• The Journal of the Korea Contents Association
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• v.20 no.1
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• pp.31-44
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• 2020

The purpose of this study is to investigate the relationship among SNS users' interpersonal trust, brand image and purchase intention. A total of 335 questionnaires were collected during 6 days by Embrain online research company. Collected data were analyzed by SPSSWIN and AMOS program and frequency analysis, confirmatory factor analysis, validity test, correlation analysis and structural equation model analysis were performed. The results of verifying the relationship among variables are as follows. First, SNS users' interpersonal trust in influencers had positively influenced by brand image. Second, brand image sold by influencers had positively influenced by purchase intention. Third, SNS users' interpersonal trust in influencers had a significant effect on purchase intention.

• Journal of Korea Society of Industrial Information Systems
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• v.20 no.2
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• pp.85-96
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• 2015

Despite the growth of body-related industry has generated considerable interest in this topic among both academics and practitioners, there has been lack of studies that explore body esteem toward online fashion products leads to purchase intentions, which self-monitoring moderates the relationship between body esteem toward online fashion products and purchase intentions. To fill this gap, this study aim to propose a research model where body esteem influences on the purchase intentions, with self-monitoring as a moderator. In order to test hypotheses, response from 172 consumers were achieved, and the proposed model was estimated by using hierarchical moderated regression analysis. The empirical results showed that body esteem negatively related to purchase intentions toward online fashion products. Additionally, this study indicated that the moderating effects of self-monitoring exist between body esteem and purchase intentions toward online fashion products, thereby implying the importance of contingent role of self-monitoring in managing online channels.

• Journal of Internet of Things and Convergence
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• v.5 no.2
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• pp.7-13
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• 2019

As online shopping is activated by the development of the Internet, consumers' purchase form is changing from the traditional face-to-face purchase method to online purchase method. Many sellers have flowed into shopping malls, and competition among sellers is very intense. Therefore, sellers in shopping malls need to establish rational marketing strategies by analyzing consumer purchase patterns and product sales trends. In this paper, we analyzed the purchase price of consumers by analyzing the product price, rating, and sales quantity of competitors who sell the same product in open shopping malls by time zone. In addition, the collected information was visualized in a chart so that the company's and competitors' sales trends could be easily compared. Using the above system, it is possible to predict the sales volume through the analyzed purchasing pattern and to select the reasonable price of the product by grasping the sales trend.

• Management & Information Systems Review
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• v.30 no.3
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• pp.153-167
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• 2011

This study conducts to examine the effect of purchase intention on social shopping by connection density and centrality which is a structural characteristic of social network. Furthermore, this study suggests and analyses the difference of social shopping purchase intention between online community which focuses on a group and SNS(social network service) which focuses on an individual. To examine these reason, this study proposes hypotheses that reflects structural characteristic then analyses them. The result of analysis shows that the purchase intention on social shopping seems to be high when the density of connection is high and the purchase intention seems to be high when the centrality is high as well. Moreover, there is difference in the purchase intention on social shopping between online community and SNS and it is found that both cases where the connection density is high in the online community and the connection centrality is high in SNS have significant impact on the purchase intention. Based on these results, this study provides an implication on the importance on network structure in social network and social shopping and to increase the purchase intention of social shopping, this study suggests the implication on the importance and direction which understands the structure of social network type.

• The Journal of the Korea Contents Association
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• v.13 no.5
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• pp.436-442
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• 2013

Recently, online environment is actively used so it will be needed to identify the factors influencing satisfaction for continuous success. In this paper, we explain the users' satisfaction of online purchasing IT and verify them through the empirical analysis. We select basic variables from TAM (Technology Acceptance Model) and add specific variables from former research about user's trait. We chose satisfaction, perceived easiness, perceived usefulness, regret and maximizing tendency. Data collected from 150 user who had prior experiences with online purchasing IT were empirically tested against the research model using partial least square (PLS). The results show that perceived easiness, perceived usefulness and regret are significantly related to satisfaction and maximizing tendency has positive impact on perceived easiness, perceived usefulness and regret significantly.

• Proceedings of the Korean DIstribution Association Conference
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• 2004.02a
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• pp.63-85
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• 2004

• Proceedings of the Korea Information Processing Society Conference
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• 2009.04a
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• pp.387-390
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• 2009

인터넷의 생활화를 통해 우리 생활 패턴이 크게 변화하였다. 특히 상품 구매의 경우 온라인 시장의 성장과 상품 정보의 범람으로 소비자들의 구매 의사결정은 더욱 어려워졌다. 따라서 효율적인 상품 구매 의사결정을 위해서는 소셜 네트워크 분석(Social Network Analysis)을 기반으로 한 더 가치있는 정보를 선별하여 제공해 줄 수 있는 서비스가 필요하다. 따라서 본 논문에서는 온라인 소셜 네트워크 요소 분석을 통해 상품 후기에 대한 개인화된 가치 측정값 정보를 제공함으로써 소비자의 보다 효율적인 상품 구매가 가능하도록 도와주는 '가치 측정 알고리즘'을 제안한다.

• 한국벤처창업학회:학술대회논문집
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• 2023.04a
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• pp.11-13
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• 2023

대기업 등을 비롯한 중소기업들은 여러 광고 매체를 이용해 자사의 상품이나 브랜드 이미지를 홍보하는 것 이외에 유튜브와 같은 온라인 동영상 서비스 플랫폼에서 제품이나 서비스를 동영상으로 제작하여 다채로운 방법으로 가공, 소개하며 마케팅 효과를 극대화하고 있다. 이는 기업의 제품 및 서비스의 동영상 마케팅이 소비자들에게 어떤 영향을 미치고 직접적인 매출과 상관관계가 있는지를 이미 파악하고 접근하고 있다는 증거이다. 상대적으로 소상공인들은 동영상의 필요성에 대한 인식이 부족한 상태이다. 이에 유튜브와 같은 온라인 동영상 서비스 플랫폼에서 효과적으로 제품 및 서비스에 대해 관심과 흥미를 불러 일으키기 위해 동영상 마케팅을 시행하고자 할 때 동영상은 어떤 요소들이 충족되어야 하는지를 연구하려고 한다. 그리고 정확하게 동영상의 어떤 요소들이 소비자들의 구매 욕구를 상승시키는지와 같은 소비자들의 구매 행동 부분에 밀접한 영향을 미치는 동영상의 요소들에 대해 연구하고자 한다. 소비자들이 느끼는 구매 의지에 영향을 미치는 동영상의 요소들을 역설적으로 소상공인들에게 영상의 필요성을 인식시키기 위함이다.

• Journal of Global Scholars of Marketing Science
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• v.16 no.3
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• pp.169-189
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• 2006

The product categories that can be sold on-line are expanding. It is interesting to see which product categories have more sales possibilities on internet. Small-sized firms' products have low distribution coverage, low brand recognition, bigger dispersion in the perception on the values which consist of quality vs. price, and higher possibilities of perceived purchase risks. Since on-line shopping is supposed to provide opportunities to small-sized firms that have low distribution and brand power, it is quite necessary to evaluate the fitness of on-line sales for small-sized firms' product categories. There are virtually no research studies on the on-line sales for small-sized firms' product categories. In this study, based on the integration of SEC, FCB, and related concepts, we develop new theoretical framework and test the fitness of on-line sales for small-sized firms' product categories by conducting empirical analysis. The empirical results on 17 product categories show that SEC, FCB, purchase risks, brand factors are somewhat related. Unlike previous studies, since the fitness of SEC and on-line sales are not clearly shown, we need to consider those problems within inter-related multiple frameworks. That is, it is necessary to evaluate the fitness of on-line sales after defining the product categories within the integrated multiple frameworks rather than within the single framework.

• CRM연구
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• v.4 no.2
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• pp.19-29
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• 2011

There is a large difference between purchasing patterns in an online shopping mall and in an offline market. This difference may be caused mainly by the difference in accessibility of online and offline markets. It means that an interval between the initial purchasing decision and its realization appears to be relatively short in an online shopping mall, because a customer can make an order immediately. Because of the short interval between a purchasing decision and its realization, an online shopping mall transaction usually contains fewer items than that of an offline market. In an offline market, customers usually keep some items in mind and buy them all at once a few days after deciding to buy them, instead of buying each item individually and immediately. On the contrary, more than 70% of online shopping mall transactions contain only one item. This statistic implies that traditional data mining techniques cannot be directly applied to online market analysis, because hardly any association rules can survive with an acceptable level of Support because of too many Null Transactions. Most market basket analyses on online shopping mall transactions, therefore, have been performed by expanding the co-occurrence criteria of traditional association rule mining. While the traditional co-occurrence criteria defines items purchased in one transaction as concurrently purchased items, the expanded co-occurrence criteria regards items purchased by a customer during some predefined period (e.g., a day) as concurrently purchased items. In studies using expanded co-occurrence criteria, however, the criteria has been defined arbitrarily by researchers without any theoretical grounds or agreement. The lack of clear grounds of adopting a certain co-occurrence criteria degrades the reliability of the analytical results. Moreover, it is hard to derive new meaningful findings by combining the outcomes of previous individual studies. In this paper, we attempt to compare expanded co-occurrence criteria and propose a guideline for selecting an appropriate one. First of all, we compare the accuracy of association rules discovered according to various co-occurrence criteria. By doing this experiment we expect that we can provide a guideline for selecting appropriate co-occurrence criteria that corresponds to the purpose of the analysis. Additionally, we will perform similar experiments with several groups of customers that are segmented by each customer's average duration between orders. By this experiment, we attempt to discover the relationship between the optimal co-occurrence criteria and the customer's average duration between orders. Finally, by a series of experiments, we expect that we can provide basic guidelines for developing customized recommendation systems.