and to examine the differences in post-purchase dissatisfaction and satisfaction of clothing according to the clothing purchase motives. Questionnaire was comprised of 36 Likert type items of clothing purchase motive measure, 15 items of post-purchase clothing dissatisfaction measure, and 1 item of satisfaction measures. Samples were 492 women in Incheon, Korean ; 279 were college students and 213 were housewives. The data were analyzed using factor analysis, cluster analysis, one-way ANOVA, Duncan's multiple range test, and χ2-test. The results of the study were the followings : 1. Subjects perceived 'becomingness' to be the most important motive, 'attractiveness of color' the second important, and 'salesperson's recommendation' the least. 2. 6 factors of clothing purchase motives were derived by factor analysis : F.1 'clothing utility and deficiency' ; F.2 'clothing quality' ; F.3 'financial frugality'. 3. Subjects were classified into the three motive groups by cluster analysis of the 6 factors : G.1 'the clothing appearance and others' influence' ; G.2 'the clothing quality and deficiency' ; G.3 'the motiveless'. 4. More college women were distributed in clothing appearance and others' influence group than housewives, while more housewives were distributed in clothing quality and deficiency group. 5. The clothing appearance and others' influence group expressed the highest post-purchase dissatisfaction and the lowest post-purchase satisfaction. The clothing quality and deficiency group expressed the highest post-purchase satisfaction, and the motiveless group expressed the lowest post-purchase dissatisfaction.

• Journal of the Korea Fashion and Costume Design Association
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• v.14 no.4
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• pp.43-61
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• 2012

This research aims to examine the impact of store personality and service quality on the customers' intention of revisiting the department store and their intention of recommendation to others. The participants were women in their 20s to 50s with experiences of purchasing apparel from major department stores. A total of 324 survey responses were used for the final analysis. The data were analyzed using factors analysis, reliability analysis, and multiple regression analysis with PASW 18.0. The results were as follows. First, the department store personality was composed of 3 factors; prestige, passion, sincerity. Service quality factors were defined as tangibility, responsiveness, and empathy. Second, the three dimensions of brand personality-prestige, passion and sincerity turned out to be influential factors affecting the customers' revisiting intention and recommendation intention. Also, tangibility and responsiveness of service quality factors had a significant influence on their revisiting intention, whereas tangibility, responsiveness and empathy factors had a significant influence on their recommendation intention. Third, the sub-dimensions of store personality and service quality had a different influence on the customers' revisiting intention and recommendation intention according to the department store brand.

• Smart Media Journal
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• v.10 no.1
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• pp.116-123
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• 2021

Due to the rapid growth of the online fashion market and the resulting expansion of online choices, there is a problem that the seller cannot directly respond to a large number of consumers individually, although consumers are increasingly demanding for more personalized recommendation services. Images are being tagged as a way to meet consumer's personalization needs, but when people tagging, tagging is very subjective for each person, and artificial intelligence tagging has very limited words and does not meet the needs of users. To solve this problem, we designed an algorithm that recognizes the shape, attribute, and emotional information of the product included in the image with AI, and codes this information to represent all the information that the image has with a combination of codes. Through this algorithm, it became possible by acquiring a variety of information possessed by the image in real time, such as the sensibility of the fashion image and the TPO information expressed by the fashion image, which was not possible until now. Based on this information, it is possible to go beyond the stage of analyzing the tastes of consumers and make hyper-personalized clothing recommendations that combine the tastes of consumers with information about trends and TPOs.

• The Journal of the Convergence on Culture Technology
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• v.9 no.1
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• pp.347-353
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• 2023

Currently, soldiers enlisted in the military (Army) are receiving measurements (automatic, manual) of body parts and trying on sample clothing at boot training centers, and then receiving clothing in the desired size. Due to the low accuracy of the measured size during the measurement process, in the military, which uses a relatively more detailed sizing system than civilian casual clothes, the supplied clothes do not fit properly, so the frequency of changing the clothes is very frequent. In addition, there is a problem in that inventory is managed inefficiently by applying the measurement system based on the old generation body shape data collected more than a decade ago without reflecting the western-changed body type change of the MZ generation. That is, military uniforms of the necessary size are insufficient, and many unnecessary-sized military uniforms are in stock. Therefore, in order to reduce the frequency of clothing replacement and improve the efficiency of stock management, deep learning-based automatic measurement of body size, big data analysis, and machine learning-based "Personalized Combat Uniform Automatic Recommendation System for Enlisted Soldiers" is proposed.

• Proceedings of the Korean Fiber Society Conference
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• 2003.10a
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• pp.112-112
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• 2003

A Web-based fabric information system has been developed. Recently the numbers of textile companies that have their own homepage to advertise their product fabrics for apparel through the Web-based E-commerce rapidly increase.(omitted)

• ETRI Journal
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• v.46 no.2
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• pp.277-289
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• 2024

In this paper, we describe a neural network-based application that recommends multiple items using dialog context input and simultaneously outputs a response sentence. Further, we describe a multi-item recommendation by specifying it as a set of clothing recommendations. For this, a multimodal fusion approach that can process both cloth-related text and images is required. We also examine achieving the requirements of downstream models using a pretrained language model. Moreover, we propose a gate-based multimodal fusion and multiprompt learning based on a pretrained language model. Specifically, we propose an automatic evaluation technique to solve the one-to-many mapping problem of multi-item recommendations. A fashion-domain multimodal dataset based on Koreans is constructed and tested. Various experimental environment settings are verified using an automatic evaluation method. The results show that our proposed method can be used to obtain confidence scores for multi-item recommendation results, which is different from traditional accuracy evaluation.

• Journal of the Korean Home Economics Association
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• v.47 no.7
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• pp.83-95
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• 2009

This study investigated the differences in the effects of the perception of the internet fashion shopping mall characteristics on satisfaction and loyalty of internet fashion shopping mall between Korean and American college students. Questionnaires were administered to 251 Korean and 221 American college students. The results were as follows. First, service and product diversity had significant effects on satisfaction of internet fashion shopping mall in both group, while convenience had a significant impact on satisfaction of internet fashion shopping mall in American group. Second, service, product diversity, and promotion had significant influences on repurchase intention of internet fashion shopping mall in Korean consumer group, while service and reliability, product diversity, and convenience had significant effects on repurchase intention of internet fashion shopping mall in American consumer group. Third, service had a significant effect on recommendation intention in Korean group, while service and reliability and product diversity had significant influences on recommendation intention in American group.

• Journal of the Korea Fashion and Costume Design Association
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• v.14 no.3
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• pp.161-176
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• 2012

This study aims to find out the influence of satisfaction of the product and shopping mall attributes on mall reliability, repurchase intention, and recommendation intention in internet open market. For this purpose, this study surveyed 266 male and female consumers in their 20's~40's for empirical analysis who have ever purchased clothing through internet open markets. Respondents are selected using the convenience sampling through online survey in August 2011. For statistical analysis, descriptive statistics, reliability analysis, factor analysis, t-test, ANOVA, and regression analysis are carried out using SPSS for Windows 12.0. The results are as follows; First, it was identified that there were Significant differences in consumers' satisfaction on product and shopping mall attributes according to purchase price, degree of purchase, and the demographics. Second, it was identified that performance, sewing condition, the stability of the form, texture, harmony with other clothes, the response of people, fashionability, seller, origin, detailed explanation on products, interaction with shopping malls, and ease-of-use have significant influence on the reliability of open market. Third, it was identified that easiness to be active in, the stability of the food, design, suitability to T.P.O, price, origin, detailed explanation on products, product assortment, reputation of shopping malls, ease-of-use, and delivery charge policy have significant influence on the repurchase intention. Fourth, it was identified that easiness to be active in, the stability of the form, design, suitability to T.P.O, price, origin, detailed explanation on products, product assortment, reputation of shopping malls, ease-of-use, and delivery charge policy have significant influence on the intention to recommend.