• Journal of the Korea Fashion and Costume Design Association
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• v.18 no.2
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• pp.1-14
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• 2016

사회적기업의 브랜드를 추구하는 패션 소비층은 개인적인 가치 기준을 바탕으로 합리적인 소비생활을 하며 브랜드 이미지를 중시하고 자신만의 감도를 찾는 공통된 특징을 가지고 있다. 이러한 추세에 따라 패션 사회적 브랜드는 새로운 각도에서 소비자들을 이해하며 환경변화에 능동적으로 대응할 필요성이 요구되고 있다. 이에 본 연구에서는 패션 사회적 브랜드-소비자 관계의 세부적 요인이 브랜드 자산 구성요소들에 미치는 구조적 관계에 대해 규명하며, 연구결과를 기준으로 패션사회적 브랜드가 소비자의 구매행동을 예측하여 보다 효율적인 브랜드 전략을 진행하는데 있어 시사점을 제공하고자 한다. 이를 위해 2015년 4월 1일부터 30일까지 ${\bigcirc}{\bigcirc}$ 패션 사회적 브랜드 상품구매경험자를 800명을 대상으로 설문을 실시하였으며, SPSS 20.0, AMOS 20.0을 사용하여, 빈도분석, 신뢰도 분석, 요인분석 및 경로분석을 실시하였다. 이상을 바탕으로 도출된 연구결과는 다음과 같다. 첫째, 브랜드-소비자 관계의 행위적 몰입, 인지적 믿음은 브랜드 인지도에 유의한 영향을 미쳤으나, 감성적 유대는 브랜드 인지도에 영향을 미치지 않았다. 둘째, 브랜드-소비자 관계의 행위적 몰입, 감성적 유대, 인지적 믿음은 브랜드 이미지에 유의한 영향을 미쳤다. 셋째, 패션 사회적 브랜드 이미지는 브랜드 태도 및 브랜드 충성도에 유의한 영향을 미쳤다. 넷째, 패션 사회적 브랜드의 지각된 품질은 브랜드 이미지, 브랜드 태도, 브랜드 충성도에 유의한 영향을 미쳤다. 다섯째, 패션 사회적 브랜드 태도는 브랜드 충성도에 유의한 영향을 미쳤다.

• Proceedings of the Korean Society for Emotion and Sensibility Conference
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• 2001.05a
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• pp.253-261
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• 2001

화장품의 사용감은 개개인에 따라 다양한 기호를 나타내며 상대적이고 감성적인 개념들이 우선하게 된다. 이러한 관능특성들을 보다 객관적이며, 과학적으로 고찰하고자 하는 연구분야가 바로 관능평가이다. 본 연구에서는 메이크업 단계 중 베이스 메이크업에 속하는 제품인 파운데이션의 관능 특성을 보다 객관적이며 신뢰성 있게 평가, 분석하는 전문패널 평가 시스템을 구축하기 위하여 사내 여성을 대상으로 discriminative 및 descriptive 테스트를 실시하였다. 이를 통해 적합한 패널을 선정하였고 일정하게 규정된 일련의 교육과정들을 통해 패널을 훈련시킴으로써 베이스 메이크업 전문 패널 평가 시스템을 구축하였다. 그 후 파운데이션에 대해 질감별 제품을 평가하도록 한 후 이러한 방법으로 수집된 데이터를 신뢰성 있는 통계적 분석법을 이용하여 제품의 사용감 특성이 위치되니 2차원적 공간영역과 제품별 사용감의 특성을 분석하였다. 그 후 분석된 결과를 자사 브랜드 메이크업 라인의 파운데이션 제품에 응용하여 제품을 차별화 시키도록 설계하고 질감별 특징적 사용감과 적합한 특성강도를 제시한 후 이를 나타내는 처방의 제품을 결정하였다. 최종적으로 출시된 제품을 실제 소비자들을 통해 기호형 관능평가를 다시 한번 실시하였으며, 그 결과 실제 느끼는 사용감각 특성과 상품개발 계획 시 소구하고자 했던 관능특성이 일치하게 나타나 사용감 설계의 객관성을 검증하였다. 따라서, 본 연구는 이와 같은 결과를 통해 관능평가를 제품개발에 응용한 활용방안으로 보고자 하였다.

• Proceedings of the Korea Information Processing Society Conference
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• 2002.11c
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• pp.2133-2136
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• 2002

인터넷 특성상 방대한 양의 정보와 상품 등으로 사용자들이 원하는 정보를 찾기 위해서 많은 시간을 낭비하고 있는 실정이다. 이러한 사용자의 시간 소모를 중이기 위해서 추천 시스템이 개발되었다. 현재 인터넷 상의 추천 기술 중에서 가장 많이 사용하는 기법으로는 협력적 여과(Collaborative filtering) 방법이다. 그러나, 협력적 추천 방법으로 추천 받기 위해서는 특정수 이상의 아이템에 대한 평가가 필요하며, 또한 비슷한 성향을 가지는 일부 사용자 정보에 근거하여 추천함으로써 나머지 사용자 정보를 무시하는 경향이 있다. 이러한 문제점이 발생되므로 최근에는 데이터 마이닝(Data Mining) 기법 중 연관 규칙(Association Rule)을 이용한 추천 시스템이 개발되고 있다[1,10]. 그러나, 연관 규칙 기법은 개인별 사용자의 성향을 반영하지 못하는 단점이 있다[4]. 연관 규칙은 단지 대용량 데이터 베이스에서 아이템간의 지지도(Support)와 신뢰도(Confidence)에 근거하여 규칙을 발견하는 특징을 가지고 있기 때문이다. 즉 개인성향을 무시하고 아이템간의 연관성만을 근거로 하여 아이템을 추천하기 때문이다. 본 논문에서는 효율적인 연관 규칙을 이용한 개인화 추천 시스템을 구현하기 위해서 연관 규칙과 여과 방법을 통합한 시스템을 제안한다. 본 시스템에 대하여 성능 비교 실험을 수행함으로써 제안한 방법의 타당성을 제시한다.

• Journal of the Korean Home Economics Association
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• v.46 no.4
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• pp.37-45
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• 2008

The purpose of this study is to investigate how relationship benefit affect trust and commitment, and how trust and commitment affect relationship continuity intention between apparel purchaser and salesperson. For the research, it was surveyed to 230 females in their 20's, who lives in Seoul and Kyeonggi on Feb 10th to 15th in 2007. With SPSS 11.0 program, the data was analysed by frequency analysis, reliability analysis, factor analysis and multiple regression analysis. The results are as follows: First, regarding to the results of factor analysis on relationship benefit, trust and commitment, the relationship benefit factor was divided into the social, psychological and economic benefits. The trust factor was divided into the professional and considerable trust, and the commitment factor was divided into the emotional and calculative commitment. Second, as investigating how relationship benefit affect trust and commitment during purchasing apparel, social and psychological benefits affected professional trust. The psychological benefit only affected to considerable trust. Also social and psychological benefit were statically affected to emotional commitment, economic benefit and psychological benefit were affected to calculative commitment. Third, relationship continuity intention was affected to professional and considerable trust, and emotional commitment.

• Journal of the Korean Society of Clothing and Textiles
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• v.33 no.11
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• pp.1817-1827
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• 2009

This study analyzes how the purchase reviews of fashion merchandise influence consumer trust, satisfaction, commitment, word-of-mouth intention, and repurchase intention in internet shopping malls. The survey was conducted from October $15^{th}$ to December $5^{th}$ in 2008, and 368 responses were used in the data analysis. The statistical analysis methods were frequency analysis, factor analysis, reliability analysis, and multiple regression analysis. The results show that the purchase reviews factors of fashion merchandise in internet shopping malls were amusement, assentation, overstatement, genuineness, and usefulness. The assentation, genuineness, and usefulness of purchase reviews have an effect on consumer trust and satisfaction. The amusement, overstatement, and usefulness of purchase reviews have an effect on the emotional commitment of consumers, while the amusement, assentation, overstatement, genuineness, and usefulness of purchase reviews influence the reasonable commitment of consumers. Consumer trust and commitment effect word-of-mouth intention and repurchase intention in internet shopping malls.

• Journal of the Korean Society of Clothing and Textiles
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• v.32 no.5
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• pp.834-845
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• 2008

The purpose of this study is to find out the important factors and efficient strategies concerning Internet marketing. The areas of study interest are, the perceived risk, trust, usefulness, Shopping-mall attitude, and purchase intention. To fulfill this objectives, First, a survey was performed targeting customers with first-hand experience with fashion merchandise in Internet shopping-mall. Second, the improbability sampling method was used on aged from 20s to 40s, and the survey was performed over a one month period. A total of 806 questionnaires. The empirical studies were summarized as follows. First, the exchange/return/delivery risk and social/psychological risk had an effect on the perceived trust in Internet fashion shopping mall. Second, the perceived trust had an effect on the perceived usefulness, the attitude toward using and intention of repurchase in Internet fashion shopping mall. Third, the perceived usefulness had an effect on the attitude toward using and intention of repurchase in Internet fashion shopping mall. Forth, the attitude toward using had an effect on intention of repurchase in Internet fashion shopping mall.

• Journal of the Korean Society of Clothing and Textiles
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• v.31 no.8
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• pp.1168-1179
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• 2007

The objective of this research is to validate the BRQ(Brand Relationship Quality) Construct perceived by fashion product consumers. In order to establish and verify the BRQ scale, qualitative survey and quantitative survey were conducted together. 1592 copies of questionnaire were distributed to women in their 20s to 40s living in Seoul and other metropolitan areas from Dec. 26, 2005 to Jan. 8, 2006, and 723 copies of them were used for statistical data. Samplel(n=482)was used for empirical analysis, and sample2(n=241) was used for cross validity test. The data was analyzed using Exploratory Factor Analysis, Confirmatory Factor Analysis, and Pearson's Correlation Analysis. BRQ emerged from exploratory factor analysis as the hierarchical construct composed of six facets including 'self-connective attachment', 'symbol/mystery', 'trust', 'nostalgia', 'intimacy', and 'knowledge'. As the fit of this structural model was not good as a result of Confirmatory Factor Analysis, it was revised to have better fitting. Finally, empirical survey results indicate the hierarchical construct consisting of eight distinct BRQ facets including 'love/commitment', 'self-connection', 'symbol', 'mystery', 'trust', 'nostalgia', 'intimacy', and 'knowledge' as best representing the final 39item BRQ Scale. Reliability, construct validity, and cross validity of the construct were verified.

• Proceedings of the Korea Information Processing Society Conference
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• 2021.11a
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• pp.797-800
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• 2021

인공지능을 활용한 주가 예측 모형을 실제 금융 서비스에 도입한 사례가 많아지고 있다. 주식 데이터는 일반적인 시계열 데이터와 다르게 예측을 어렵게 하는 복합적인 요소가 존재하며 주식은 리스크가 큰 자산 상품 중 하나이다. 주가 예측 모형의 활용 가능성을 높이기 위해선 성능을 향상시키는 것과 함께 모델을 해석 가능한 형태로 제시해 신뢰성을 향상시킬 필요성이 있다. 본 논문은 주가 전망 결정 방법에 따른 예측 결과를 비교하고, 설명 가능성을 부여해 모형 개선했다는 것에 의의가 있다. 연구 결과, 주가 전망을 장기적으로 결정할수록 정확도가 증가하고, XAI 기법을 통해 모형의 개선 근거를 제시할 수 있음을 알 수 있었다. 본 연구를 통해 인공지능 모형의 신뢰성을 확보하고, 합리적인 투자 결정에 도움을 줄 수 있을 것으로 기대한다.

• Journal of Distribution Research
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• v.14 no.2
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• pp.67-95
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• 2009

The purpose of this study is to empirically examine the transference of trust process, an important factor to consumer's purchase decision-making. Even though several researchers have discussed the trust transference process, there is no research related to this concept. Specifically we have focused on the transference of trust from the retailer to low involvement private label (PL) products. PL products were chosen as transference of trust occurs under ambiguity due to lack of information about the product and their manufacturer. PL products provide relatively less information than national brand (NB) products. In addition, retailers have been rapidly expanding their PL product categories. To identify the theoretical and empirical limitations of prior studies, we discuss several theories explaining the transference of trust: 'Balance theory' and 'availability heuristic' in transference of cognitive trust; 'affective transference' and 'affect as information' in transference of affective trust. An empirical test was performed. A self completion questionnaire was developed and administered to a convenience sample of PL users. 206 usable questionnaire were received. The results show that the transference of trust plays a mediating role linking the retailer to the manufacturer and to the product. Although our model, which included the transference process of trust as a mediating effect, did not improve the competitive model, the coefficients of the respective paths were found to be better. This study confirms the transference of cognitive trust from the retailer to both the manufacturer and the product, but not for affective trust. We offer the explanation that PL products may tend to have affective trust resulting from brand familiarity but not to their PL manufacturers.

• Journal of Intelligence and Information Systems
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• v.23 no.1
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• pp.127-141
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• 2017

Advances in Internet technologies and the proliferation of mobile devices enabled consumers to approach a wide range of goods and services, while causing an adverse effect that they have hard time reaching their congenial items even if they devote much time to searching for them. Accordingly, businesses are using the recommender systems to provide tools for consumers to find the desired items more easily. Association Rule Mining (ARM) technology is advantageous to recommender systems in that ARM provides intuitive form of a rule with interestingness measures (support, confidence, and lift) describing the relationship between items. Given an item, its relevant items can be distinguished with the help of the measures that show the strength of relationship between items. Based on the strength, the most pertinent items can be chosen among other items and exposed to a given item's web page. However, the diversity of the measures may confuse which items are more recommendable. Given two rules, for example, one rule's support and confidence may not be concurrently superior to the other rule's. Such discrepancy of the measures in distinguishing one rule's superiority from other rules may cause difficulty in selecting proper items for recommendation. In addition, in an online environment where a web page or mobile screen can provide a limited number of recommendations that attract consumer interest, the prudent selection of items to be included in the list of recommendations is very important. The exposure of items of little interest may lead consumers to ignore the recommendations. Then, such consumers will possibly not pay attention to other forms of marketing activities. Therefore, the measures should be aligned with the probability of consumer's acceptance of recommendations. For this reason, this study proposes a model-based approach to combine those measures into one unified measure that can consistently determine the ranking of recommended items. A regression model was designed to describe how well the measures (independent variables; i.e., support, confidence, and lift) explain consumer's acceptance of recommendations (dependent variables, hit rate of recommended items). The model is intuitive to understand and easy to use in that the equation consists of the commonly used measures for ARM and can be used in the estimation of hit rates. The experiment using transaction data from one of the Korea's largest online shopping malls was conducted to show that the proposed model can improve the hit rates of recommendations. From the top of the list to 13th place, recommended items in the higher rakings from the proposed model show the higher hit rates than those from the competitive model's. The result shows that the proposed model's performance is superior to the competitive model's in online recommendation environment. In a web page, consumers are provided around ten recommendations with which the proposed model outperforms. Moreover, a mobile device cannot expose many items simultaneously due to its limited screen size. Therefore, the result shows that the newly devised recommendation technique is suitable for the mobile recommender systems. While this study has been conducted to cover the cross-selling in online shopping malls that handle merchandise, the proposed method can be expected to be applied in various situations under which association rules apply. For example, this model can be applied to medical diagnostic systems that predict candidate diseases from a patient's symptoms. To increase the efficiency of the model, additional variables will need to be considered for the elaboration of the model in future studies. For example, price can be a good candidate for an explanatory variable because it has a major impact on consumer purchase decisions. If the prices of recommended items are much higher than the items in which a consumer is interested, the consumer may hesitate to accept the recommendations.