• Journal of Distribution Science
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• v.13 no.7
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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.

• Journal of the Korea Safety Management & Science
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• v.14 no.4
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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.

• Journal of Advanced Navigation Technology
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• v.18 no.5
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• pp.524-531
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• 2014

In this paper, we have proposed the processing and analyzing the linked open data (LOD), a kind of big-data, using resources of cloud computing. The LOD is web-based open data in order to share and recycle of public data. Specially, we defined the InfograaS (Info-graphic as a service), new business area of SaaS (software as a service), to support visualization technique for BA (business analytics) and Info-graphic. The goal of this study is easily to use it by the non-specialist and beginner without experts of visualization and business analysis. Data visualization is the process to represent visually and understand the data analysis easily. The purpose of data visualization is to deliver information clearly and effectively by chart and figure. The big data of public data are shared and presented in the charts and the graphics understood easily by various processing results using Hadoop, R, machine learning, and data mining of open source and resources of cloud computing.

• Information Systems Review
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• v.18 no.2
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• pp.39-57
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• 2016

Previous studies on the success factors of big data implementation have called for future research and further examination of the top management leadership's impact. This research proposes and empirically tests three hypotheses, including how top management leadership can directly affect big data investment, how it can mediate the causal relationship between big data investment and idea usefulness, and how it can mediate the relationship between idea usefulness and business utilization. Based on the data collected from 108 big data users in Korean companies, we determined that all three hypotheses are statistically significant. By shedding light on top management leadership and its characteristics, we can provide better suggestions on what needs to be done to ensure the success of big data.

• Journal of the Korea Society of Computer and Information
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• v.25 no.4
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• pp.149-156
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• 2020

In the Fourth Industrial Revolution, successful cases using big data in various industries are reported. This paper examines cases that successfully use big data in the medical industry to develop the service and draws implications in value that big data create. The related work introduces big data technology in the medical field and cases of eight innovative service in the big data service are explained. In the introduction, the overall structure of the study is mentioned by describing the background and direction of this study. In the literature study, we explain the definition and concept of big data, and the use of big data in the medical industry. Next, this study describes the several cases, such as technologies using national health information and personal genetic information for the study of diseases, personal health services using personal biometric information, use of medical data for efficiency of business processes, and medical big data for the development of new medicines. In the conclusion, we intend to provide direction for the academic and business implications of this study, as well as how the results of the study can help the domestic medical industry.

• Korean Business Review
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• v.17
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• pp.27-52
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• 2004

The miraculous growth of Korean economy and its business corporations during 1960' s and 1970's are mainly due to the government leadership and its market intervention. We can find the reasons why the government initiated economic growth plan was so successful in Korea in its efficient bureaucratic government system and fair discipline to the corporations based on its contribution to the economy. During 1960's, the primary factors for the growth of business entities and the formation of business groups were the financial special favor, the preferential treatment in the new industry entrance and the merge & acquisition, lavish export incentives from the government, and the export explosion to Vietnam. During 1970's, the substantial deduction of corporations' private debt, enormous support in heavy industry investment, special benefits to general trading companies by the government, and the construction export to the Middle-East were the main causes of the business growth and the business groups formation. Also, the economic rent for the big companies had still been effective since 1960's. However, the preferential benefit to the big companies made them to diversify into the unrelated business ares and to be in very vulnerable financial position. The governmental support brought about the monopoly as well.

• Proceedings of the Korean Society of Computer Information Conference
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• 2015.01a
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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.

• Journal of Internet Computing and Services
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• v.17 no.3
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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.

• Asia pacific journal of information systems
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• v.34 no.1
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• pp.226-247
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• 2024

Most studies on recommender systems to evaluate recommendation performances focus on offline evaluation methods utilizing past customer transaction records. However, evaluating recommendation performance through real-world stimulation becomes challenging. Moreover, such methods cannot evaluate the duration of the recommendation effect. This study measures the personalized recommendation (stimulus) effect when the product recommendation to customers leads to actual purchases and evaluates the duration of the stimulus personalized recommendation effect leading to purchases. The results revealed a 4.58% improvement in recommendation performance in the online environment compared with that in the offline environment. Furthermore, there is little difference in recommendation performance in offline experiments by period, whereas the recommendation performance declines with time in online experiments.

• Journal of Convergence Society for SMB
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• v.5 no.4
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• pp.11-16
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• 2015

In recent years, small businesses are increasing attempt to create better value through a combination of benefits with small and flexible organization of big data. However, until now small businesses are lacking to secure sustainable competitiveness to match the ICT paradigm alteration to focus on improving productivity. This paper propose an efficient small businesses process model which can effectively take advantage of a low cost, identify customer needs, taget marketing, customer management for new product. Proposed model can retain the necessary competitiveness in generating new business for collaboration between companies inside and companies using a massive big data. Also, proposed model can be utilized the overall business activities such as the target customer selection, pricing strategies, public relations and promotional activities and enhanced new product development capabilities using big data.