• Journal of the Korean Society for Library and Information Science
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• v.58 no.2
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• pp.343-361
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• 2024

This study aimed to assess perceptions of library usage and services among users of public libraries within Chungcheongbuk-do, as part of the groundwork for developing the basic plan for establishing the Chungcheongbuk-do Central Library. The survey results indicated that respondents consider policy formulation and implementation for the development of local libraries and enhancement of library services to be the most important role of the Chungcheongbuk-do Central Library. Additionally, respondents showed a preference for print materials as the preferred type of information resource for collection management, with literature being the most favored subject area. Finally, survey participants expressed a desire for the provision of diverse books and knowledge resources as the desired library service.

• Economic and Environmental Geology
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• v.39 no.5 s.180
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• pp.615-626
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• 2006

The natural resources and material life-cycle include all human activities related to resources and material extraction, transportation, processing, use, recovery and disposal. Sustainable material management (SMM) is an integrated set of policy approaches targeted on economic agents throughout the material life-cycles and designed to result in economically efficient and environmentally effective material use. The material flows of industrial mineral, ores and fossil fuels have also long been a focal area for environmental policies because of the high environmental pressures associated with extraction, processing, consumption, and final disposal of these materials. OECD work on material flow is to improve the quantitative and analytical knowledge bases about natural resource and material flows within and among countries, so as to better understand the importance of material resources in member countries' economies. In several EU Member States, material flow accounts are part of official statistics. Material flow analysis (MFA) is a valuation method which assesses the efficiency of use of materials using information from material flow accounting. Material flow analysis helps to identify waste of natural resources and other materials in the economy which would otherwise go unnoticed in conventional economic monitoring systems. Resource use and resource efficiency has emerged as a major issue for long-term sustainability and environmental policy.

• Knowledge Management Research
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• v.23 no.4
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• pp.133-157
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• 2022

As data becomes a new core resource with high attention, MyData service is spreading to various fields such as finance, medical care, and the public sector. However, research on the behavior of MyData service users is insufficient. Therefore, this study aims to empirically examine the effect of MyData service traits on value perception and acceptable behavior particularly in the financial sector where MyData service is most active. To this end, this study proposed a research model based on the literature. 295 survey responses were collected from individuals and analyzed using AMOS 26.0 for hypothesis testing. As a result of the analysis, it was found that self-information control, financial convenience, and personalized service had a significant effect on perceived value, and that perceived value had a significant effect on the intention to accept MyData service. Furthermore, this study examined the role of personal innovation and technological security in the relationship between variables by suggesting them as moderators. Results show that individual innovation was found to strengthen the relationship between two variables(self-information control and personalized service) and perceived value. Also, technological security was shown to strengthen the relationship between perceived value and intention to accept financial MyData services. The findings are expected to provide useful information to understand the factors affecting the acceptance of financial MyData service users and to understand the importance of individual innovation levels and technological security.

• Journal of Intelligence and Information Systems
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• v.26 no.4
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• pp.27-65
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• 2020

Many companies on information and communication technology make public their own developed AI technology, for example, Google's TensorFlow, Facebook's PyTorch, Microsoft's CNTK. By releasing deep learning open source software to the public, the relationship with the developer community and the artificial intelligence (AI) ecosystem can be strengthened, and users can perform experiment, implementation and improvement of it. Accordingly, the field of machine learning is growing rapidly, and developers are using and reproducing various learning algorithms in each field. Although various analysis of open source software has been made, there is a lack of studies to help develop or use deep learning open source software in the industry. This study thus attempts to derive a strategy for adopting the framework through case studies of a deep learning open source framework. Based on the technology-organization-environment (TOE) framework and literature review related to the adoption of open source software, we employed the case study framework that includes technological factors as perceived relative advantage, perceived compatibility, perceived complexity, and perceived trialability, organizational factors as management support and knowledge & expertise, and environmental factors as availability of technology skills and services, and platform long term viability. We conducted a case study analysis of three companies' adoption cases (two cases of success and one case of failure) and revealed that seven out of eight TOE factors and several factors regarding company, team and resource are significant for the adoption of deep learning open source framework. By organizing the case study analysis results, we provided five important success factors for adopting deep learning framework: the knowledge and expertise of developers in the team, hardware (GPU) environment, data enterprise cooperation system, deep learning framework platform, deep learning framework work tool service. In order for an organization to successfully adopt a deep learning open source framework, at the stage of using the framework, first, the hardware (GPU) environment for AI R&D group must support the knowledge and expertise of the developers in the team. Second, it is necessary to support the use of deep learning frameworks by research developers through collecting and managing data inside and outside the company with a data enterprise cooperation system. Third, deep learning research expertise must be supplemented through cooperation with researchers from academic institutions such as universities and research institutes. Satisfying three procedures in the stage of using the deep learning framework, companies will increase the number of deep learning research developers, the ability to use the deep learning framework, and the support of GPU resource. In the proliferation stage of the deep learning framework, fourth, a company makes the deep learning framework platform that improves the research efficiency and effectiveness of the developers, for example, the optimization of the hardware (GPU) environment automatically. Fifth, the deep learning framework tool service team complements the developers' expertise through sharing the information of the external deep learning open source framework community to the in-house community and activating developer retraining and seminars. To implement the identified five success factors, a step-by-step enterprise procedure for adoption of the deep learning framework was proposed: defining the project problem, confirming whether the deep learning methodology is the right method, confirming whether the deep learning framework is the right tool, using the deep learning framework by the enterprise, spreading the framework of the enterprise. The first three steps (i.e. defining the project problem, confirming whether the deep learning methodology is the right method, and confirming whether the deep learning framework is the right tool) are pre-considerations to adopt a deep learning open source framework. After the three pre-considerations steps are clear, next two steps (i.e. using the deep learning framework by the enterprise and spreading the framework of the enterprise) can be processed. In the fourth step, the knowledge and expertise of developers in the team are important in addition to hardware (GPU) environment and data enterprise cooperation system. In final step, five important factors are realized for a successful adoption of the deep learning open source framework. This study provides strategic implications for companies adopting or using deep learning framework according to the needs of each industry and business.

• Journal of Korean Library and Information Science Society
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• v.42 no.3
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• pp.189-208
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• 2011

In the digital environment where the Internet and IT change rapidly, researchers have utilized scientific information by relying on more complex and various media than before. This study performed a group interview with thirteen questions derived from five categories in order to understand information needs and information seeking behaviors of Korean doctoral researchers in this information environment. The five categories are (1) identifying information resource usage pattern, (2) attitude towards information resources and reasons for use, (3) IT skills and information literacy, (4) physical library use vs electronic access, and (5) attitudes toward the digital library. In particular, this study focused on analyzing similarities and differences of two groups of researchers selected equally in the humanities and social sciences and in science and technology by doing the interview. The research showed that there are no differences in the goal of using scientific information, information literacy, the ratio of using written materials to electronic resources, and routes of acquiring research ideas or knowledge, but there are differences in materials used for studies or researches and in favorite scientific portal sites.

• Proceedings of the Korea Association of Information Systems Conference
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• 1996.11a
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• pp.5-26
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• 1996

This study has two research objectives related to end-user computing (EUC). One of the research objectives was to investigate the current status of EUC of Korean firms. Another research objective was to examine the relationship between individual differences of end-users and EUC success. Using survey data from 752 end-users of 23 firms, the surrent status of EUC and the relationship between individual differences of end-users and EUC success were investigated. The current status of EUC was examined from six perspectives: 1). what is the characteristics of EUC strategy of Korean firms, 2). what are the individual characteristics of end-users in Korean Firms, #0. what are the characteristics of tasks performed by end-users using computer, 4). what are the application a areas of EUC, 5). How end-users are satisfied with the support of firms, 6). what are system usage and satisfaction of end-users. It was also foud that individual differences of end-users are related to EUC success. More specifically, it wat shown that the male gender, younger age, higher level of education, higher rank and organizational tenure, higher math ability, thinking type of cognitive style, positive and optimistic attitudes toward computer, more experience with computer, more computer education and knowledge are individual differences variables associated with EUC success. The results of stepwise regression analysis suggested that the individual difference variables accounted for 14%, 25%, 39% and 30% of the variances of four EUC success variables, satisfaction for outcome, satisfaction for ability, frequency of computer use, and the number of tasks, respectively. These empirical findings suggest that EUC managers should consider individual differences of end-users in managing EUC, such as education, training, support, and human resource management, to maximize potential benefits of EUC.

• The Journal of Information Systems
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• v.5
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• pp.383-409
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• 1996

This study has two research objectives related to end-user computing (EUC). One of the research objectives was to investigate the current status of EUC of Korean firms. Another research objective was to examine the relationship between individual differences of end-users and EUC success. Using survey data from 752 end-users of 23 firms, the current status of EUC and the relationship between individual differences of end-users and EUC success were investigated. The current status of EUC was examined from six perspectives : 1) what is the characteristics of EUC strategy of Korean firms, 2) what are the individual characteristics of end-users in Korean firms 3) what are the characteristics of tasks performed by end-users computer, 4) what are the application areas of EUC, 5) How end-users are satisfied with the support of firm, 6) what are system usage and satisfaction of end-users. It was also found that individual differences of end-users are related to EUC success. More specifically, it was shown that the male gender, younger age, higher level of education, higher rank and organizational tenure, higher math ability, thinking type of cognitive style, positive and optimistic attitudes toward computer, more experience with computer, more computer education and knowledge are individual differences variables associated with EUC success. The results of stepwise regression analysis suggested that the individual difference variables accounted for 14%, 25%, 39%, and 30% of the variances of four EUC success variables, satisfaction for outcome, satisfaction for ability, frequency of computer use, and the number of tasks, respectively. Theses empirical findings suggest that EUC managers should consider individual differences of end-users in managing EUC, such as education, training support, and human resource management, to maximize potential benefits of EUC.

• Journal of the Korean Society for information Management
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• v.19 no.4
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• pp.298-319
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• 2002

The Semantic Web is a new technology that attempts to achieve effective retrieval, automation, integration, and reuse of web resources by constructing knowledge bases that are composed of machine-readable definitions and associations of resources that express the relationships among them. To have this kind of Semantic Web in place, it is necessary to have the following infrastructures: capability to assign unchangeable and unique identifier (URI) to each resource, adoption of XML namespace concept to prevent collision of element and attribute names defined by various institutions, widespread use of RDF to describe resources so that diverse metadata can be interoperable, use of RDF schema to define the meaning of metadata elements and the relationships among them, adoption of DAML+OIL that is built upon RDF(S) to increase reasoning capability and expressive power, and finally adoption of OWL that is built upon DAML+OIL by removing unnecessary constructors and adding new ones based on experience of using DAML+OIL. The purpose of this study is to describe the central concepts and technologies related to the Semantic Web and to discuss the benefits of metadata interoperability based on XML/RDF schemas and the potential applications of diverse ontologies.

• The Journal of Information Systems
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• v.26 no.3
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• pp.1-23
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• 2017

Purpose With the advent of the 4th Industrial Revolution era, ICT convergence industry is leading the wave of new change. These changes in the industrial field are recognizing convergence as a strategic cooperation tool of management for creating new value. In order to achieve the research purpose, conceptual understanding of ICT convergence is summarized by focusing on concepts, features, types and cases. In addition, this study established the theoretical rationale for the determinants of ICT convergence performance, and examined previous researches related to ICT convergence. Design/methodology/approach The empirical research method is based on a survey of 510 companies including managers and mid-level practitioners who understand the contents of the relevant field, 305 data were used for analysis. We conducted exploratory factor analysis to verify the grouping of these questionnaire items and conducted confirmatory factor analysis to analyze the validity and reliability of the measurement model. Through the statistical analysis, we analyzed the structural relationship of ICT firms' competencies for convergence performance. Findings Linkage of ICT strategies established by corporations is an important factor for enhancing resource capacity and convergence ability. It is important to ensure that product innovation, consumer-oriented strategies, and ICT strategies for the implementation of business strategies are closely linked. In addition, in the convergence environment, companies should make efforts to develop convergence ability and improve organizational performance through utilization of ICT resources. From the CEO's perspective, it is necessary to understand the knowledge, technology and resources arising from the convergence environment, and to integrate with the resources possessed by the enterprise to induce the organization's performance.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2013.10a
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• pp.581-584
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• 2013

E-Learning, a technology-based learning process is the obtaining of knowledge from the basis of IT technology. The development of e-Learning requires corporate educational staff as well as HR staff, who manage e-learning, to drastically change their roles. The main reason for this is that the properly adapted and highly experienced education and training abilities of HR staff could accelerate the adoption and usage of e-Learning but they need to clearly select and define an appropriate curriculum from among the extensive mass-customized content with an e-learning basis. Here the research has analyzed the influence of the introduction and usage of e-Learning in hotels on HR staff and their roles from the viewpoint of hermeneutic phenomenology.