• Journal of the Korean Society of Fashion and Beauty
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• v.3 no.2 s.2
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• pp.55-64
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• 2005

The purpose of this study is to investigate consumers' knowledge and preference towards functional cosmetics. Through the beauty advisors' surveys, their own selling styles and consumer behaviors recognized by beauty advisors were analyzed. It was intended to help extend and strengthen the functional cosmetic market which has continued to grow rapidly since the approved goods under cosmetic law in 2001. For this study, the data was collected through questionnaires the professional consumer counselors confirmed from Korean women over the age. of twenty old living in the Seoul and Kyoungki areas. After pre-research was implemented on 45 women, 328 samples were analyzed as final samples. In addition,46 samples, which were collected through the questionnaires from beauty advisors were analyzed. Samples were analyzed by frequency, percentage, T-test, ANOVA using the SPSS program. The results of study were as follows: First consumers recognized whether functional cosmetics or not. According to the beauty advisor's surveys, consumers regard the functional cosmetic boundary as being wider than real functional cosmetic boundary according to cosmetic law. So, there is a gap between consumers' opinions and real law. Second, regarding the purchasing channels, the largest channel is the cosmetic store. As far as consumers are concerned the most important factor when buying cosmetics, is the suitability of their own skin types. The second factor is product quality and the third factor is price. Functional cosmetics non-experienced group are more concerned with price compared to experienced group. Related to purchasing products, functional cosmetics experienced group buy set products compared to non-experienced group buy one product. Third, the ultraviolet filter cosmetics portion is the largest in the functional cosmetics market the second largest portion is bleaching cosmetics and the third largest portion is the anti-senility cosmetics. However, Most preferred by consumers is the anti-senility cosmetics. Moreover, preference for ultraviolet filter cosmetics is the least. Finally, the level of satisfaction for functional cosmetics is high and dissatisfaction is low. Consumers feel that beauty advisors are simply pushing high priced products without recognizing the consumers' real needs. In conclusion, to develop the functional cosmetic market continually in the future, it needs to extend various products and advertise them until consumers are more aware.

• Journal of the Korean Society of Clothing and Textiles
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• v.31 no.11
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• pp.1554-1564
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• 2007

In apparel industry, the production of clothing for the global market, has it#s origin in its characteristics depending on hands on working style, according to the globalization of a fashion industry. These days, however, the globalized production is unable to keep pace with the short cycle of production due to the unpredictable change of the taste or demands in the local area, as a result, the industry has come to take a focus on the production and consumption in the circumscribed region. In this stream, the northeastern area, specially, Dalian which is renowned for a center of fashion was designated as a city of this study as a representative. The cultural, racial and geographical uniqueness, asks for the analysis, based on the individual local area on the part of Korean fashion company desiring to launch into China fashion market. The purpose of this thesis is to analyse the style, color, and items of street fashion in Dalian. I would contribute to the understanding the preference of fashion in northeastern area, thereby, affording a fundamental resources for designing strategies for Korean fashion brands in China. The period of investigation is about 5 weeks from 14 May 2006 until 18 June 2006, with combined use of camcorder and digital camera. The site was Victory Shopping Plaza, in center of city, also with Mycal, Ansung, Dasang department store situated in the Economic Development area. The result of this study are as follows: 1. Preferred clothing styles are casual styles(68%) rather than formal styles(32%). In the casual styles, sports casual(36.0%), character casual(29.5%), jean casual(2.6%) were listed. All kinds of clothes are tightly fitted due to the stretched fabric and knit fabric. 2. Preferred colors are white(31.1%), red(16.6%), black(15.8%) khaki(7.8%) and blue(7.6%) for tops, and black(34.6%), blue(27.2%), white(15.4%), brown(14.6%) for bottoms. 3. Preferred clothing items are T-shirt(36.5%), jumper(33.6%), jacket(20.0%), blouse(8.7%), etc.(1.2%) for tops, pants(91.4%), skirts(8.6%) for bottoms. In the pants, cigarette pants(34.6%), bell bottom pants(21.0%), cargo pants(19.9%), straight pants(15.9%) were listed respectively. In the skirts, flare skirt(3.9%), tight skirt(2.2%), semi tight skirt(1.7%), pleats skirt(0.8%) were listed.

• The Research Journal of the Costume Culture
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• v.12 no.6 s.53
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• pp.984-998
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• 2004

The purpose of this study was to analyze contents of clothing product evaluation statements in the internet shopping mall and to discover consumers' recognition and evaluation of it. The data were collected from 151 consumers' statements in the four internet apparel shopping malls and a questionnaire was developed to measure consumers' recognition of clothing product evaluation statements. The questionnaire was administrated 272 consumers over 18 years old. The results of this study were as follows; First, The contents of clothing product evaluation statements in the internet shopping blog, were divided into three categories which were product, service and consumer buying decision process. Product category include evaluation of clothing product, description of difference between real product and product on the screen, and advice of uses. Service category include quickness and kindness in delivery, store preference for good service. For consumer buying decision process, motivation of purchasing, perceived risk, expression of satisfaction from good buying and canvassing for purchasing were included. Second, consumer recognized that clothing product evaluation statements has function of furnishing information, confirmation of purchasing decision, risk reduction of internet shopping, and interesting entertainment. Consumers also were dependent on product evaluation statements for making purchasing decision. And it was trusted by consumers. This recognition & evaluation were correlated with consumer's clothing product knowledge, involvement, risk perception of internet shopping, experiences of internet shopping. Managerial implications are provided for internet shopping mall.

• Fashion & Textile Research Journal
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• v.16 no.4
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• pp.635-644
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• 2014

This study provides basic reference data for brassiere wearing conditions, design preferences of new silver women (50s-60s) and development of brassiere products. We compiled and compared 163 pieces of brassiere (considering of 105 domestic general brassieres and 58 foreign silver brassieres) analyzed using SPSS Statistics 21 program. A survey was then conducted on the actual wearing, purchasing conditions, design preferences for 176 females (50s-60s). The result of this study are as follows: First, comparing actual product conditions (domestic general products and foreign silver products), the ratio of full cup in cup height, V-shape type in neckline shape, long type in front-end length, wide type in wing width, U-shape type in shoulder strap form, wide type in shoulder strap width, no-wire brassieres in breast wire type, all-in-one type in shoulder strap separation, back type in closure type appeared higher than other types of brassiere in domestic general product. Second, a study also showed that 60s women's wearing time is lower than 50s women's; however, 60s women expressed a higher figure and preference for the purchasing ratio in the department store, full cup in cup height, short type in length of brassieres, wide type in wing width, U-shape in shoulder strap form, small type in shoulder strap width, back type in closure type and no-wire brassieres than those in their 50s. It was found they prefer fabric with a high natural content, nude tone color without decoration & pattern and camisole brassieres.

• Journal of Intelligence and Information Systems
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• v.19 no.2
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• pp.39-54
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• 2013

Recent explosive increase of electronic commerce provides many advantageous purchase opportunities to customers. In this situation, customers who do not have enough knowledge about their purchases, may accept product recommendations. Product recommender systems automatically reflect user's preference and provide recommendation list to the users. Thus, product recommender system in online shopping store has been known as one of the most popular tools for one-to-one marketing. However, recommender systems which do not properly reflect user's preference cause user's disappointment and waste of time. In this study, we propose a novel recommender system which uses data mining and multi-model ensemble techniques to enhance the recommendation performance through reflecting the precise user's preference. The research data is collected from the real-world online shopping store, which deals products from famous art galleries and museums in Korea. The data initially contain 5759 transaction data, but finally remain 3167 transaction data after deletion of null data. In this study, we transform the categorical variables into dummy variables and exclude outlier data. The proposed model consists of two steps. The first step predicts customers who have high likelihood to purchase products in the online shopping store. In this step, we first use logistic regression, decision trees, and artificial neural networks to predict customers who have high likelihood to purchase products in each product group. We perform above data mining techniques using SAS E-Miner software. In this study, we partition datasets into two sets as modeling and validation sets for the logistic regression and decision trees. We also partition datasets into three sets as training, test, and validation sets for the artificial neural network model. The validation dataset is equal for the all experiments. Then we composite the results of each predictor using the multi-model ensemble techniques such as bagging and bumping. Bagging is the abbreviation of "Bootstrap Aggregation" and it composite outputs from several machine learning techniques for raising the performance and stability of prediction or classification. This technique is special form of the averaging method. Bumping is the abbreviation of "Bootstrap Umbrella of Model Parameter," and it only considers the model which has the lowest error value. The results show that bumping outperforms bagging and the other predictors except for "Poster" product group. For the "Poster" product group, artificial neural network model performs better than the other models. In the second step, we use the market basket analysis to extract association rules for co-purchased products. We can extract thirty one association rules according to values of Lift, Support, and Confidence measure. We set the minimum transaction frequency to support associations as 5%, maximum number of items in an association as 4, and minimum confidence for rule generation as 10%. This study also excludes the extracted association rules below 1 of lift value. We finally get fifteen association rules by excluding duplicate rules. Among the fifteen association rules, eleven rules contain association between products in "Office Supplies" product group, one rules include the association between "Office Supplies" and "Fashion" product groups, and other three rules contain association between "Office Supplies" and "Home Decoration" product groups. Finally, the proposed product recommender systems provides list of recommendations to the proper customers. We test the usability of the proposed system by using prototype and real-world transaction and profile data. For this end, we construct the prototype system by using the ASP, Java Script and Microsoft Access. In addition, we survey about user satisfaction for the recommended product list from the proposed system and the randomly selected product lists. The participants for the survey are 173 persons who use MSN Messenger, Daum Caf$\acute{e}$, and P2P services. We evaluate the user satisfaction using five-scale Likert measure. This study also performs "Paired Sample T-test" for the results of the survey. The results show that the proposed model outperforms the random selection model with 1% statistical significance level. It means that the users satisfied the recommended product list significantly. The results also show that the proposed system may be useful in real-world online shopping store.