• 한국산학기술학회논문지
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• 제17권11호
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• pp.453-462
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• 2016

인터넷의 등장으로 고객들은 자신의 의견이나 생각을 인터넷 공간에서 다른 사람들과 공유하기 시작하였다. 이에 따라 기업은 인터넷에서 수집된 데이터를 이용하여 기업에 활용할 수 있는 유의미한 결과를 찾으려는 노력을 하고 있다. 과거 설문조사를 기반으로 고객의 브랜드에 대한 태도나 만족도, 충성도 등을 분석하던 방식에서 소셜 네트워크 서비스(Social Network Service) 등에서 추출된 빅데이터를 이용하여 분석하려는 시도가 이루어지고 있다. 본 연구에서는 SNS에서 수집된 결과를 활용하여 브랜드간의 군집을 발견하는 프레임워크를 제시하고자 한다. 또한 제시된 프레임워크의 실무적용 가능성을 살펴보기 위해 자동차 산업에 대한 사례연구를 수행하였다. 두 개의 브랜드 이름이 소셜 미디어에서 동시에 언급되는 빈도가 높을수록 고객이 두 브랜드를 유사하게 인식한다는 가정 하에 자동차 브랜드 사이의 유사성을 측정하고 거리의 개념으로 변화한 후 다차원 척도법을 이용하여 3차원 상에 표시하였다. 또한 자동차 브랜드에 대한 고객의 인식을 파악하기 위해 유사한 브랜드간의 군집을 도출하고 각 군집을 특징을 기술하였다. 아울러 연구의 한계점과 향후 연구방향을 제시하였다.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2005년도 추계학술대회 학술발표 논문집 제15권 제2호
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• pp.271-275
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• 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
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• 제5권4호
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• pp.353-359
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• 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).

• 패션비즈니스
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• 제17권6호
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• pp.125-140
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• 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.

• 복식문화연구
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• 제26권3호
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• pp.427-449
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• 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.

• 한국의류학회지
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• 제22권7호
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• pp.833-842
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• 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.

• 융합정보논문지
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• 제9권4호
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• pp.59-67
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• 2019

기존 연구들은 브랜드확장의 효과성을 예측하기 위한 지표로 구매의도를 주로 활용하고 있다. 이와 달리 본 연구는 브랜드확장된 신제품에 대한 소비자 반응을 예측하는데 더 적절한 지표로 시용의도를 제시함으로써 선행요인을 바탕으로 도출한 영향요인인 모브랜드 태도, 지각된 유사성, 모브랜드 소비경험이 확장브랜드 제품의 시용의도에 미치는 영향을 분석하고자 한다. 구체적으로, 모브랜드 태도가 확장브랜드 제품 시용의도에 미치는 영향을 분석하고, 또한 두 변인간의 관계에서 지각된 유사성과 모브랜드 소비경험의 조절적 영향력을 분석하고자 한다. 본 연구의 목적을 달성하기 위해 브랜드확장 제품의 사용경험이 있는 소비자들을 대상으로 실험조사와 설문조사를 실시하였고 분석에는 최종적으로 186개의 자료가 사용되었으며 회귀분석과 군집분석을 실시하였다. 분석결과, 브랜드확장제품의 시용의도에 대한 모브랜드 태도의 강력한 영향력을 확인할 수 있었다. 또한 지각된 유사성이 높을수록 모브랜드 태도가 브랜드확장 제품의 시용의도에 미치는 영향이 커지는 것으로 나타났고, 모브랜드에 대한 소비경험이 많을수록 두 변인 간의 관계가 더 긍정적인 영향을 미치는 것으로 나타났다. 이를 통해 기존연구와는 달리 소비자 관점에서의 브랜드확장 제품의 시용의도에 영향을 미치는 중요한 요인을 밝혔다.

• 한국의류산업학회지
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• 제23권4호
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• pp.480-490
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• 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.

• 복식문화연구
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• 제32권2호
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• pp.199-214
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• 2024

Until now, research on consumers' purchasing behavior has primarily focused on psychological aspects or depended on consumer surveys. However, there may be a gap between consumers' self-reported perceptions and their observable actions. In response, this study aimed to investigate consumer purchasing behavior utilizing a big data approach. To this end, this study investigated the purchasing patterns of fashion items, both online and in retail stores, from a data-driven perspective. We also investigated whether individual consumers switched between online websites and retail establishments for making purchases. Data on 516,474 purchases were obtained from fashion companies. We used association rule analysis and K-means clustering to identify purchase patterns that were influenced by customer loyalty. Furthermore, sequential pattern analysis was applied to investigate the usage patterns of online and offline channels by consumers. The results showed that high-loyalty consumers mainly purchased infrequently bought items in the brand line, as well as high-priced items, and that these purchase patterns were similar both online and in stores. In contrast, the low-loyalty group showed different purchasing behaviors for online versus in-store purchases. In physical environments, the low-loyalty consumers tended to purchase less popular or more expensive items from the brand line, whereas in online environments, their purchases centered around items with relatively high sales volumes. Finally, we found that both high and low loyalty groups exclusively used a single preferred channel, either online or in-store. The findings help companies better understand consumer purchase patterns and build future marketing strategies around items with high brand centrality.

• 한국산학기술학회논문지
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• 제22권3호
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• pp.303-309
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• 2021

본 논문은 20-30대 소비자들이 사회적 가치가 높은 명품, 매스티지 브랜드와 복제품에 대해 어떤 태도를 가지고 구분하는지, 과시소비성향과 동조성으로 설명할 수 있을지를 탐색하였다. 브랜드들에 대한 태도와 구매의도의 유사성을 기준으로 20-30대 소비자를 구분하고, 집단별로 동조성과 과시소비 성향의 하위차원에서의 차이를 연구하였다. 군집분석을 통해 20-30대 소비자는 네 집단으로 구분되었고, 다변량분산분석을 실시하여 각 집단 간의 차이를 확인하였다. 개성추구성향(F=4.282, p=.006)과 브랜드지향성향(F=23.178, p=.000)은 명품과 매스티지 브랜드와 연관이 있었고, 유행추구성향(F=8.376, p=.000)은 명품과 매스티지 브랜드를 매우 좋아하는 집단과 복제품에도 관심이 있는 집단에서 높게 나타났다. 고가격추구성향은 유의한 차이가 없었다. 동조성(F=3.537, p=.015)은 명품과 매스티지에 대해 약간 좋아하지만 복제품은 싫어하는 집단만 제외하면 모두 높았다. 본 연구는 상징적 의미가 큰 브랜드들에 대한 20-30대 소비자의 태도와 구매의도를 통합적으로 고찰한 연구로서 향후 소비자의 브랜드 범주화에 대한 연구로 발전시키기 위한 탐색적 연구로 의미가 있다.