• Journal of dental hygiene science
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• v.12 no.2
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• pp.85-91
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• 2012

The purpose of this study was to examine the factors influencing the decision to get implant treatment at dental clinic. The subjects in this study were 321 patients at dental hospitals and clinics. Andersen model in which predisposing variables, enabling variables and need variables were suggested as independent variables was used. The implant decision making was selected as a dependent variable in the model. Using logistic regression analysis, we found statistically significant effects of three independent variables: 1) class, 2) satisfaction with the facility; 3) familiarity with others received implant treatment. Those with the middle or high class background were more likely to take implant treatment. Those who were satisfied with clinic facility were more likely to take implant treatment. Those who were familiar with others received implant treatment were more likely to take implant treatment. This result implies the importance of opinion of others were received the same treatment. Hence viral marketing effort is required even in dental care field.

• Journal of Intelligence and Information Systems
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• v.17 no.4
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• pp.75-94
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• 2011

In this paper, we explore the information diffusion mechanism under social network environments by investigating the effect of message characteristics on the volume and speed of retweeting in Twitter, a popular online social media service. To this end, we select eight main keywords (i.e., '무상급식', '반값등록금', '나가수', '평창', '김연아', '박태환', '아이폰', '갤럭시') that have been popular on online social media in recent days. Each keyword represents various social aspects of Korea that recently grab people's attention such as political issues, entertainment, sports celebrities, and the latest digital products, and eventually holds distinctive message characteristics. Analyzing the frequency and velocity of retweeting for each keyword, we find that more than half of the sample messages posted on Twitter contain personal opinions for the certain keyword, but we also find that the tweets which include objective messages with hyperlink are the fastest ones when being retweeted by other followers. In overall, when being retweeted, the group of messages related to the certain keyword present distinctive diffusion patterns and speed according to message characteristics. From academic perspective, the findings in the study broaden our theoretical knowledge of information diffusion mechanism over online social media. For practitioners, the results also provide managerial implications regarding how to strategically utilize online social media for marketing communications with customers.

• Journal of Intelligence and Information Systems
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• v.18 no.2
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• pp.85-105
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• 2012

In recent years, IT advancement has brought out the new Internet communication environment such as online social network services, where people are connected in global network without temporal and spatial limitation. The popular use of online social network helps people share their experience and preference for specific products and services, thus holding large potential to significantly affect firms' business performance through Word-of-Mouth (WOM). This study examines the role of online social network in raising WOM effect on the movie industry by comparing with the similar role of Internet portal, another major online communication channel. Analyzing 109 movies and data from both Twitter and Naver movie, we found that significant WOM effect exists simultaneously in both Twitter and Naver movie. However, we also found that different figures of online viral effects exist depending on the popularity of movies. In the hit movie group, before the movie release, the WOM effect occurs only in Twitter while the WOM effect arises in both Twitter and Naver movie at the same time after the movie release. In the less-popular (or niche) movie group, the WOM effect occurs in both Twitter and Naver movie only before the movie release. Our findings not only deepen theoretical insights into different roles of the two online communication channels in provoking the WOM effect on entertainment products but also provide practitioners with incentive to utilize SNS as strategic marketing platform to enhance their brand reputations.

• Journal of the Korea Convergence Society
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• v.12 no.2
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• pp.163-171
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• 2021

The purpose of this study is to examine the current operation condition of fashion start-up companies and the characteristics of their founders in Fashion Creative Studio that is one of government programs supporting fashion start-up of rising fashion designer's brands in Korea and one of supporting facilities. For this purpose, this study surveyed 32 fashion start-up companies founders in Busan Fashion Creative Studio and analyzed the data based on the survey. The results are as follows. First of all, 82% of the founders have experience to start their business in 20s and 60% of founders with not more than 3 to 5 years of work experience related to fashion challenge to start a business. Secondly, major distribution channels of the fashion start-up companies are mainly on-line open-market consisting of 36% and SNS is up to 80% as the main promotion method. In addition, exports to China account for 71% of all exports. Lastly, 33% of businesses consider viral marketing by influencer and 50% of them make plan to export their items to East Asia. It is of research significance that this study can suggest the successful direction of establishing and operating fashion start-up companies through making good use of Fashion Creative Studio, the supporting program including facility.

• Information Systems Review
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• v.20 no.2
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• pp.63-85
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• 2018

Emerging hotspot and trendy areas are formed into alleys and blocks with the help of viral effects among social network services (SNS) users called "Golmogleo." These users search for every corner of the alleys to share and promote their own favorite places through SNS. An analysis of hot places is limited if it is only based on macroeconomic indicators such as commercial area data published by national organizations, large-scale visiting facilities, and commuter figures. Careful analyses based on consumers' actual activities are needed. This study develops a "social big data analysis methodology" using Instagram data, which is one of the most popular SNSs suitable to identify recent consumer trends. We build a spatial analysis model using Local Moran's I. Results show that our model identifies new trend zones on the basis of posting data in Instagram, which are not included in the commercial information prepared by national organizations. The proposed analysis methodology enables better identification of the latest trend areas formulated by SNS user activities. It also provides practical information for start-ups, small business owners, and alley merchants for marketing purposes. This analytical methodology can be applied to future studies on social big data analysis.