• Knowledge Management Research
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• v.21 no.4
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• pp.243-263
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• 2020

The purpose of this study is to propose the performance measurement model for open big data platform. In order to develop the performance measurement model, we have integrated big data reference architecture(NIST 2018) with performance prism model(Neely et al. 2001) in the platform perspective of open big data. Our proposed model consists of five key building blocks for measuring performance of open data platform as follows: stakeholder contribution, big data governance capabilities, big data service capabilities, big data IT capabilities, and stakeholder satisfaction. In addition, our proposed model have twenty four evaluation indices and seventy five measurement items. We believe that our model could offer both research and practical implications for relevant research.

• International Journal of Knowledge Content Development & Technology
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• v.12 no.3
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• pp.79-99
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• 2022

South Korea is at an important juncture in its history to decide whether to continue its investment to become a first-mover of artificial intelligence (A.I.) platform technology or stay as a fast follower. This paper compares South Korea's A.I. platform capacity to that of the United States, China and the European Union by reviewing publicly opened documents and reports on AI platform strategies and policies using the three elements of the national innovation capacity: common innovation infrastructure, cluster-specific conditions, and quality of linkages. This paper found three major areas the South Korean government can focus on in the A.I. platform industry. First, South Korea needs to increase its investment in the A.I. field and expand its public-private collaboration activities. Second, unlike the U.S. and the U.K., South Korea lacks data protection policies. Third, South Korea needs to build a high-performance system and environment to experiment with artificial intelligence technology and big data.

• Journal of the Korea Society of Computer and Information
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• v.21 no.7
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• pp.31-38
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• 2016

In this paper, we propose a direction for improving 'Geospatial information open platform' service to support the converged and integrated geospatial information. Since there can be a number of issues relating to the support for geospatial information convergence industry, two qualitative surveys were performed to collect opinions comprehensively and specifically. The responses from 165 experts from 5 areas that use geospatial information were used, and the requirements of demanders were divided into the aspect of policy, aspect of data development and distribution, and aspect of data utilization support in order to effectively analyze the survey results. As a result, a total of 26 major issues were derived and it was deemed that it is necessary to find a way to expand the role of 'Geospatial information open platform' from "Open-API Oriented Passive Spatial Information Open Platform" to "Platform that Comprehensively Provides Active Convergence Support Information" order to resolve the issues derived.

• The Journal of Information Systems
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• v.32 no.3
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• pp.225-251
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• 2023

Purpose The purpose of this study is to examine the future direction of in-vehicle app development and service, the relationship between potential customers' intention to use and the factors that affect it was explored. It was also checked whether the two types of app development platform and the experience of the existing smartphone app platform had a moderating effect on these relationships. Design/methodology/approach Data was gathered through surveys, collecting responses from 904 potential consumers of vehicle app services in Korea. Structural equation modeling was utilized to analyze the data. Findings According to the empirical analysis result, it was found that potential customers considered enjoyment as the most important benefit factor in in-vehicle app service, and the most important external factor affecting enjoyment was functional compatibility with smartphone. The type of vehicle app development platform did not have a meaningful moderating effect on the factor relationship, whereas the smartphone app platform experience showed a meaningful moderating effect on the relationship between factors. It was analyzed that the risk of app performance, personal information privacy, and driving safety data did not have a negative effect on the intention to use the vehicle app service.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.58-61
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• 2022

As data is evaluated as a key asset for digital transformation, efficient and stable management of data, smooth sharing data, and provision of services using data are also required in the defense. To support this, the Korean military is laying the foundation for the Military Artificial Intelligence Platform which is a defense data management infrastructure. In this paper, we examine the data strategies and data platform promotion directions of Korea and major advanced groups, and we look for suggestion and present the direction of development of the Military Intelligent Platform. We are expected that it can contribute to the establishment of a safe and efficient defense data management infrastructure for the Korean military.

• Journal of Convergence for Information Technology
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• v.11 no.5
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• pp.23-29
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• 2021

Recently, a situation in which a specific content service is impossible worldwide has occurred due to a failure of the platform service and a significant social and economic problem has been caused in the global service market. In order to secure the stability of platform services, intelligent platform operation management is required. In this study, big data flow management(BDFM) and implementation method were proposed to quickly detect to abnormal service status in the platform operation environment. As a result of analyzing, BDFM technique improved the characteristics of abnormal failure detection by more than 30% compared to the traditional NMS. The big data flow management method has the advantage of being able to quickly detect platform system failures and abnormal service conditions, and it is expected that when connected with AI-based technology, platform management is performed intelligently and the ability to prevent and preserve failures can be greatly improved.

• Journal of Internet Computing and Services
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• v.20 no.6
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• pp.73-84
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• 2019

Machine learning as a service, the so-called MLaaS, has recently attracted much attention in almost all industries and research groups. The main reason for this is that you do not need network servers, storage, or even data scientists, except for the data itself, to build a productive service model. However, machine learning is often very difficult for most developers, especially in traditional science due to the lack of well-structured big data for scientific data. For experiment or application researchers, the results of an experiment are rarely shared with other researchers, so creating big data in specific research areas is also a big challenge. In this paper, we introduce the KISTI-ML platform, a community-based rapid AI model development for scientific data. It is a place where machine learning beginners use their own data to automatically generate code by providing a user-friendly online development environment. Users can share datasets and their Jupyter interactive notebooks among authorized community members, including know-how such as data preprocessing to extract features, hidden network design, and other engineering techniques.

• The Journal of Information Systems
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• v.32 no.2
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• pp.25-43
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• 2023

Purpose In online delivery platforms, platform workers are required to perform both platform labor, which is compensated with immediate wages, and shadow work which is a kind of unpaid job to support the platform labor. Thus, the objective of this study is to empirically examine how platform workers' platform labor and shadow work affect their job burnout and their turnover intention in the online delivery platform context. Design/methodology/approach This study developed a research model by employing platform labor and shadow work to influence job burnout and turnover intention. This study also tested the model by partial least square techniques after collecting 169 cross-sectional data from food delivery riders in Korea. Findings This study found that both platform labor and shadow work affected platform workers' job burnout. In addition, the results showed that shadow work influenced their turnover intention while platform labor did not affect the turnover intention. Based on the results, this study contributed to relevant researchers who are interested in platform contexts by offering measurable constructs on platform labor and shadow work. In addition, this study could provide practitioners with practical implications on managing platform workers.

• Journal of Korea Water Resources Association
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• v.55 no.6
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• pp.471-480
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• 2022

In this study, a integrated platform applied with various analysis and evaluation models and data collection modules was developed for urban river management. Modules applied to the integrated platform are data collection and provision module, flood analysis module, river evaluation module, and levee breach simulation module, which were selected and applied for efficient urban river management. The integrated platform collects data for application to analysis and evaluation modules from various institutions. The collected data is refined through pre-processing and stored. The stored data is used as input data for each module and is also provided as an Open API through the platform. The flood analysis module is provided to analyze and prepare for floods occurring in cities and rivers. The river evaluation module is used for river planning and management by evaluating rivers in various ways. Finally, the levee breach simulation module can be used to establish countermeasures by deriving a possible damage area due to levee breach through analysis of a virtual breach situation.

• Journal of Distribution Science
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• v.19 no.11
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• pp.81-90
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• 2021

Purpose: The purpose of this research is that Metaverse platforms' UXBDI can be distinguished among Metaverse platform channel types. Metaverse platform represents a collective term signifying services that include augmented reality, lifelogging, mirror worlds, and virtual worlds. User Experience-Based Design Innovativeness (UXBDI) is characterized by novelty in product design and services that satisfy user experience. This study examined the effect of Metaverse platforms' UXBDI on user-Metaverse platform relationships. Research design, data and methodology: Metaverse platform users were selected as samples, and a marketing research institution known as a panel company conducted the survey. It used multiple regression to test the impact on platform identification and commitment based on a survey of 442 South Korean respondents. Results: The research confirmed that UXBDI sub-dimensional scales of attractiveness and interaction increased user-Metaverse platform identification and commitment. Also, a Metaverse platform identity increased user-Metaverse platform identification in virtual and mirror worlds. Conclusion: This study contributes to multiple academic fields. First, the UXBDI of Metaverse platforms appears to be a key component of ongoing user-Metaverse relationships. Second, UXBDI affects relationships differently based on the Metaverse platform type.