• Water for future
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• v.48 no.11
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• pp.42-49
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• 2015

• Venture DIGEST
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• s.95
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• pp.12-17
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• 2006

세계화와 더불어 규제의 강화, 경쟁의 심화 등 조직을 둘러싼 환경이 급변함에 따라 체계적인 지식관리를 통한 조직의 경쟁력 강화와 혁신을 추구하는 사례가 늘어나고 있다. 지식 자원의 가치를 극대화하기 위한 지식관리시스템(KMS)이 기업 경영의 핵심요소로 자리 잡아가고 있는 것이다.

• Agrochemical news magazine
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• v.24 no.8 s.191
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• pp.14-17
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• 2003

• Proceedings of the Korea Technology Innovation Society Conference
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• 2016.10a
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• pp.619-627
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• 2016

• Proceedings of the Military Operations Research Society of Korea Conference
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• 2007.03a
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• pp.103-117
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• 2007

• Journal of Intelligence and Information Systems
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• v.26 no.3
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• pp.127-147
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• 2020

The world is suffering from numerous human and economic losses due to the novel coronavirus infection (COVID-19). The Korean government established a strategy to overcome the national infectious disease crisis through research and development. It is difficult to find distinctive features and changes in a specific R&D field when using the existing technical classification or science and technology standard classification. Recently, a few studies have been conducted to establish a classification system to provide information about the investment research areas of infectious diseases in Korea through a comparative analysis of Korea government-funded research projects. However, these studies did not provide the necessary information for establishing cooperative research strategies among countries in the infectious diseases, which is required as an execution plan to achieve the goals of national health security and fostering new growth industries. Therefore, it is inevitable to study information services based on the classification system and classification model for establishing a national collaborative R&D strategy. Seven classification - Diagnosis_biomarker, Drug_discovery, Epidemiology, Evaluation_validation, Mechanism_signaling pathway, Prediction, and Vaccine_therapeutic antibody - systems were derived through reviewing infectious diseases-related national-funded research projects of South Korea. A classification system model was trained by combining Scopus data with a bidirectional RNN model. The classification performance of the final model secured robustness with an accuracy of over 90%. In order to conduct the empirical study, an infectious disease classification system was applied to the coronavirus-related research and development projects of major countries such as the STAR Metrics (National Institutes of Health) and NSF (National Science Foundation) of the United States(US), the CORDIS (Community Research & Development Information Service)of the European Union(EU), and the KAKEN (Database of Grants-in-Aid for Scientific Research) of Japan. It can be seen that the research and development trends of infectious diseases (coronavirus) in major countries are mostly concentrated in the prediction that deals with predicting success for clinical trials at the new drug development stage or predicting toxicity that causes side effects. The intriguing result is that for all of these nations, the portion of national investment in the vaccine_therapeutic antibody, which is recognized as an area of research and development aimed at the development of vaccines and treatments, was also very small (5.1%). It indirectly explained the reason of the poor development of vaccines and treatments. Based on the result of examining the investment status of coronavirus-related research projects through comparative analysis by country, it was found that the US and Japan are relatively evenly investing in all infectious diseases-related research areas, while Europe has relatively large investments in specific research areas such as diagnosis_biomarker. Moreover, the information on major coronavirus-related research organizations in major countries was provided by the classification system, thereby allowing establishing an international collaborative R&D projects.

• Spatial Information Research
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• v.23 no.5
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• pp.21-30
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• 2015

Korean government has promoted the projects of National Geographic Information Systems since 1995 and the utilization level of Korean National Spatial Data Infrastructure based on them has also developed. However, due to the limit to domestic market size and the legal regulation on prohibition of large sized companies' expansion into domestic spatial information markets, Korean spatial information markets are tied up in term of industrial competitiveness. To overcome those problems and evade the domestic red oceans, it is necessary to find new one in overseas' blue ocean markets. It is estimated that overseas spatial information market will be grown to 125 billion-dollar size and the annual growth rate of it will be reached to 10.5% until 2015. Thus, Asian spatial information market has a huge growth potential and it is newly rising blue oceans for Korea. Advanced countries such as Finland, Germany, Sweden, and Japan have already expanded their market size into the newly industrializing countries. To step with advanced countries, it is time to set up the new globalization strategy of Korean spatial information for expansion into newly industrializing markets. The purpose of this study is to analyze the SWOT of domestic spatial information, investigate the status on spatial information of Asian developing countries, and suggest the globalization strategy of Korean spatial information for expansion into them. The globalization strategy can be labelled as K-FBI composed of 4 domains such as Knowledge sharing platform, Frontier, Back to the basic, and Internalization. In near future, the establishment and performance of road map based on the strategy will be the milestone for Korean spatial information companies' advance into Asian developing countries.

• Journal of the Korea Convergence Society
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• v.12 no.8
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• pp.257-265
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• 2021

Although researches on digital transformation and competitive strategies are active, but research or alternatives considering fitness between them are still insufficient. Therefore, this study aims to identify the relationship between the types of digital transformation project and the innovation of competitive strategies, and to suggest strategic implications and alternatives for how to utilize digital transformation when establishing a competitive strategy. To this end, this study first derived 14 types of digital transformation in 4 areas through literature research. Then, the relevance of digital transformation and competitive strategy identified through previous studies and case analysis was identified, an effective link between competition strategy and digital transformation, and optimization of fitness between competition strategy and internal resources were presented. This study contributed in that it attempted to advance research on competitive strategies in an academic perspective by approaching them from the perspective of strategic fitness about digital transformation. In addition, in the industrial aspect, it contributed to the fact that it supported the systematic implementation of the competitive strategic response of companies that had to deal with the situation where they wanted to promote digital transformation wisely from the viewpoint of fitness.

• Information Systems Review
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• v.9 no.3
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• pp.45-65
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• 2007

As digital economy era and knowledge society advent, division of the industry has been indistinctive and complex. This change of business environment has leaded todifficulty in operations of firms consisted of continuous decision making. To develop effective SDSS needs systematic strategic decision making process, efficient problem solving techniques, information of good quality, efficiently information system, and analysis ability of problem solver. This research develop SDSS framework combined strategic decision making process with various problem solving techniques for designing SDSS. Finally, this paper developed the technique recommendation system by selected the criterions of technique assortment.

• Proceedings of the Korean Information Science Society Conference
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• 2008.06c
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• pp.132-137
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• 2008

최근 들어, 기업의 내재 가치를 평가하여 투자에 활용하는 이른바 가치투자에 대한 많은 분석과 전략들이 나오고 있다. 그러나 현존하는 대부분의 투자 지원 툴들은, 단기적으로 등락을 반복하는 주가에 매매 조건을 제시하여 차액을 얻는 방식인 기술적 분석 툴로서 기업의 내재 가치를 평가하여 투자를 지원하기 에는 제한이 있다. 때문에 가치 투자자들은 기업의 가치를 체계적이고 객관적으로 판단하기 보다는, 몇몇의 공시된 자료들을 보고 개인의 판단에 따라 평가하는 경우가 대부분이다. 따라서 감정과 선입견을 배제한 기존의 기술적 분석 툴과 같이 기업의 가치를 정량적으로 추정하여 다양한 전략개발을 할 수 있는 툴이 필요한 실정이다. 본 논문에서는 기업의 가치를 정량화하여 가치투자 전략을 개발할 수 있는 가치투자 시스템(이하 KPU-VISS)의 설계 및 구현 내용을 기술한다. 즉, 본 시스템은 주식가격을 포함한 기업의 다양한 정보와 경기 지표 등을 이용하여 기업의 가치 모델 개발을 지원하고, 이 모델에 근거하여 저평가된 종목을 검색하는 전략 개발을 지원한다. 또한, 개발된 전략을 과거의 특정 시점에 반영시킨 투자 시뮬레이션을 통하여, 전략의 실효성을 검증하는 기능도 지원한다. 본 논문에서 제안한 가치투자 지원시스템은 최초로 가치투자전략의 개발과 검증을 지원하는 시스템으로, 향후 가치투자 시스템 개발을 위한 선도적인 방향을 제시할 것으로 예상한다.