• Journal of Information Technology Services
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• v.18 no.2
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• pp.123-141
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• 2019

The goal of this study is to review the major research trend on the convergence studies of AI and healthcare technologies. For the study, 15,260 English articles on AI and healthcare related topics were collected from Scopus for 55 years from 1963, and text mining techniques were conducted. As a result, seven key research topics were defined : "AI for Clinical Decision Support System (CDSS)", "AI for Medical Image", "Internet of Healthcare Things (IoHT)", "Big Data Analytics in Healthcare", "Medical Robotics", "Blockchain in Healthcare", and "Evidence Based Medicine (EBM)". The result of this study can be utilized to set up and develop the appropriate healthcare R&D strategies for the researchers and government. In this study, text mining techniques such as Text Analysis, Frequency Analysis, Topic Modeling on LDA (Latent Dirichlet Allocation), Word Cloud, and Ego Network Analysis were conducted.

• Journal of Korean Society of Archives and Records Management
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• v.17 no.3
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• pp.23-47
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• 2017

According to a recent survey, over 18,000 government information systems have numerous different functions and characteristics. Although every dataset that is created and maintained in government information systems is declared as a collection of records according to the Public Records Management Act, current electronic records management policies cannot cover dataset records management. This study suggests the policy directions for dataset records management at the national level. It emphasizes the necessity to preserve the appearance and behavior (function) of database systems to ensure the authenticity of dataset records. In addition, this study investigates "emulation" as a representation and long-term preservation methodology for dataset-type records. It also suggests a dataset records model.

• Journal of Korea Trade
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• v.26 no.6
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• pp.20-40
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• 2022

Purpose - In recent times, the international trade environment has been changing rapidly, centering on the online market. In the post-COVID-19 era, small and medium-sized trading companies are facing the problem of not being properly provided with overseas market research, market trend analysis, and trade-related information. Cloud-based digital trade is being sought as an alternative to solve these problems; however, there is a lack of research on the intention to switch to digital trade among small and medium-sized trading companies. Therefore, this study empirically analyzes the intention to switch to digital trade based on the migration theory, and through this, attempts to identify each factor that affects the intention to switch to digital trade. Design/methodology - In this study, in order to identify factors influencing intention to switch to digital trade and innovation resistance of small and medium-sized trading companies, through previous research on migration theory and the PPM (Push, Pull, Mooring) model, each variable was selected for the purpose of the study. Based on this, a research model was established for the factors affecting switching to digital trade of small and medium-sized trading companies and empirically analyzed. In addition, considering the differences in the innovation propensity and maturity of information infrastructure of trading companies as the recipients of innovation, this study analyzes the moderating effect of the mooring effect and seeks ways to establish specific strategies according to the degree. Findings - As a result of empirical analysis, the pull effect was found to have the greatest influence on intention to switch to digital trade. However, the pull factor was found to have an effect on user resistance, and it was confirmed that it was a factor simultaneously inducing positive and negative consumption behaviors among users. In addition, it was found that the higher the company's innovation propensity, the higher the pull effect's influence on the intention to switch, and analysis showed that the push effect had no influence. In addition, companies with high information infrastructure maturity were expected to have a relatively high level of intention to switch compared to companies with low information infrastructure maturity, and the difference between the two groups was found not to be statistically significant. Originality/value - This study is a timely study in that it demonstrated the effect on the switching to cloud-based digital trade for small and medium-sized trading companies and that the cloud system related to digital trade is in full swing. There are academic implications in that it revealed that the pull effect is an important factor in the intention to switch to cloud service. Practical implications were presented in that small and medium-sized trading companies suggested ways to increase the value of the cloud system for switching to digital trade and a way to increase the switching ratio by minimizing the mooring effect. In addition, the study argues that active institutional support from the government is needed to activate cloud service.

• Journal of the Korea Society of Computer and Information
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• v.26 no.10
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• pp.117-124
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• 2021

In this paper, we propose CANVAS (Creative ANalytics enVironment And System), an analytics system of the National Research Data Platform (DataON). CANVAS is a personalized analytics cloud service for researchers who need computing resources and tools for research data analysis. CANVAS is designed in consideration of scalability based on micro-services architecture and was built on top of open-source software such as eGovernment Standard framework (Spring framework), Kubernetes, and JupyterLab. The built system provides personalized analytics environments to multiple users, enabling high-speed and large-capacity analysis by utilizing high-performance cloud infrastructure (CPU/GPU). More specifically, modeling and processing data is possible in JupyterLab or GUI workflow environment. Since CANVAS shares data with DataON, the research data registered by users or downloaded data can be directly processed in the CANVAS. As a result, CANVAS enhances the convenience of data analysis for users in DataON and contributes to the sharing and utilization of research data.

• The Journal of Information Systems
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• v.31 no.1
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• pp.59-90
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• 2022

Purpose This paper presents a new method of classifying online platforms. It also explains how to apply the framework using case studies and generate new insight about platform strategies and policy development. Design/methodology/approach This paper focuses on the relationship between platforms, especially the hierarchy and power relations, and broadly classifies platforms as follows: content/services, meta information, app stores, operating systems, and cloud. Both the content/service platform and the meta information platform have matching as their main function. However, most content/services tend to collect and access information through meta-information platforms, so meta-information platforms are closer to infrastructure than content/service platforms. App store, operating system, and cloud can be said to be platforms of platforms. A small number of companies in the US and China dominate platforms of platforms, and become the recent development and regulatory targets of their respective governments. Findings We should be wary of the attempts to regulate domestic platforms by importing foreign regulations that ignore the hierarchical structure that our framework highlights. We believe that Korea's strategy to become a true platform powerhouse is clear. As one of the few countries with significant companies in the area of meta information platforms, it will be necessary to fully utilize the position and advance into the strategically important area of platforms of platforms. Furthermore, it is necessary to encourage world-class companies to appear in Korea in the app store, operating system, and cloud. To do so, the government needs to introduce promotion policies to strategically nurture such platforms rather than to regulate them.

• Journal of Korean Society for Quality Management
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• v.50 no.4
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• pp.751-776
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• 2022

Purpose: The purpose of this paper is to present implications by analyzing research trends on CSR, CSV and ESG by text analysis and visual analysis(Comprehensive/ Fields / Years-based) which are big data analyses, by collecting data based on previous studies on CSR, CSV and ESG. Methods: For the collection of analysis data, deep learning was used in the integrated search on the Academic Research Information Service (www.riss.kr) to search for "CSR", "CSV" and "ESG" as search terms, and the Korean abstracts and keyword were scrapped out of the extracted paper and they are organize into EXCEL. For the final step, CSR 2,847 papers, CSV 395 papers, ESG 555 papers derived were analyzed using the Rx64 4.0.2 program and Rstudio using text mining, one of the big data analysis techniques, and Word Cloud for visualization. Results: The results of this study are as follows; CSR, CSV, and ESG studies showed that research slowed down somewhat before 2010, but research increased rapidly until recently in 2019. Research have been found to be heavily researched in the fields of social science, art and physical education, and engineering. As a result of the study, there were many keyword of 'corporate', 'social', and 'responsibility', which were similar in the word cloud analysis. Looking at the frequent keyword and word cloud analysis by field and year, overall keyword were derived similar to all keyword by year. However, some differences appeared in each field. Conclusion: Government support and expert support for CSR, CSV and ESG should be activated, and researches on technology-based strategies are needed. In the future, it is necessary to take various approaches to them. If researches are conducted in consideration of the environment or energy, it is judged that bigger implications can be presented.

• Asia pacific journal of information systems
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• v.34 no.1
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• pp.150-190
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• 2024

This article proposes a framework to elucidate the structural dynamics of the generative AI ecosystem. It also outlines the practical application of this proposed framework through illustrative policies, with a specific emphasis on the development of the Korean generative AI ecosystem and its implications of platform strategies at AI platform-squared. We propose a comprehensive classification scheme within generative AI ecosystems, including app builders, technology partners, app stores, foundational AI models operating as operating systems, cloud services, and chip manufacturers. The market competitiveness for both app builders and technology partners will be highly contingent on their ability to effectively navigate the customer decision journey (CDJ) while offering localized services that fill the gaps left by foundational models. The strategically important platform of platforms in the generative AI ecosystem (i.e., AI platform-squared) is constituted by app stores, foundational AIs as operating systems, and cloud services. A few companies, primarily in the U.S. and China, are projected to dominate this AI platform squared, and consequently, they are likely to become the primary targets of non-market strategies by diverse governments and communities. Korea still has chances in AI platform-squared, but the window of opportunities is narrowing. A cautious approach is necessary when considering potential regulations for domestic large AI models and platforms. Hastily importing foreign regulatory frameworks and non-market strategies, such as those from Europe, could overlook the essential hierarchical structure that our framework underscores. Our study suggests a clear strategic pathway for Korea to emerge as a generative AI powerhouse. As one of the few countries boasting significant companies within the foundational AI models (which need to collaborate with each other) and chip manufacturing sectors, it is vital for Korea to leverage its unique position and strategically penetrate the platform-squared segment-app stores, operating systems, and cloud services. Given the potential network effects and winner-takes-all dynamics in AI platform-squared, this endeavor is of immediate urgency. To facilitate this transition, it is recommended that the government implement promotional policies that strategically nurture these AI platform-squared, rather than restrict them through regulations and stakeholder pressures.

• Journal of Digital Convergence
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• v.11 no.3
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• pp.115-126
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• 2013

The purpose of this study was to confirm the extent of the reduction in the total cost of ownership of the open source software in comparison to the commercial software installed for information system, PC and cloud computing. Accordingly, the actual reduction rates in the total cost of ownership, when open source software is installed in the information system, PC and cloud computing, were computed and analyzed for 51 companies in the area of information system, 18 companies in the area of PC and 6 companies in the area of cloud computing, which included government institution, educational institution and private enterprises. The results of expert survey illustrated that the reduction rates are (1)63.3% on the average for the 4areas of information system, namely, DBMS, WAS, Web and OS, (2) 59.4% on the average for the 6 areas of PC, namely, OS, Documentation Program, Back-up and Restoration, Screen Capture, Vaccine and Others and (3) 61.2% on the average for the 6 areas of cloud computing, namely, Virtualization, OS, WEM/WAS, DBMS, DFS and Cloud Management.

• International journal of advanced smart convergence
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• v.10 no.2
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• pp.53-58
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• 2021

In this paper, based on the real estate registration model in the Chinese internet environment, we propose a model for the joint business of banking collateral registration. This is to increase the efficiency and service level of the real estate mortgage registration process. And it can solve the problems that in the process of registering a mortgage loan, difficulty of data sharing between the real estate registration agency and the bank, and ordinary users and bank clerks duplicate unnecessary work. In addition, it realizes joint processing and data sharing of real estate registration work with real estate registration agencies and banks, increases the efficiency and level of government affairs services, and offers an optimized solution to realize a one-stop service for real estate security registration. The results of this study are expected to provide theoretical support for the application and innovation of the Internet environment real estate registration model.

• Electronics and Telecommunications Trends
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• v.39 no.3
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• pp.48-57
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• 2024

Cyberthreats and crimes have become common in society and demand the adoption of robust security measures. Financial cybercrimes, personal information breaches, and spam messages are now prevalent, while companies and nations face an increasing number of cyberthreats and attacks such as distributed denial of service, ransomware, and malware. As the overall socioeconomic landscape undergoes digitalization powered by big data, cloud computing, and artificial intelligence technologies, the importance of cybersecurity is expected to steadily increase. Developed nations are actively implementing various policies to strengthen cybersecurity and providing government support for research and development activities to bolster their domestic cybersecurity industries. In particular, the South Korean government has designated cybersecurity as one of the 12 nationwide strategic technology sectors. We examine the current landscape of cybersecurity companies and the information and communication technology supply chain, providing insights into the domestic cybersecurity market and suggesting implications for South Korea.