• International Journal of Contents
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• v.17 no.3
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• pp.48-66
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• 2021

We proposed a B2B food distribution platform by transforming an established food distribution and management platform based on blockchain technology. Our proposed model introduced a method to bring innovation into the domestic B2B food distribution market and systematically manage and utilize massive data (country of origin, producer, transaction, distributor, final consumer) generated within the food distribution process.

• The Korean Journal of Archival Studies
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• no.77
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• pp.37-74
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• 2023

As the Yoon Seok-yeol administration enters its second year in office, it is beginning to vigorously promote policies related to the "digital platform government," which is the 11th of the 120 national tasks. Accordingly, the Digital Platform Government Committee established and reported the 'Digital Platform Government Realization Plan' to the President in April 2023, and the 「Act on Provision and Use of Public Data」 and 「Data An amendment to the Act on the Vitalization of Infrastructure Administration" was submitted to the National Assembly in June 2023. In addition, the 「Regulations on the Promotion of Administrative Efficiency and Collaboration」, which is a Presidential Decree, was revised to 「Regulations on Operation and Innovation of Administrative Affairs」, including the name change, to effectively promote innovation in administrative work, and was completed on June 27, 2023. Therefore, this study aims to examine the trends of public institutions related to the digital platform government as a government task, and discuss whether the recent trends will affect the management of institutional records. Indications to respond to the government's digital platform, which is leading the way, it was emphasized that the operation of the current Medical Records Act is strange.

• Management & Information Systems Review
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• v.39 no.1
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• pp.93-114
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• 2020

Platform is considered as an alternative strategy to the traditional linear pipeline based business. Moreover, in the 4th industrial revolution period, efficiency driven pipeline business model needs to be changed to platform business. We have such success stories about platform as Apple, Google, Amazon, Uber, and so on. However, for those smaller corporations, it is not easy to find out the transformation strategy. The essence of platform business is to leverage network effect in management. Thus platform based management can be rephrased as network management across the business functions. Research on platform business is popular and related to diverse facets. But few scholars cover what the research trend of the domain is. The main purpose of this paper is to identify the research trend on platform business in Korea. To do that we first propose the analytical model for platform architecture whose components are consumers, suppliers, artifacts, and IT platform system. We conjecture that mapping of the research work on platform to the components of the model will make us understand the hidden domain of platform research. We propose three hypotheses regarding the characteristics of research and one proposition for the transitional path from pipeline to platform business model. The mapping is based on the research articles filtered from the Korea Citation Index, using keyword search. Research papers are searched through the keywords provided by authors using the word of "platform". The filtered articles are summarized in terms of the attributes such as major component of platform considered, platform type, main purpose of the research, and research method. Using the filtered data, we test the hypotheses in exploratory ways. The contribution of our research is as follows: First, based on the findings, scholars can find the areas of research on the domain: areas where research has been matured and territory where future research is actively sought. Second, the proposition provided can give business practitioners the guideline for changing their strategy from pipeline to platform oriented. This research needs to be considered as exploratory not inferential since subjective judgments are involved in data collection, classification, and interpretation of research articles.

• Journal of Platform Technology
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• v.11 no.5
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• pp.49-58
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• 2023

Factory energy management system is rapidly growing and evolving due to factors such as the 3rd Basic Energy Plan and global energy cost increases, as well as environmental issues. However, implementing an essential data collection system for energy management in factory settings, which have limited space and unique characteristics, presents spatial, environmental, and energy-related challenges. This paper endeavors to mitigate these challenges by devising a data collection system implemented through an edge-based lightweight platform. A comparison and evaluation of database operation on edge devices are conducted. To conduct the evaluation, a benchmarking tool called CDI Benchmark is developed, utilizing the characteristics of existing factories involved in practical applications. The evaluation results revealed that RDBMS systems like MySQL encountered errors in the database due to high data insertion loads, making them inoperable. On the other hand, InfluxDB, thanks to its highly efficient compression algorithm, demonstrated compression rates about 6 times higher than MyRocks according to the evaluation. However, it was observed that MyRocks outperformed InfluxDB by a significant margin, recording a maximum processing time approximately 80 times faster compared to InfluxDB.

• Proceedings of the Korea Contents Association Conference
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• 2009.05a
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• pp.797-801
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• 2009

In the proposed u-health service platform mobile u-health served an a series of process of bio data collection and storage and bio data analyses and results notice, and I interpreted it to a process. I became a design so as the service platform which supported health management system construction easily loaded service applied mobile u-health, and to be able to operate it in mobile environments, and took utility of a service platform and usability into consideration, and I got the crux of u-health use service.

• Journal of Information Technology Applications and Management
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• v.31 no.1
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• pp.163-175
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• 2024

This study conducts topic modeling analysis on four electric scooter sharing platforms: Alpaca, SingSing, Kickgoing, and Beam. Using user review data, the study aims to identify key topics and issues associated with each platform, as well as uncover common themes across platforms. The analysis reveals that users primarily express concerns and preferences related to application usability, service mobility, and parking/accessibility. Additionally, each platform exhibits unique characteristics and challenges. Alpaca users generally appreciate convenience and enjoyment but express concerns about safety and service areas. SingSing faces issues with application functionality, while Kickgoing users encounter connectivity problems and device usability issues. Beam receives overall positive feedback, but users express dissatisfaction with application usability and parking. Based on these findings, scooter sharing service providers should focus on enhancing application features, stability, and expanding service coverage to meet user expectations and improve customer satisfaction. Furthermore, highlighting platform-specific strengths and providing tailored services can enhance competitiveness and foster continuous service growth and development.

• Journal of Korea Society of Industrial Information Systems
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• v.17 no.7
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• pp.149-158
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• 2012

Much attention is being paid to social media because of their potentials to draw collective intelligence. In this context does this study attempt to draw some implications of social media as knowledge creation platform and suggest a conceptual framework of social media management. Information sharing among the public through social media literally produces profound influence throughout the society and thus not only business firms but all levels of public institutions, including government are seeking to take its advantage for various purposes such as public relations, crowd sourcing, etc. Especially considering that social media open the possibility of social knowledge creation platform in the Big Data era, this study is perhaps able to contribute to further development of social media management model together with a series of measuring indexes.

• Journal of the Korea Society of Computer and Information
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• v.28 no.1
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• pp.55-63
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• 2023

In this paper, we propose a function and service of the Disaster Crisis Alert Management System that automatically analyzes the situation judgment criteria to issue a disaster crisis alert and a plan to operate in the National Disaster Management System(NDMS). In the event of a disaster, a crisis alert(interest-caution-alert-serious) is issued according to the crisis alert level. In order to automatically analyze and determine the crisis alert level, first, data collection, crisis alert level analysis, crisis alert level judgment, and disaster crisis alert management system that expresses the crisis alert level by spatial scale(province, city, district) were implemented. The crisis alert level was analyzed and expressed in two ways by applying the intelligent crisis alert level(determination of regional sensitivity, risk level, and crisis alert level) and the crisis alert standard of the crisis management manual(province-level standard setting). Second, standard metadata, linkage of situation information of target) and API standards for data provision are presented to jointly utilize data linkage and crisis alert data of the disaster and safety data sharing platform so that it can be operated within the NDMS.

• Journal of Platform Technology
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• v.12 no.1
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• pp.141-150
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• 2024

The importance of personal data protection is increasingly emphasized both at home and abroad, and while overseas countries are applying various policies and dynamic management technologies, there are some gaps between compliance with laws and regulations and the application of technologies in Korea, and there are few user interfaces that provide convenient ways for data subjects to stop processing personal data. This study first analyzes the need for dynamic personal information consent management technology, the current state of the industry, and the prospects for its development. Next, this study proposes a basic model for dynamic management of personal information consent that maximizes the data subject's right to personal data self-determination while strictly complying with personal data protection laws in Republic of Korea. In particular, this study analyzes the basis of domestic laws and regulations related to the suspension of personal data processing, designs a basic model of personal data consent dynamic management interface, and presents its effectiveness. Based on the results of this study, we expect that the proposed dynamic management model for personal data use consent can be used in various ways for various websites and applications in the future.

• International Journal of Internet, Broadcasting and Communication
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• v.14 no.3
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• pp.91-100
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• 2022

Major developed countries are seriously considering smart factories to increase their manufacturing competitiveness. Smart factory is a customized factory that incorporates ICT in the entire process from product planning to design, distribution and sales. This can reduce production costs and respond flexibly to the consumer market. The smart factory converts physical signals into digital signals, connects machines, parts, factories, manufacturing processes, people, and supply chain partners in the factory to each other, and uses the collected data to enable the smart factory platform to operate intelligently. Enhancing personalized value is the key. Therefore, it can be said that the success or failure of a smart factory depends on whether big data is secured and utilized. Standardized communication and collaboration are required to smoothly acquire big data inside and outside the factory in the smart factory, and the use of big data can be maximized through big data analysis. This study examines big data analysis and standardization in smart factory. Manufacturing innovation by country, smart factory construction framework, smart factory implementation key elements, big data analysis and visualization, etc. will be reviewed first. Through this, we propose services such as big data infrastructure construction process, big data platform components, big data modeling, big data quality management components, big data standardization, and big data implementation consulting that can be suggested when building big data infrastructure in smart factories. It is expected that this proposal can be a guide for building big data infrastructure for companies that want to introduce a smart factory.