• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.17 no.11
• /
• pp.453-462
• /
• 2016

Since the Internet provides a way of expressing and sharing Internet users' mindsets, corporate marketers want to acquire measurable and actionable insights from web data. In the past, companies used to analyze the attitude, satisfaction, and loyalty of consumers toward their brands using survey data, whereas nowadays this is done using the big data extracted from Social Network Services. In this study, we propose a framework for clustering brand names using the social metrics gathered on social media. We also conduct a case study of the automobile industry to verify the feasibility of the proposed framework. We calculate the brand name distance for each pair of brand names based on the total number of times that they are mentioned together. These distances are used to project the brand name onto a 3-dimensional space using multidimensional scaling. After the projection, we found the clusters of brand names and identified the characteristics of each cluster. Furthermore, we concluded this paper with a discussion of the limitations and future directions of this research.

• Proceedings of the Korean Institute of Intelligent Systems Conference
• /
• 2005.11a
• /
• pp.271-275
• /
• 2005

In this research, we propose a Unified Fuzzy rule-based knowledge Inference Systems UFIS) to help the expert in cosmetic brand detection. Users' preferred cosmetic product detection is very important in the level of CRM. To this Purpose, many corporations trying to develop an efficient data mining tool. In this study, we develop a prototype fuzzy rule detection and inference system. The framework used in this development is mainly based on two different mechanisms such as fuzzy rule extraction and RDB (Relational DB)-based fuzzy rule inference. First, fuzzy clustering and fuzzy rule extraction deal with the presence of the knowledge in data base and its value is presented with a value between $0\∼1$. Second, RDB and SQL(Structured Query Language)-based fuzzy rule inference mechanism provide more flexibility in knowledge management than conventional non-fuzzy value-based KMS(Knowledge Management Systems)

• International Journal of Fuzzy Logic and Intelligent Systems
• /
• v.5 no.4
• /
• pp.353-359
• /
• 2005

In this research, we propose a Unified Fuzzy rule-based knowledge Inference Systems (UFIS) to help the expert in cosmetic brand detection. Users' preferred cosmetic product detection is very important in the level of CRM. To this purpose, many corporations trying to develop an efficient data mining tool. In this study, we develop a prototype fuzzy rule detection and inference system. The framework used in this development is mainly based on two different mechanisms such as fuzzy rule extraction and RDB (Relational DB)-based fuzzy rule inference. First, fuzzy clustering and fuzzy rule extraction deal with the presence of the knowledge in data base and its value is presented with a value between 0 -1. Second, RDB and SQL (Structured Query Language)-based fuzzy rule inference mechanism provide more flexibility in knowledge management than conventional non-fuzzy value-based KMS (Knowledge Management Systems).

• Journal of Fashion Business
• /
• v.17 no.6
• /
• pp.125-140
• /
• 2013

The aim of this study was to analyze e-commerce sites of luxury fashion brands in order to provide insights on how to enhance online site quality. For the research, forty-eight components of thirty-one luxury fashion brands' e-commerce sites were investigated during October 2013. For the analysis of clustering e-commerce site components and segmenting e-commerce sites of luxury brands, a hierarchical cluster analysis was applied through using the Ward's method and squared Euclidian distance for binary data. Further, Fisher's exact test was applied in order to distinguish three groups of characteristics in the luxury e-commerce sites. These analyses were carried out by SPSS 21. The result indicated that the components of e-commerce sites were grouped into three categories: basic elements, additional elements and elements of building brand identity. These components were categorized by whether their functions were basic and essential or additional and advanced. The other norm of categorization was related to brand identity. Furthermore, the luxury brands' e-commerce sites were segmented into three groups: a group of endeavoring to promote goods, a group of undistinguished performance, and a group of endeavoring to intensify brand identity. In this segmentation, brand identity or promotional aspects were decisive. Overall, luxury brands were trying to convey their traditional strength through their e-commerce sites. In order to achieve this purpose, brand identity or promotional aspects played an important role.

• The Research Journal of the Costume Culture
• /
• v.26 no.3
• /
• pp.427-449
• /
• 2018

The current study aimed to segment Mongolian female consumers based on luxury consumption values and to compare lifestyle, demographic characteristics, purchase behavior, and perceived brand personality among the segments. The survey was administered to consumers who had purchased luxury products in Ulaanbaatar, Mongolia. A total of 184 surveys were used for data analysis. Exploratory factor analysis revealed five luxury values: quality value, hedonic value, conspicuous value, social value, and unique value. Using the five luxury values, clustering analysis was conducted, showing that there were four distinct segments: passive shoppers, showoffs, rational value groups, and hedonists. ANOVAs and chi-square analyses revealed that these four segments differed in consumption values, demographic characteristics, lifestyle dimensions (including appearance consciousness, leisure orientation, life enjoyment, and achievement orientation), and purchase behavior (including purchase frequency, price of products purchased, and product selection criteria). Moreover, value segments showed differences in five dimensions of luxury brand personality: sincerity, professionalism/attractiveness, excitement, materialism, and sophistication. The results suggest that consumption values serve as a significant basis for segmentation. Furthermore, the current study indicates that value segments can be described as consumers' perceived brand personality. The study concludes with a discussion of the results, theoretical and practical implications, and limitations.

• Journal of the Korean Society of Clothing and Textiles
• /
• v.22 no.7
• /
• pp.833-842
• /
• 1998

The purpose of this study is to (1) investigate on the impulse purchase tendency of women who buy women's character clothing brands and (2) to clarify the relationship between the women's impulse purchase tendency and the marketing factors, and the brand image. The subjects were 203 women in their twenties and thirties who had purchased the women's character clothing brands in last six months living in Seoul. The data were collected by self-administered questionnaire and were analyzed by frequency, percentage, t-test, clustering analysis and MDS(Multi-Dimensional Scale). The results of the study were as follows: (1)66.0% of the women were categorized as the group of high-degree of impulse purchase tendency and 34.0% of the women were identified as the group of low-degree of impulse purchase tendency. (2) In identifying the relationship between the marketing factors and the impulse purchase tendency, the group of the high-degree of impulse purchase tendency was affected by the marketing factors such as new and fashionable products, status of display, advertising and discout selling. (3) Brand image was not statistically significant according to the impulse purchase tendency. As a whole, 'Obzee' was recognized as unique-style and sexy brand, 'Time' and 'Mine' were thought as the reasonable-prince and basic-style brands, 'Deco' were clarified as the intellectual-image brand, and 'Ego' and 'Telegraph' were revealed as high-price-image brands.

• Journal of Convergence for Information Technology
• /
• v.9 no.4
• /
• pp.59-67
• /
• 2019

Most of the prior researches in brand extension evaluation have utilized purchase intention as a n effective variable to assess the effectiveness of brand extensions. In contrast, the author proposes that trial intention is to better predict consumers' behavioral response in the newly launched brand extension markets where relate to high risk and uncertainty. Furthermore, the study explores the effects of attitude toward parent brand and consumers' characteristics (perceived similarity and consumption experience) on trial intention of brand extensions. In order to achieve the purpose of the study, the data collection was conducted for actual consumers who had experience using parent brand products. This study employed experiment and questionnaire survey and collected data of 186 was analyzed using clustering analysis and regression analysis. The main results are as follows. First, attitude toward parent brand has a positive effect on trial intention of the extensions. Second, perceived similarity and consumption experience of parent brand have moderating effects on the relation of attitude toward parent brand and trial intention of brand extensions. The results provide that both industry and academic researchers with a guide to process trial intention of brand extension from a comprehensive perspective.

• Fashion & Textile Research Journal
• /
• v.23 no.4
• /
• pp.480-490
• /
• 2021

Sales forecasting is crucial for many retail operations. For apparel retailers, accurate sales forecast for the next season is critical to properly manage inventory and plan their supply chains. The challenge in this increases because apparel products are always new for the next season, have numerous variations, short life cycles, long lead times, and seasonal trends. In this study, a sales forecasting model is proposed for apparel products using machine learning techniques. The sales data pertaining to outerwear items for four years were collected from a Korean sports brand and filtered with outliers. Subsequently, the data were standardized by removing the effects of exogenous variables. The sales patterns of outerwear items were clustered by applying K-means clustering, and outerwear attributes associated with the specific sales-pattern type were determined by using a decision tree classifier. Six types of sales pattern clusters were derived and classified using a hybrid model of clustering and decision tree algorithm, and finally, the relationship between outerwear attributes and sales patterns was revealed. Each sales pattern can be used to predict stock-keeping-unit-level sales based on item attributes.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.22 no.3
• /
• pp.303-309
• /
• 2021

This study examined how consumers in their 20s and 30s perceive luxury goods, masstige brands, and counterfeits, which have high social value, and whether the propensity for conspicuous consumption and conformity can explain them. Consumers were classified based on the similarity of attitudes toward these brands and purchase intentions. The groups were compared on the sub-dimensions of conspicuous consumption and conformity. Clustering analysis identified four groups, and the MANOVA result confirmed the differences among the groups. Personality (F=4.282, p=.006) and brand orientation (F=23.178, p=.000) were positively related to luxury and masstige brands. Fashion orientation (F=8.376, p=.000) was high for both groups, which likes luxury and masstige brands very much, and which likes counterfeits. High-price orientation did not make any significant difference among the groups. Conformity (F=3.537, p=.015) was high for all the groups, except for the group that liked luxury and masstige brands and did not like counterfeits. This study comprehensively examined the attitudes and purchase intentions of luxury and masstige brands and their counterfeits and can be the groundwork for further research on brand categorization.

• Korean journal of food and cookery science
• /
• v.28 no.6
• /
• pp.721-729
• /
• 2012

This paper aimed to investigate the influence of consumer lifestyle on consumer selection of bakery cafe attributes. Data were collected through a self-administered questionnaire by 403 random consumers between the ages 20s and 30s in several bakery cafes in Seoul and Gyonggi area. Different methods of statistical analysis had been used such as frequency analysis, factor analysis, k-means clustering analysis, cross tabulation, one way ANOVA and Duncan's multiple range test with SPSS for Window 13.0 package. First, when analyzing the 16 questions of comsumer lifestyles, four factors were extracted: 'dining out-oriented factor', 'achievement-oriented factor', 'brand-oriented factor', and 'health-oriented factor'. Second, the respondents were divided into three groups by k-means cluster analysis: no interest group, dining-out & value oriented group, and health-brand oriented group. Third, consumer's bakery cafe attributes were categorized into five factors including 'food', 'convenience and image', 'store promotion', 'positive dining experience', and 'menu & merchandises'. Finally when analyzing the differences in the selection of bakery cafe attributes according to consumer's lifestyles, it showed a significant differences.