• Journal of the Korean Society of Clothing and Textiles
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• v.40 no.6
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• pp.1150-1163
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• 2016

This study makes use of meta-analysis to statistically integrate the quantitative results of individual research on the influence of fashion product attributes on purchase; in addition, this study utilizes the effect sizes of correlation coefficients. This study was based on 24 individual studies from January 2000 to March 2015. The meta-analysis analyzed 91 effect sizes and 24 studies and calculated the correlation coefficient effect sizes. A random effect model was employed for meta-analysis because the results for the homogeneity test indicated that the effect sizes of each research were heterogeneous. The analysis results are as follows. First, when the total effect sizes of the fashion product attributes that influence clothing purchase decisions were calculated as .256; this indicated that the effect size is slightly below the mid-sized level. Second, upon examining the effect sizes of the categorized fashion product attributes, the intrinsic attributes yielded .222, extrinsic factors yielded .235, and the compiled attributes yielded .420; this demonstrated that the compiled attributes have a larger effect size than individual attributes. Third, when they were measured by the characteristics of study targets, they were larger for a mixed-gender group than women as well as for ordinary citizens than university students. When the effect sizes were measured based on the characteristics of fashion products as suggested in the study, there were significant differences with respect to sportswear, followed by SPA brand clothing, general clothing, fashion accessories, and designer clothing. The cases where the clothing were purchased in non-retail stores were found to have a slightly larger effect size than those of offline retail stores when the effect sizes were measured based on purchase routes; however, the difference was not statistically significant. Next, an investigation of the trend of effect sizes based on published year via the meta regression analysis indicated slightly larger effect sizes as shown in more recent publications, but this was not statistically significant.

• Journal of the Korean Society of Food Culture
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• v.26 no.6
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• pp.673-681
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• 2011

The purpose of this study was to analyze the difference in bakery choice attributes according to consumers' general characteristics and purchasing behavior. Among 350 questionnaires distributed to bakery consumers, 277 complete questionnaires (79.1%) were analyzed. Bakery choice attributes were classified into five factors: "environment and image", "bakery product features", "location", "employee service", and "price and sales promotion"; the mean scores of these factors' importance levels were 3.59, 3.58, 3.49, 3.36, and 3.00, respectively. Males considered 'employee service' factor significantly more than did females. Further, the importance level of 'employee service' factor was significantly greater as consumer's age increased. The importance levels of 'bakery product features' and 'employee service' factors were considered significantly more by consumers who spent KRW10,000-15,000 than those who spent KRW5,000 or less. 'Price and sales promotion' was considered to be more important by consumers who obtained information from the Internet than from the TV and radio. 'Location' factor was considered to be more significant as purchasing frequency increased. Such differences in importance level of bakery choice attributes according to consumers' gender, age, job, and purchasing behavior should be considered and applied to the development of marketing strategies targeted at consumers.

• Journal of the Korean Society of Costume
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• v.50 no.8
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• pp.87-97
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• 2000

The purposes of this study are to classify the male consumers in new generation by evaluating the fashion mania elements and to examine the differences among consumer groups in product attributes, benefits, dressing for self and others, and sensation seeking tendency. Fashion mania elements are compose of purchase frequency, the storage of clothes, the affection toward clothes and fashion knowledge. Data were obtained from 492 adult male living in Seoul and Kyunggi Do. Statistics used for data analysis were frequency, means, one-way Anova, Duncan's multiple range test, factor analysis, cluster analysis using Spss 9.0. The results can be summarized as follows: There consumer groups are identified based on the fashion mania elements: fashion mania, fashion interests, non-fashion mania. The fashion mania group has positive fashion behavior and high fashion attitude, the fashion interests group has high fashion attitude and light fashion behavior, non fashion mania group has light fashion attitude and behavior. Fashion mania group regard intrinsic attributes very highly in order to express individuality, shows the tendency to dress for self strongly rather than to dress for others. And fashion mania group shows a high sensation seeking tendency compared with the remaining groups.

• Journal of the Korean Society of Clothing and Textiles
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• v.32 no.1
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• pp.1-11
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• 2008

The purpose of this study was to investigate the effects of Internet shopping interests on the casual relationships among Internet shopping mall attributes, emotions, and impulse buying behavior. Data were obtained from 414 internet shoppers who had bought fashion products in internet shopping mall. The result showed that the highly interested Internet shoppers, when perceived the product attributes of Internet shopping mall, were more likely to feel positive emotions, and then were more likely to buy fashion products impulsively in Internet shopping. The less perceived the convenience of checkout & trust in Internet, the more negative emotions they had. However, the less interested Internet shoppers were more likely to buy impulsively fashion products with positive emotions when they perceived various product assortments, and were negatively influenced by the high speed of loading and promotions of Internet shopping mall. The findings provide implications of impulse buying behavior in Internet shopping malls for fashion products.

• Proceedings of the KAIS Fall Conference
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• 2003.11a
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• pp.118-126
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• 2003

In data mining, having access to large amount of data sets for the purpose of predictive data does not guarantee good method, even where the size of Real data is Mobile commerce unlimited. In addition to searching expected Goods objects for Users, it becomes necessary to develop a recommendation service based on XML. In this paper, we design the optimized XML Recommender product data. Efficient XML data preprocessing is required, include of formatting, structural, and attribute representation with dependent on User Profile Information. Our goal is to find a relationship among user interested products from E-Commerce and M-Commerce to XDB. Firstly, analyzing user profiles information. In the result creating clusters with analyzed user profile such as with set of sex, age, job. Secondly, it is clustering XML data which are associative products classify from user profile in shopping mall. Thirdly, after composing categories and goods data in which associative objects exist from the first clustering, it represent categories and goods in shopping mall and optimized clustering XML data which are personalized products. The proposed personalized user profile clustering method has been designed and simulated to demonstrate it's efficient.

• Journal of the Korean Society for Precision Engineering
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• v.18 no.12
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• pp.116-123
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• 2001

An automated injection molding design methodology has been developed to optimize multiple quality attributes, which are usually in conflict with each other, in injection molded parts. For the optimization, commercial CAE simulation tools and optimization techniques are integrated into the methodology. To decal with the multiple objective problem the relative closeness computed in TOPSIS(Technique for Order Preference by Similarity to Ideal Solution) is used as a performance measurement index for optimization multiple part defects. To attain robustness against process variation, Taguchi's quadratic loss function is introduced in the TOPSIS. Also, the modified complex method is used as an optimization tool to optimize objective function. The verification of the developed design methodology was carried out on simulation software with an actual model. Applied to production this methodology will be useful to companies in reducing their product development time and enhancing their product quality.

• Korean Journal of Organic Agriculture
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• v.31 no.1
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• pp.29-44
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• 2023

The activation of consumption of environment-friendly agricultural processed foods means not only the growth of environment-friendly agriculture, but also the development of related industries. Therefore, it is necessary to identify and apply the needs and purchasing attributes of environment-friendly agricultural processed food consumers. For this, survey was conducted to adult men and women in their 20s and 60s and a total of 200 copies were used for empirical analysis. In this study, the average difference between importance-satisfaction for purchase attributes of environment-friendly agricultural processed food was verified, and the IPA Matrix was prepared based on this. As a result, in terms of purchasing importance and satisfaction, it was found that those with no experience in purchasing environment-friendly agricultural processed foods regarded product, price, place, promotion as more important than those with experience in purchasing. In case of IPA, product and price factors were all important and satisfactory regardless of purchasing experience. On the other hand, it was found that the key factors for promotion were neither important nor satisfied with consumers regardless of their purchasing experience. Therefore, it is mainly necessary to focus on marketing and mass media promotion. At the same time, various domestic and foreign best practices should be benchmarked and a 4P marketing strategy should be established and promoted.

• Asia Marketing Journal
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• v.14 no.4
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• pp.1-22
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• 2013

A growing gap between market needs and the capabilities of the enterprise prompts repositioning (Corstjens and Dolye 1989). This article examines the strategic repositioning of 'Korando Sports' undertaken by SYMC throughout the period from Jan. 2012 to Jun. 2012, to boost sales volume and market share by entering market of active-lifestyle consumers currently occupied by SUVs. SYMC's experience indicates that it is essential to close the gap between the market needs and the ability of the enterprise to make a shift to new consumer segment with a new positioning. The successful repositioning framework(Ryan et al. 2007) were employed in this paper. This framework is comprised of six elements: core strategic values, strategic flexibility/learning capabilities, customer awareness and sensitivity, external orientation, management commitment, and belief in the product and brand. The evaluation based on the successful framework also confirms that 'Korando Sports' case meets all the requirements of the successful strategic repositioning. This paper provides some of the managerial implications with aim of assisting executives in identifying strategic repositioning opportunities. Primarily, the 'Korando Sports' case affirms the repositioning as a viable strategy and indicates that repositioning is a feasible means for strategic change. Second, this case shows the influence of a target consumer and SYMC's repositioning to follow consumer preference for a particular attribute. Moreover, we can understand how a product formerly considered weak in attributes can enjoy benefits in other segments with the same attributes.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.46 no.4
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• pp.142-151
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• 2023

Sentiment analysis is a method used to comprehend feelings, opinions, and attitudes in text, and it is essential for evaluating consumer feedback and social media posts. However, creating sentiment dictionaries, which are necessary for this analysis, is complex and time-consuming because people express their emotions differently depending on the context and domain. In this study, we propose a new method for simplifying this procedure. We utilize syntax analysis of the Korean language to identify and extract sentiment words based on the Reason-Sentiment Pattern, which distinguishes between words expressing feelings and words explaining why those feelings are expressed, making it applicable in various contexts and domains. We also define sentiment words as those with clear polarity, even when used independently and exclude words whose polarity varies with context and domain. This approach enables the extraction of explicit sentiment expressions, enhancing the accuracy of sentiment analysis at the attribute level. Our methodology, validated using Korean cosmetics review datasets from Korean online shopping malls, demonstrates how a sentiment dictionary focused solely on clear polarity words can provide valuable insights for product planners. Understanding the polarity and reasons behind specific attributes enables improvement of product weaknesses and emphasis on strengths. This approach not only reduces dependency on extensive sentiment dictionaries but also offers high accuracy and applicability across various domains.

• The Journal of Industrial Distribution & Business
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• v.15 no.3
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• pp.11-20
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• 2024

Purpose: This study focuses on the Chinese smartphone market to estimate product attributes influencing Chinese customers' preference for developing new smartphones through conjoint analysis. Research design, data and methodology: The online questionnaire survey is processed among Chinese potential smartphone customers. Conjoint analysis including traditional conjoint analysis (TCA) and choice-based conjoint analysis (CBCA), is used to analyze the useful data of 500. Results: Results indicate that price is the most important predictor while screen size is the least for Chinese customers' preference whether the method is TCA or CBCA. However, the importance of brand, capacity, CPU, and screen design is different. Moreover, based on each smartphone attribute level's utility, the new products with the best combinations are different compared with both methods. Finally, the predicted market shares of the top 3 products are the same with maximum utility rule model between TCA and CBCA. However, when considering with the new best combined product, they are significantly different. Conclusions: Managers should recognize the differences between TCA and CBCA and select the best method to develop new smartphones for sustainable business in the Chinese competitive market based on the important attributes of price, brand, capacity, CPU, screen design, and size.