• 산업경영시스템학회지
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• 제39권2호
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• pp.54-63
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• 2016

As technology has developed and cost for data processing has reduced, big data market has grown bigger. Developed countries such as the United States have constantly invested in big data industry and achieved some remarkable results like improving advertisement effects and getting patents for customer service. Every company aims to achieve long-term survival and profit maximization, but it needs to establish a good strategy, considering current industrial conditions so that it can accomplish its goal in big data industry. However, since domestic big data industry is at its initial stage, local companies lack systematic method to establish competitive strategy. Therefore, this research aims to help local companies diagnose their big data capabilities through a reference model and big data capability assessment system. Big data reference model consists of five maturity levels such as Ad hoc, Repeatable, Defined, Managed and Optimizing and five key dimensions such as Organization, Resources, Infrastructure, People, and Analytics. Big data assessment system is planned based on the reference model's key factors. In the Organization area, there are 4 key diagnosis factors, big data leadership, big data strategy, analytical culture and data governance. In Resource area, there are 3 factors, data management, data integrity and data security/privacy. In Infrastructure area, there are 2 factors, big data platform and data management technology. In People area, there are 3 factors, training, big data skills and business-IT alignment. In Analytics area, there are 2 factors, data analysis and data visualization. These reference model and assessment system would be a useful guideline for local companies.

• 유통과학연구
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• 제13권7호
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• pp.53-61
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• 2015

Purpose - This research analyzes overseas expansion support systems for small- and medium-sized enterprises in Germany and Japan. Germany and Japan have developed overseas expansion support policies for such enterprises. The study then explores the implications for Korea and its local governments. Research design, data, and methodology - We did a comparative analysis of Japan and Germany and their support for overseas expansion of small and medium companies. Data were mainly collected from the Ministry of Economy, Trade and Industry (Japan) and the Germany Trade and Invest (Germany) agency through statistics and literature surveys, and analysis studies. Results - First, human resources cultivation and funding support policies, which both Germany and Japan use as part of small- and medium-sized enterprise policies, should be modified to Korean circumstances and to reflect its own small- and medium-sized enterprise support needs. Second, both the German policies that support overseas expansion of small- and medium-sized enterprises and those of Japan's include the philosophy and methods that put an emphasis on these enterprises, despite the fact that there are big differences in the overseas policies in these two countries. Third, German and Japanese governments are embracing the idea that small- and medium-sized enterprises are key to their national economies and implementing policies based on the ratio occupied by these enterprises in the domestic consumption or GDP. In other words, Germany and Japan consider small- and medium-sized enterprises as central to their nation's industry, and assess them as economic industry that should definitely exist for the continued survival of big businesses, and not just as merely supplemental to big business. Fourth, whereas Germany emphasizes support to product exhibition in its overseas expansion support policies, Japan is providing integrated support containing foreign direct investment to small- and medium-sized enterprises. Fifth, there are differences in the overseas expansion support in Germany and Japan in terms of their support to big business. Whereas Germany considers support to big business unnecessary, Japan is implementing active support policies to areas corresponding to big business. Korea will have to benchmark the policies of Germany and Japan, and decide whether or not to give full support to small- and medium-sized enterprises, while excluding areas supporting big business. Conclusions - Based on this analysis of German and Japanese overseas expansion support policies, we need to choose the policies that will engender a solid outcome and derive modified policies for the circumstances of Korea. Additionally, we can use the comparison of the overseas support policies of Japan and Germany to choose small- and medium-sized enterprise overseas expansion support policies for Korea. However, we cannot provide specific overseas support policies by industry. This point will be referenced as a limitation of this study. In future research, we expect that some researchers will take an empirical approach to exploring Korean overseas expansion support through collecting cases of overseas support policies and interviewing policy authorities.

• 대한안전경영과학회지
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• 제14권4호
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• pp.229-238
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• 2012

Within last 10 years, internet has become a daily activity, and humankind had to face the Data Deluge, a dramatic increase of digital data (Economist 2012). Due to exponential increase in amount of digital data, large scale data has become a big issue and hence the term 'big data' appeared. There is no official agreement in quantitative and detailed definition of the 'big data', but the meaning is expanding to its value and efficacy. Big data not only has the standardized personal information (internal) like customer information, but also has complex data of external, atypical, social, and real time data. Big data's technology has the concept that covers wide range technology, including 'data achievement, save/manage, analysis, and application'. To define the connected technology of 'big data', there are Big Table, Cassandra, Hadoop, MapReduce, Hbase, and NoSQL, and for the sub-techniques, Text Mining, Opinion Mining, Social Network Analysis, Cluster Analysis are gaining attention. The three features that 'bid data' needs to have is about creating large amounts of individual elements (high-resolution) to variety of high-frequency data. Big data has three defining features of volume, variety, and velocity, which is called the '3V'. There is increase in complexity as the 4th feature, and as all 4features are satisfied, it becomes more suitable to a 'big data'. In this study, we have looked at various reasons why companies need to impose 'big data', ways of application, and advanced cases of domestic and foreign applications. To correspond effectively to 'big data' revolution, paradigm shift in areas of data production, distribution, and consumption is needed, and insight of unfolding and preparing future business by considering the unpredictable market of technology, industry environment, and flow of social demand is desperately needed.

• 한국항행학회논문지
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• 제18권5호
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• pp.524-531
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• 2014

본 논문에서는 클라우드 컴퓨팅 자원을 이용하여 빅데이터의 일종인 LOD (linked open data)를 가공 및 분석하는 방법을 제안한다. LOD는 공공 데이터를 공유 및 재활용하기 위한 웹기반의 오픈 데이터이다. 특히 BA(business analytics)와 Info-graphic을 위한 시각화 (visualization) 기술을 제공하는 새로운 SaaS (software as a service) 비즈니스 영역을 InforgraaS (Info-graphic as a service)라고 정의한다. 본 연구의 목표는 시각화 및 비즈니스 전문가 없이 비전문가 또는 초보자가 사용할 수 있도록 하는 것이다. 데이터 시각화 (data visualization)는 데이터 분석 결과를 쉽게 이해할 수 있도록 시각적으로 표현하고 전달되는 과정을 말한다. 데이터 시각화의 목적은 챠트와 그래프를 통해 정보를 명확하고 효과적으로 전달하는 것이다. 공공기관의 빅데이터를 클라우드 컴퓨팅 자원과 오픈 소스인 하둡, R, 기계학습, 데이터 마이닝 등을 이용하여 다양한 처리 결과를 이해하기 쉬운 그래픽 또는 챠트로 표현하고 공유한다.

• 경영정보학연구
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• 제18권2호
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• pp.39-57
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• 2016

최근 빅데이터에 대한 관심이 높아지고 있지만 그 성공 여부의 불확실성에 대한 우려도 깊어지고 있다. 이 연구는 빅데이터 성공에 미치는 최고경영층 리더십의 영향을 이론적으로 도출하고 그 타당성을 실증 분석하였다. 국내외 선행 연구를 토대로 빅데이터 성공 단계를 빅데이터 도입, 분석, 유용한 아이디어 발견, 현업 활용, 효과 창출 5단계로 조명하였다. 그리고 5개 단계에서 작용하는 최고경영층 리더십의 영향을 (1) 빅데이터 투자에 미치는 영향, (2) 빅데이터 투자와 아이디어 유용성 사이의 상관관계에 미치는 조절효과, (3) 아이디어 유용성과 현업 활용 사이의 상관관계에 미치는 조절효과 3개 가설로 제시하였다. 빅데이터를 도입한 국내 기업 및 공공기관을 대상으로 설문조사를 수행하였으며, 통계 분석 결과 최고경영층 리더십이 빅데이터 성공 과정 전반에 걸쳐 다양한 형태로 작용하고 있음을 확인할 수 있었다. 이 연구는 빅데이터 성공에 대한 중요한 역할과 책임이 최고경영층에게 있음을 시사하고 있다.

• Journal of Information Processing Systems
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• 제20권3호
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• pp.391-398
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• 2024

Given the further promotion of economic globalization, China's financial market has also expanded. However, at present, this market faces substantial risks. The main financial and economic risks in China are in the areas of policy, credit, exchange rates, accounting, and interest rates. The current status of China's financial market is as follows: insufficient attention from upper management; insufficient innovation in the development of the financial economy; and lack of a sound financial and economic risk protection system. To further understand the current situation of China's financial market, we conducted a questionnaire survey on the financial market and reached the following conclusions. A comprehensive enterprise questionnaire from the government's perspective, the enterprise's perspective and the individual's perspective showed that the following problems exist in the financial and economic risk prevention aspects of big data and Internet of Things in China. The political system at the country's grassroots level is not comprehensive enough. The legal regulatory system is not comprehensive enough, leading to serious incidents of loan fraud. The top management of enterprises does not pay enough attention to financial risk prevention. Therefore, we constructed a financial and economic risk prevention model based on big data and Internet of Things that has effective preventive capabilities for both enterprises and individuals. The concept reflected in the model is to obtain data through Internet of Things, use big data for screening, and then pass these data to the big data analysis system at the grassroots level for analysis. The data initially screened as big data are analyzed in depth, and we obtain the original data that can be used to make decisions. Finally, we put forward the corresponding opinions, and their main contents represent the following points: the key is to build a sound national financial and economic risk prevention and assessment system, the guarantee is to strengthen the supervision of national financial risks, and the purpose is to promote the marketization of financial interest rates.

• 한국컴퓨터정보학회논문지
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• 제25권4호
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• pp.149-156
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• 2020

4차산업 혁명으로 다양한 산업분야에서 빅데이터 기술을 성공적으로 활용하여 경영성과를 얻은 사례들이 보고되고 있다. 본 논문은 의료산업에서 빅데이터를 성공적으로 활용한 혁신 사례들 살펴보고 어떤 데이터가 어떠한 목적으로 활용되고 있으며 이러한 빅데이터가 어떤 가치를 창출하는지 시사점을 도출하고자 하였다. 서론에서는 본 연구의 배경과 방향에 대해 기술하여 연구의 전체적인 구조를 파악하고자 하였다. 문헌 연구에서는 빅데이터의 정의 및 개념과 빅데이터 연구와 관련된 내용, 그리고 의료 산업에서의 빅데이터의 활용과 관련된 내용을 설명하고자 하였다. 본문에서는 질병연구를 위해 국민건강정보와 개인유전정보를 활용한 기술, 개인의 생체정보를 활용하여 개인 건강 서비스, 기업의 업무 프로세스 효율화를 위해 기업이 확보하고 있는 지식 데이터와 전자의무기록 정보를 활용한 사례, 그리고 신약개발을 위해 의료빅데이터 활용 사례 등을 서술하였다. 결론에서는 본 연구의 학문적, 비즈니스적 시사도출과 함께 연구의 성과가 국내 의료산업에 어떠한 도움을 줄 수 있는지 방향성을 제시하고자 하였다.

• 산학경영연구
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• 제17권
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• pp.27-52
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• 2004

1960년대와 1970년대에 걸친 한국경제의 성공적 도약과 이에 따른 기업의 성장은 정부의 적극적 개입에 의한 것이다. 이러한 정부주도의 경제성장이 우리나라에서 성공하게 된 이유는 박정희 정권이 효과적인 관료제를 확립하였을 뿐 아니라 수출실적 등과 같은 객관적 기구에 의하여 시장기구 못지않은 기율을 기업들에 실시한데 있다. 1960년대의 기업성장 및 기업집단 형성의 요인들로는 경제개발과정에서의 정부정책사업 및 수출 진흥정책에의 편승에 의한 특혜, 차관도입을 위시한 금융특혜, 공기업의 민영화 및 부실차관기업의 정리, 그리고 월남특수 등을 들 수 있다. 1970년대에는 8.3 사채동결조치, 중화학공업화, 중동건설특수, 종합무역상사제도의 도입 그리고 60년대 정부의 금융지배이후 계속되어오는 금융 및 자본시장에서의 경제적 지대를 기업성장 및 기업집단형성의 요인들로 들 수 있다. 그러나 이러한 특혜에 의한 성장은 기업의 비관련 다각화를 촉진시켰고, 간접금융에 의존하는 악성 기업재무구조를 유도하였고, 재벌중심의 독과점산업구조를 형성시켰다.

• 한국컴퓨터정보학회:학술대회논문집
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• 한국컴퓨터정보학회 2015년도 제51차 동계학술대회논문집 23권1호
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• pp.283-284
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• 2015

We can picture a workforce that extends beyond your employees: one that consists of any user connected to the Internet. Cloud, social, and collaboration technologies now allow organizations to tap into vast pools of resources across the world, many of whom are motivated to help. Channeling these efforts to drive business goals is a challenge, but the opportunity is enormous: it can give every business access to an immense, agile workforce that is not only better suited to solving some of the problems that organizations struggle with today but in many cases will do it for free. In this paper, we research on factors to design an organizational crowd source for Big Data.

• 인터넷정보학회논문지
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• 제17권3호
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• pp.115-128
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• 2016

Recently, converging Big Data and IoT(Internet of Things)has become mainstream, and public sector is no exception. In particular, this combinationis applicable to crime prevention in Korea. Crime prevention has evolved from CPTED (Crime Prevention through Environmental Design) to ubiquitous crime prevention;however, such a physical engineering method has the limitation, for instance, unexpected exposureby CCTV installed on the street, and doesn't have the function that automatically alarms passengers who pass through a criminal zone.To overcome that, this paper offers a crime prevention method using Big Data from public organizations along with IoT. We expect this work will help construct an intelligent crime-prevention system to protect the weak in our society.