• The Journal of Asian Finance, Economics and Business
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• 제6권3호
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• pp.193-203
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• 2019

The issue of health risks from consuming unhealthy product is an important issue that is happening right now. Both developed and developing countries are already aware of the need for attention to the health-risk products. One tool that is believed to be able to change the consumption behavior of the health-risk products is the use of warning label on product packaging. As a persuasive act, both visual and textual warning label are believed to be able to change people's consumption behavior. In addition to the labels that contain health hazards, this research also uses social consequence contents. The main targets of such unhealthy product marketing are children and adolescents. Correspondingly, this study targets the age groups of kids and tweens. The method used in this research is experiment, involving 180 participants from two age groups namely kids and tweens. As a result, the study found that the influence of warning label on the age of tweens is greater in the age of the children. Meanwhile, the use of visual and textual warning label using social consequences contents, proved to be effective at the age of tweens. These results are useful for enrich social marketing subjects, especially within warning label research.

• 대한가정학회지
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• 제35권1호
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• pp.47-58
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• 1997

The purpose of this study was to investigate the relationship between children's gender role attitude measured by component model and social competency. Subjects were 232 elementary school children: 113 4th graders and 119 6th graders. The main results were as follows. First there were significant differences in mean scores of gender role attitude with age and sex variable. And among three dimensions of component model(i.e, gender label-component links within-component links between-component links) the difference was most discriminant in gender label-component links. Second there were significant relationship between gender role attitude and social competency. Among three dimensions of gender role attitude the most predictor variable for social competency was gender label-component links. And among four dimensions of social competency the most effective criterion variable for gender role attitude was leadership. And there were significant differences in social competency score with mother's educational level and sex of children as well as gender role attitude. In conclusion children's gender role attitude influence their social competency. More flexible gender role attitude they have more improved in their social competency , especially in boys.

• The Journal of Asian Finance, Economics and Business
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• 제8권2호
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• pp.1063-1070
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• 2021

The study aims to investigate the role of consumer's social risk perceptions in retailing private label brands. Since private label brands are exclusively available at retail stores, consumers make their purchase decisions regarding them based on the image of that retail outlet. While buying them, risk perceptions are influenced by the retail store's image. The study identifies various retail store dimensions. For this purpose, primary data was collected using a survey questionnaire that was administered to a representative sample of retail store consumers in Riyadh. The data was analyzed and exploratory factor analysis was applied using SPSS 25 version to extract store image dimensions. The results showed six significant dimensions of retail store image namely 'Sales Staff', 'Promotion', 'Store Environment', 'Store Services', 'Product Assortment', and 'Customer Convenience'. Regression Analysis was performed and the effect of these retail store image dimensions was tested on social risk perceptions of consumers. Results indicate that store image dimensions significantly influence consumer's perceived social risk perceptions. However, the relationship is not consistent across all the six identified store image dimensions. The study brings forth several valuable consumer insights and the findings of the study have some very interesting and practical implications for retailers.

• 복식문화연구
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• 제23권3호
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• pp.523-536
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• 2015

Corporate association-which refers to consumers' beliefs, knowledge, perceptions, and evaluations of a corporation -can affect consumers' purchasing intentions. Corporate association consists of corporate ability association and corporate social responsibility association. Corporate ability association refers to a company's product quality, corporate innovation, productivity, consumer orientation, and after service. Corporate social responsibility association, which refers to the social perspective a company has of its responsibility to society, can affect corporate image and consumers' purchasing intentions. Eco-labeling for protecting and sustaining the environment is one of the important green marketing strategies in the fashion business that can influence corporate association and consumers' purchasing intentions. The purpose of this study was to investigate the effect of consumers' eco-label recognition on their corporate association and intentions to purchase eco-friendly fashion products. Questionnaires were distributed to consumers. The 263 usable questionnaires that were returned were analyzed by descriptive statistics, Cronbach's alpha, factor analysis, regression analysis, and t-test. The results were as follows: There was a significant effect of eco-label recognition on corporate association (ability association and social responsibility association). Eco-label recognition and corporate association were found to significantly affect consumers' purchasing intentions. Regarding the eco-friendly fashion product buying experience, there was no significant difference on corporate association and buying intention, but there was significant difference on eco-label recognition.

• 한국전자통신학회논문지
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• 제15권4호
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• pp.709-716
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• 2020

소셜 미디어에서 일반적으로 게시물을 올릴 때 이미지의 태그 정보를 사용하는데, 태그를 이용하여 주로 검색이 이루어지기 때문이다. 사용자는 태그를 게시물에 붙임으로써 게시물을 많은 사람들에게 노출시키길 원한다. 또한, 사용자는 게시물과 함께 태깅될 태그를 붙이는 행위를 번거롭게 여겨 태깅하지 않은 게시물도 올리게 된다. 본 논문에서는 입력 이미지와 유사한 이미지를 찾아 해당 이미지에 부착된 레이블을 추출하여 그 레이블이 태그로 존재하는 인스타그램의 게시물들을 찾아 게시물 속 존재하는 다른 태그들을 추천해주는 방법을 제안한다. 제안하는 방법에서는 CNN(Convolutional Neural Network) 딥러닝 기법의 모델을 통하여 이미지로 부터 레이블을 추출하여 추출된 레이블로 인스타그램을 크롤링하여 레이블 외의 태그를 정렬하여 추천해준다. 추천된 태그를 이용하여 이미지를 게시하기도 편해지고, 검색의 노출을 높일 수 있고, 검색오류가 적어 높은 정확도를 도출할 수 있음을 알 수 있다.

• 한국생활과학회지
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• 제20권1호
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• pp.143-154
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• 2011

The purpose of this study was to examine consumers' ability to distinguish advertorial and editorial about consumer information. The data were collected between June, 28 and July, 2 in 2010 through the Internet surveys. Total of 603 respondents were included in the analysis. The findings are follows as: First, consumers showed better ability to discern advertorial than ability to discern editorial. It implied that editorials could be considered as advertorial rather than advertorial could be considered as editorials. Second, it seems likely that rather than executional cues such as format and source information, the types of products/services were used as source cues among consumers. Third, consumers tend to prefer 'consumer information', 'advertorial' and 'advertisement' among 10 given advertising labels. In Conclusion, to prevent misleading potentials of advertorial and editorials, standardized advertising label should be used and notify consumers of advertising label.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2019년도 춘계학술발표대회
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• pp.273-276
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• 2019

There is a lot of information in our world, quick access to the most accurate information or finding the information we need is more difficult and complicated. The recommendation system has become important for users to quickly find the product according to user's preference. A social recommendation system using community detection based on label propagation is proposed. In this paper, we applied community detection based on label propagation and collaborative filtering in the movie recommendation system. We implement with MovieLens dataset, the users will be clustering to the community by using label propagation algorithm, Our proposed algorithm will be recommended movie with finding the most similar community to the new user according to the personal propensity of users. Mean Absolute Error (MAE) is used to shown efficient of our proposed method.

• 한국전자거래학회지
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• 제26권1호
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• pp.29-41
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• 2021

최근 패션업계에서는 급속도로 발전하는 딥러닝 방법론을 활용하려는 시도가 늘고 있다. 이에 따라 다양한 패션 관련 문제들을 다루는 연구들이 제안되었고, 우수한 성능을 달성하였다. 하지만 패션 스타일 분류 문제의 경우, 기존 연구들은 한 옷차림이 여러 스타일을 동시에 포함할 수 있다는 패션 스타일의 특성을 반영하지 못하였다. 따라서 본 연구에서는 동시에 존재하는 레이블 간의 종속성을 모델링하고, 이를 반영하여 패션 스타일의 다중 분류 문제를 해결하고자 한다. 패션 스타일 사이의 종속성을 포착하고 탐색하기 위해 GCN(graph convolution network) 기반의 다중 레이블 인식 모델을 적용하였다. 또한 전이학습을 통해 모델의 학습 속도 및 성능을 향상시켰다. 제안하는 모델은 웹 크롤링을 통해 수집한 SNS 이미지 데이터를 이용하여 검증하였으며, 비교 모델 대비 우수한 성능을 기록하였다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제15권11호
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• pp.3935-3949
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• 2021

With the rapid development of Internet and big data technology, various online social network platforms have been established, producing massive information every day. Hot topic discovery aims to dig out meaningful content that users commonly concern about from the massive information on the Internet. Most of the existing hot topic discovery methods focus on a single network data source, and can hardly grasp hot spots as a whole, nor meet the challenges of text sparsity and topic hotness evaluation in cross-network scenarios. This paper proposes a novel hot topic discovery method across social network based on an im-proved LDA model, which first integrates the text information from multiple social network platforms into a unified data set, then obtains the potential topic distribution in the text through the improved LDA model. Finally, it adopts a heat evaluation method based on the word frequency of topic label words to take the latent topic with the highest heat value as a hot topic. This paper obtains data from the online social networks and constructs a cross-network topic discovery data set. The experimental results demonstrate the superiority of the proposed method compared to baseline methods.

• 한국ITS학회 논문지
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• 제18권5호
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• pp.91-99
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• 2019

기존의 Node-to-Node기반 최적경로탐색은 기점노드에서 모든 종점노드도착조건이 성립되는 가정으로 구축되었다. 최근 적응적 경로탐색의 등장으로 Node-to-Node 경로탐색은 최적해를 도출하지 못하는 한계가 존재한다. 따라서 교통정보를 링크에서 실시간 반영하기 위한 Node-to-Link(또는 Link-to-Node; NL) 문제에 필요성이 대두되고 있다. 본 연구는 Node-to-Link의 최적 해법을 구축하는 방안으로서 링크표지와 비가산성경로비용이 존재하는 네트워크를 가정한다. 링크표지는 회전페널티가 존재하는 교차지점에서 네트워크의 원형을 유지하게 한다. 비가산성경로비용의 포함은 최적경로를 도출하기 위해서 M-유사경로의 열거를 필요로 한다. 본 연구는 진입링크기반 네트워크 변형기법에서 링크표지를 통하여 루프를 통제하며 최종링크까지 최적해를 보장하기 위한 방향삭제와 회전금지를 제안하였다. 사례연구를 통해 제안된 방법이 경험적 최적해를 도출하는 것으로 파악되었다. 향후 대규모 네트워크에서 검증작업의 필요성을 언급하며 마무리 하였다.