• Journal of Korea Society of Digital Industry and Information Management
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• v.6 no.1
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• pp.197-209
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• 2010

Supply Chain Management have been introduced and used as strategic weapon for many companies. Large investments in the SCM was made, but many companies are not fully getting the performance from the systems. The purpose of this study is to find the determinants of SCM difussion and performance in the perspective of Innovation and Information technology Acceptance. In developing the research model, The model consists of eight independent variables(Management support, Decision Making concentration, IS strategy, training education, relative advantage, technological compatibility, task compatibility, SCM cost), two moderator variables(interorganizational and intraorganizational diffusion), three dependant variables(efficiency, effectiveness, strategic advantage).

• Proceedings of the Korea Concrete Institute Conference
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• 2006.11a
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• pp.573-576
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• 2006

To predict service life of concrete structures exposed to chloride attack, surface chloride concentration, diffusion coefficient of chloride ion, and chloride corrosion threshold value in concrete, are used as important factors. of these, as the diffusion coefficient of chloride ion for concrete is strongly influenced by concrete quality and environmental conditions of structures and may significantly change the service life of structures, it is considered as the most important factor for service life prediction. The qualitative factors affecting the penetration and diffusion of chloride ion into concrete are water-binder(W/B) ratio, age, cement type and constituents, chloride ion concentration of given environment, wet and dry conditions, etc. In this paper the influence of cement type on the diffusion characteristics of chloride ion in concrete was investigated through the chloride ion diffusion test. For this purpose, the diffusion characteristics in concrete with cement type such as ordinary portland cement(OPC), binary blended cement(BBC), and ternary blended cement(TBC) were estimated for the concrete with W/B ratios of 32% and 38%, respectively. It was observed from the test that the difussion characteristics of BBC containing OPC and ground granulated blast-furnace slag was found to be most excellent of the cement type used in this study.

• Journal of Intelligence and Information Systems
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• v.21 no.3
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• pp.19-36
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• 2015

Social media is an emerging issue in content services and in current business environment. YouTube is the most representative social media service in the world. YouTube is different from other conventional content services in its open user participation and contents creation methods. To promote a content in YouTube, it is important to understand the diffusion phenomena of contents and the network structural characteristics. Most previous studies analyzed impact factors of contents diffusion from the view point of general behavioral factors. Currently some researchers use network structure factors. However, these two approaches have been used separately. However this study tries to analyze the general impact factors on the view count and content based network structures all together. In addition, when building a content based network, this study forms the network structure by analyzing user comments on 22,370 contents of YouTube not based on the individual user based network. From this study, we re-proved statistically the causal relations between view count and not only general factors but also network factors. Moreover by analyzing this integrated research model, we found that these factors affect the view count of YouTube according to the following order; Uploader Followers, Video Age, Betweenness Centrality, Comments, Closeness Centrality, Clustering Coefficient and Rating. However Degree Centrality and Eigenvector Centrality affect the view count negatively. From this research some strategic points for the utilizing of contents diffusion are as followings. First, it is needed to manage general factors such as the number of uploader followers or subscribers, the video age, the number of comments, average rating points, and etc. The impact of average rating points is not so much important as we thought before. However, it is needed to increase the number of uploader followers strategically and sustain the contents in the service as long as possible. Second, we need to pay attention to the impacts of betweenness centrality and closeness centrality among other network factors. Users seems to search the related subject or similar contents after watching a content. It is needed to shorten the distance between other popular contents in the service. Namely, this study showed that it is beneficial for increasing view counts by decreasing the number of search attempts and increasing similarity with many other contents. This is consistent with the result of the clustering coefficient impact analysis. Third, it is important to notice the negative impact of degree centrality and eigenvector centrality on the view count. If the number of connections with other contents is too much increased it means there are many similar contents and eventually it might distribute the view counts. Moreover, too high eigenvector centrality means that there are connections with popular contents around the content, and it might lose the view count because of the impact of the popular contents. It would be better to avoid connections with too powerful popular contents. From this study we analyzed the phenomenon and verified diffusion factors of Youtube contents by using an integrated model consisting of general factors and network structure factors. From the viewpoints of social contribution, this study might provide useful information to music or movie industry or other contents vendors for their effective contents services. This research provides basic schemes that can be applied strategically in online contents marketing. One of the limitations of this study is that this study formed a contents based network for the network structure analysis. It might be an indirect method to see the content network structure. We can use more various methods to establish direct content network. Further researches include more detailed researches like an analysis according to the types of contents or domains or characteristics of the contents or users, and etc.