• Knowledge Management Research
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• v.1 no.1
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• pp.19-46
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• 2000

Today, knowledge is considered the most strategically important resource. As research in knowledge management advances, it ought to review and categorize the already published literatures on knowledge management in the area of business strategy, accounting/finance, human resource management and management information technology. To identify the knowledge management research trend, we analyze 168 articles published in prominent academic journal during last two decades. This paper develops three stages model for knowledge management research: observation, initiation and evolution stage. Also, we classify the given researches according to the three criteria of contents, related academic area and applied research method.

• Journal of Information Technology Services
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• v.7 no.1
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• pp.131-149
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• 2008

Bandwidth Trading(BT) represents a potential market with over 1 trillion USD across the world and high growth potential. BT is also likely to accelerate globalization of the telecommunications industry and massive restructuring driven by unbundling rush. However, systematic researches on BT remain at an infant stage. This study starts with structure analysis of the Internet industry, and discusses significance of Internet interconnection with respect to BT Issues. We also describe the bandwidth commoditization trends and review technical requirements for effective Internet interconnection with BT capability. Taking a step further, this study explores the possibility of improving efficiency of network providers and increasing user convenience by developing an architectural prototype of Hub-&-Spoke interconnection model required to facilitate BT. The BT market provides an Innovative base to ease rigidity of two-party contract and Increase service efficiency. However, as fair, efficient operation by third party is required, this research finally proposes an exchanging hub named NIBX(New Internet Business eXchange).

• Journal of Internet Computing and Services
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• v.23 no.2
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• pp.97-105
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• 2022

Web services show a rapid evolution and integration to meet the increased users' requirements. Thus, web services undergo updates and may have performance degradation due to undetected faults in the updated versions. Due to these faults, many performances and regression anomalies in web services may occur in real-world scenarios. This paper proposed applying the deep learning model and innovative explainable framework to detect performance and regression anomalies in web services. This study indicated that upper bound and lower bound values in performance metrics provide us with the simple means to detect the performance and regression anomalies in updated versions of web services. The explainable deep learning method enabled us to decide the precise use of deep learning to detect performance and anomalies in web services. The evaluation results of the proposed approach showed us the detection of unusual behavior of web service. The proposed approach is efficient and straightforward in detecting regression anomalies in web services compared with the existing approaches.

• Journal of Intelligence and Information Systems
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• v.24 no.4
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• pp.137-154
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• 2018

Animal infectious diseases, such as avian influenza and foot and mouth disease, occur almost every year and cause huge economic and social damage to the country. In order to prevent this, the anti-quarantine authorities have tried various human and material endeavors, but the infectious diseases have continued to occur. Avian influenza is known to be developed in 1878 and it rose as a national issue due to its high lethality. Food and mouth disease is considered as most critical animal infectious disease internationally. In a nation where this disease has not been spread, food and mouth disease is recognized as economic disease or political disease because it restricts international trade by making it complex to import processed and non-processed live stock, and also quarantine is costly. In a society where whole nation is connected by zone of life, there is no way to prevent the spread of infectious disease fully. Hence, there is a need to be aware of occurrence of the disease and to take action before it is distributed. Epidemiological investigation on definite diagnosis target is implemented and measures are taken to prevent the spread of disease according to the investigation results, simultaneously with the confirmation of both human infectious disease and animal infectious disease. The foundation of epidemiological investigation is figuring out to where one has been, and whom he or she has met. In a data perspective, this can be defined as an action taken to predict the cause of disease outbreak, outbreak location, and future infection, by collecting and analyzing geographic data and relation data. Recently, an attempt has been made to develop a prediction model of infectious disease by using Big Data and deep learning technology, but there is no active research on model building studies and case reports. KT and the Ministry of Science and ICT have been carrying out big data projects since 2014 as part of national R &D projects to analyze and predict the route of livestock related vehicles. To prevent animal infectious diseases, the researchers first developed a prediction model based on a regression analysis using vehicle movement data. After that, more accurate prediction model was constructed using machine learning algorithms such as Logistic Regression, Lasso, Support Vector Machine and Random Forest. In particular, the prediction model for 2017 added the risk of diffusion to the facilities, and the performance of the model was improved by considering the hyper-parameters of the modeling in various ways. Confusion Matrix and ROC Curve show that the model constructed in 2017 is superior to the machine learning model. The difference between the2016 model and the 2017 model is that visiting information on facilities such as feed factory and slaughter house, and information on bird livestock, which was limited to chicken and duck but now expanded to goose and quail, has been used for analysis in the later model. In addition, an explanation of the results was added to help the authorities in making decisions and to establish a basis for persuading stakeholders in 2017. This study reports an animal infectious disease prevention system which is constructed on the basis of hazardous vehicle movement, farm and environment Big Data. The significance of this study is that it describes the evolution process of the prediction model using Big Data which is used in the field and the model is expected to be more complete if the form of viruses is put into consideration. This will contribute to data utilization and analysis model development in related field. In addition, we expect that the system constructed in this study will provide more preventive and effective prevention.

• The Journal of Society for e-Business Studies
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• v.20 no.4
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• pp.127-150
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• 2015

Since 9/11 attack, internet has become a major space for terrorist activities and also emerged as the most important spot of lone wolf terrorists for acquiring tools and radicalization. The accident of student Kim's defection to IS (Islamic state) in January 2015 told us that Korea is not any more "terrorism clearance area" and leaded us to look closely into the possibility of lone wolf terrorist. In this paper, I developed a "lone wolf cyber evolution model" using various materials collected by preceding papers and interviewing investigators and terrorism experts in Korea. I analyze Kim's radicalization process using this model. And I picked and closely looked over some facilitating factors of lone wolf such as multi-cultural socialization, increase of international migrants, expansion alienation hierarchy and ideological conflicts deepening and predicted the possibility of lone wolf. Finally, this paper presents some effective policy measurements against lone wolf terrorism in Korea.

• Journal of Technology Innovation
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• v.13 no.2
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• pp.23-43
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• 2005

Industrial clusters are geographical concentrations of interconnected companies, specialised suppliers, service providers, firms in related industries, and associated institutions (for example, universities, standard agencies, and trade associations) that combine to create new products and/or services in specific lines of business. At present, the concept of industrial cluster becomes very popular worldwide, policy makers at national, regional and local levels and business people in both forerunner and latecomer countries are keen to implement the cluster concept as an economic development model. Though understanding of clusters and related promoting policies varies from one place to another, the underlying benefits of clusters from collective learning and knowledge spillovers between participating actors strongly attract the attention of these people. In Thailand, a latecomer country in terms of technological catching up, the cluster concept has been used as a means to rectify weakness and fragmentation of its innovation systems. The present Thai government aspires to apply the concept to promote both high-tech manufacturing clusters, services clusters and community-based clusters at the grass-root level. This paper analyses three very different clusters in terms of technological sophistication and business objectives, i.e., hard disk drive, software and chili paste. It portrays their significant actors, the extent of interaction among them and the evolution of the clusters. Though are very dissimilar, common characteristics attributed to qualified success are found. Main driving forces of the three clusters are cluster intermediaries. Forms of these organizations are different from a government research and technology organization (RTO), an industrial association, to a self-organised community-based organization. However, they perform similar functions of stimulating information and knowledge sharing, and building trust among participating firms/individuals in the clusters. Literature in the cluster studies argues that government policies need to be cluster specific. In this case, the best way to design and implement cluster-specific policies is through working closely with intermediaries and strengthening their institutional especially in linking member firms/individuals to other actors in clusters such as universities, government R&D institutes, and financial institutions.

• Journal of Korean Society for Quality Management
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• v.45 no.4
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• pp.629-648
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• 2017

Purpose: The world faces a great turning point fundamentally rebuilding the future, and human lives, by embracing the 4th industrial revolution era. This paper aims to seek new and various business models in the 4th industrial revolution era, and to examine the evolution of quality management in the changing of the industrial ecosystem. Methods: This paper examines the various strategies of approaching the 4th industrial revolution in Germany, the USA, Japan, China, and Korea. This paper also draws detailed items by classifying the six major items of Malcolm Baldridge into large, medium, and small scale classifications, researches items from the technical perspective by applied fields, and the four major factor perspectives of quality management, as well as analyzes the relevant items in a multidimensional method. After a questionnaire survey targeting 200 quality experts was conducted, the important quality management factors were selected by applying the Analytic Hierarchy Process (AHP) method. Results: The importance of the general criteria was analyzed in the order of customers, MAKM (measurement, analysis, and knowledge management), workforce, strategy, operations, and leadership. As for the importance analysis results of the secondary subcriteria, the following items are highly analyzed: senior leadership, searching business model's innovation opportunity, customer satisfaction improvement, big data utilization, systematic management of workforce, and, planning and design quality. Conclusion: In the era of the Internet of everything, when complexity increases, this study presented a quality management direction suitable for new business methods challenging existing orders by drawing on quality management priorities.

• The Korean Journal of Applied Statistics
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• v.28 no.3
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• pp.393-406
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• 2015

We examine how to model mortality risk using the adaptation of the mean-reverting processes for the two factor model proposed by Cairns et al. (2006b). Mortality improvements have been recently observed in some countries such as United Kingdom; therefore, we assume long-run mortality converges towards a trend at some unknown time and the mean-reverting processes could therefore be an appropriate stochastic model. We estimate the parameters of the two-factor model incorporated with mean-reverting processes by a Metropolis-Hastings algorithm to fit United Kingdom mortality data from 1991 to 2015. We forecast the evolution of the mortality from 2014 to 2040 based on the estimation results in order to evaluate the issue price of a longevity bond of 25 years maturity. As an application, we propose a method to quantify the speed of mortality improvement by the average mean reverting times of the processes.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.12
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• pp.268-277
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• 2020

This study emphasizes that the survival strategy of universities should be a co-evolution strategy based on ecological thinking. Therefore, the purpose of the research is to present a theoretical framework for dividing the university innovation ecosystem into four stages and building a co-evolution strategy for each step, as universities play a prominent role in regional innovation ecosystems. Thus, our research method focused on literature research, and the theoretical framework for the university innovation ecosystem used Moore's Enterprise Ecosystem Model (1996). The university's ecological innovation strategy is divided into four stages of development, and a step-by-step co-evolution strategy is presented. Findings are summarized as follows. The pioneering stage involves the creation of values of the university-led innovation ecosystem. The expansion stage focuses on the establishment of critical mass. The authority stage covers maintaining authority and bargaining power. The renewal stage features continuous performance improvement. In particular, this theoretical model of the university-regional innovation ecosystem is meaningful in that it provides a theoretical basis for enhancing the effectiveness of government financial support projects, and for individual universities, it provides a framework for strategies suitable for their ecosystem building process.

• Journal of Families and Better Life
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• v.24 no.4 s.82
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• pp.51-73
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• 2006

The purpose of this study is to introduce the evolution of corporate family-friendly policies and programs, a recent business issue throughout the world. In addition, this study suggests implications for a corporate reference guide to work-family policies and programs by providing a comparative analysis of the typical stages of development of U.S. corporate family-friendly policies and programs, and by presenting model initiatives of Korean and American family-friendly companies. Just as technological changes at the time of the Industrial Revolution altered the relationship between workers and their work, more recent technological advances have again transformed this relationship, offering the promise of a society in which work demands a smaller portion of the worker's time and permitting the worker more freedom and control over work conditions. These new work arrangements have the promise of producing a new paradigm for work and family, based on which many industrialized nations have developed family-friendly policies already. Family-friendly policies and programs can be grouped into four discernable stages in the evolution of a corporate work-family agenda. According to these stages, most companies in Korea are in the predevelopment stage or stage 1. Development of scales to assess company family-friendliness is needed to create a family-friendly workplace environment, policies, and programs. It is critical that companies have champions who have the vision to step out in kent, and the determination to ensure that the family-friendly programs are solidly grounded. Companies should develop their work-family initiatives as an integral part of a program for managing diversity focusing on needs of women and minority employees.