• Journal of Distribution Science
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• v.12 no.3
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• pp.85-98
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• 2014

Purpose - This study primarily aims to represent the current trend of research on CPFR as a promising supply chain collaboration program and proposes a new framework for analyzing any collaboration programs in terms of three key collaborative features. Research design, data, and methodology - This study employs a literature review of selected studies that conduct research on CPFR. CPFR is analyzed based on the proposed framework that characterizes collaboration programs in terms of three key collaborative features. Results - The analysis based on the proposed framework reveals that the current form of CPFR continues to have some collaborative features that are not fully utilized to create an advanced collaboration program. The literature review indicates that most past studies ignore critical issues including the dynamic nature of the multiple-stage supply chain system and negotiation process for collaborative agreement in CPFR implementation. Conclusions - Results indicate that CPFR can become a better supply chain collaboration program by incorporating coordinative cost payment and joint decision making processes. Based on observations on the existing literature of CPFR, this study indicates several important issues to be addressed by future studies.

• Journal of Families and Better Life
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• v.6 no.1
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• pp.95-116
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• 1988

this study has dual purposes; one is to develope a new theoretical framework in consumer behavior area by applying the human ecological approach, and the other is to test the theory empirically area by applying the human ecological approach, and the other is to test the theory empirically by examining prepurchasing behavior of housing. Research methods adopted in this study are library search and survey research with self-administered questionnaires. The statistical methods used in the survey research are factor analysis, chi square test, and multivariate analysis with crosstablulations. According to the human ecological approach, ecological environments are important sources of consumer needs which , in turn, are satisfied by purchasing behavior in the market. Within this theoretical framework, consumers con improve the quality to life by perceving clearly what their needs are thereby making the most possible efficient purchasing decision making. The major findings of the empirical research on the basis of the theoretical framework are as follows; 1) Housing needs significantly vary with different ecological environment. 2) consumer information search behavior does not differ significantly by housing needs. 3) Housing needs turn out to be an intervening variable between ecological environments and consumer information search behavior. the results of this study show that the human ecological approach is useful in consumer behavior studies. The empirical result that consumer needs are not significantly satisfied by consumer behavior suggests a now direction in consumer education.

• Korean Medical Education Review
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• v.26 no.1
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• pp.19-26
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• 2024

This study examines a systematic and effective approach to career guidance in medical education, with a particular focus on the 6-year integrated career guidance education framework implemented at the College of Medicine, The Catholic University of Korea. Based on the "New SLICE" educational development principles, this framework comprehensively addresses the needs of medical students in career planning and development. It is structured into three phases: understanding yourself, exploring options, and choosing a specialty. The first phase, understanding yourself, helps students to recognize their strengths, weaknesses, aptitudes, and potentials, thereby setting the direction for future career choices. This phase includes various psychological tests and Self-Development and Portfolio courses. The second phase, exploring options, enables students to engage in related activities such as research and practical training, providing direct and indirect experiences across various fields. This phase offers courses including Medical Field Experience, Career Guidance through the Learning Community & Advisory Professors, and Student Participation in Professor Research Projects. The final phase, choosing a specialty, involves students making decisions based on in-depth self-assessment and exploration of majors, with a capstone project being a significant component. Maximizing the efficiency of career decision-making requires integration between the basic medical curriculum and postgraduate education. Including the period up to residency entrance in the framework is necessary for effective career guidance education.

• International Journal of Computer Science & Network Security
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• v.23 no.10
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• pp.135-146
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• 2023

An effective educational program warrants the inclusion of an innovative construction which enhances the higher education efficacy in such a way that accelerates the achievement of desired results and reduces the risk of failures. Educational Decision Support System (EDSS) has currently been a hot topic in educational systems, facilitating the pupil result monitoring and evaluation to be performed during their development. Insufficient information systems encounter trouble and hurdles in making the sufficient advantage from EDSS owing to the deficit of accuracy, incorrect analysis study of the characteristic, and inadequate database. DMTs (Data Mining Techniques) provide helpful tools in finding the models or forms of data and are extremely useful in the decision-making process. Several researchers have participated in the research involving distributed data mining with multi-agent technology. The rapid growth of network technology and IT use has led to the widespread use of distributed databases. This article explains the available data mining technology and the distributed data mining system framework. Distributed Data Mining approach is utilized for this work so that a classifier capable of predicting the success of students in the economic domain can be constructed. This research also discusses the Intelligent Knowledge Base Distributed Data Mining framework to assess the performance of the students through a mid-term exam and final-term exam employing Multi-agent system-based educational mining techniques. Using single and ensemble-based classifiers, this study intends to investigate the factors that influence student performance in higher education and construct a classification model that can predict academic achievement. We also discussed the importance of multi-agent systems and comparative machine learning approaches in EDSS development.

• Journal of Korean Elementary Science Education
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• v.42 no.3
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• pp.421-433
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• 2023

This study examined the reasoning of gifted elementary science students in a socioscientific issues (SSI) classroom discussion on COVID-19-related trash disposal challenges. This study aimed to understand the characteristics of evidence use and decision-making difficulties in each type of SSI-related reasoning. To this end, the transcripts of 17 gifted students of elementary science discussing SSIs in a classroom were analyzed within the framework of informal reasoning. The analysis framework was categorized into three types according to the primary influence involved in reasoning: rational, emotional, and intuitive. The analysis showed that students exhibited four categories of evidence use in SSI reasoning. First, in the rational reasoning category, students deemed and recorded scientific knowledge, numbers, and statistics as objective evidence. However, students who experienced difficulty in investigating such scientific data were less likely to have factored them in subsequent decisions. Second, in the emotional reasoning category, students' solutions varied considerably depending on the perspective they empathized with and reasoned from. Differences in their views led to conflicting perspectives on SSIs and consequent disagreement. Third, in the intuitive reasoning category, students disagreed with the opinions of their peers but did not explain their positions precisely. Intuitive reasoning also created challenges as students avoided problem-solving in the discussion and did not critically examine their opinions. Fourth, a mixed category of reasoning emerged: intuition combined with rationality or emotion. When combined with emotion, intuitive reasoning was characterized by deep empathy arising from personal experience, and when combined with rationality, the result was only an impulsive reaction. These findings indicate that research on student understanding and faculty knowledge of SSIs discussed in classrooms should consider the difficulties in informal reasoning and decision-making.

• Health Policy and Management
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• v.30 no.3
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• pp.286-300
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• 2020

In 2019, the Seoul metropolitan government established its own 'Seoul-type paid sick leave project'. Although the central government had to introduce such a system, which is also called sickness benefits, it was not implemented. In order to understand the process by which the Seoul government has implemented such a policy, this study used Kingdon's multiple streams framework. As a result, in the problem stream, it was found that the economic burden of sickness has been considered only in terms of medical expenses in the past of Korea. Then Songpa's three women and Middle East respiratory syndrome incidents raised awareness of the necessity of the sickness benefit system in 2014 and 2015. In the political stream, several social affairs such as national health insurance huge surpluses and the 2017 presidential election opened policy window. At that time, Seoul Mayor actively promoted sickness benefits as a policy entrepreneur. In the policy stream, the sickness benefit system has gained new attention through political events. To summary, these three streams flowed separately and then they assembled around huge political affairs. As a result, it was confirmed that Kingdon's model is the most effective theory than any other models in analyzing the health care policy decision process in Korea.

• KIEAE Journal
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• v.15 no.5
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• pp.95-105
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• 2015

Purpose: This paper presents a framework development for BIM (Building Information Modeling)-based OOPM (Object-Oriented Physical Modeling) for Building Thermal Simulation. The framework facilitates decision-making in the design process by integrating two object-oriented modeling approaches (BIM and OOPM) and efficiently providing object-based thermal simulation results into the BIM environment. Method: The framework consists of a system interface between BIM and OOPM-based building energy modeling (BEM) and the visualization of simulation results for building designers. The interface enables a BIM models to be translated into OOPM-based BEM automatically and the thermal simulation from the created BEM model immediately. The visualization module enables the simulation results to be presented in BIM for building designers to comprehend the relationships between design decisions and the building performances. For the framework implementation, we utilized the Modelica Buildings Library developed by the Lawrence Berkeley National Laboratory as a thermal simulation solver. We also conducted an experiment to validate the framework simulation results and demonstrate our framework. Result: This paper demonstrates a new methodology to integrate BIM and OOPM-based BEM for building thermal simulation, which enables an automatic translation BIM into OOPM-based BEM with high efficiency and accuracy.

• Journal of Electrical Engineering and Technology
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• v.1 no.4
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• pp.414-422
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• 2006

Deterministic techniques have been applied in power system planning for many years and there is a growing interest in combining these techniques with probabilistic considerations to assess the increased system stress due to the restructured electricity environment. The overall reliability framework proposed in this paper incorporates the deterministic N-1 criterion in a probabilistic framework, and results in the joint inclusion of both adequacy and security considerations in system planning. The combined framework is achieved using system well-being analysis and traditional adequacy assessment. System well-being analysis is used to quantify the degree of N-1 security and N-1 insecurity in terms of probabilities and frequencies. Traditional adequacy assessment is Incorporated to quantify the magnitude of the severity and consequences associated with system failure. The concepts are illustrated by application to two test systems. The results based on the overall reliability analysis framework indicate that adequacy indices are adversely affected by a generation deficient environment and security indices are adversely affected by a transmission deficient environment. The combined adequacy and security framework presented in this paper can assist system planners to realize the overall benefits associated with system modifications based on the degree of adequacy and security, and therefore facilitate the decision making process.

• Journal of Korean Society for Quality Management
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• v.52 no.1
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• pp.23-42
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• 2024

Purpose: This study aims to investigate the impact of two types of information quality, which are platform-oriented information quality and customer-oriented information quality, on customers' decision-making processes in the Online to offline (O2O) platform environment. Grounded in the product brokering efficiency model, which encompasses screening cost, evaluation cost, and decision quality, a model framework was developed. Furthermore, this study explores how these decision-making processes affect customer loyalty. Methods: Given that food delivery apps are the most widely used O2O service in Korea, this study targeted users of these apps for data analysis. We conducted hypothesis testing through a purposive sampling methodology focusing on food delivery app users. A Partial Least Squares Structural Equation Modeling analysis was conducted to analyze the data. The data collection occurred via an online survey from October to December 2021, with a total of 212 respondents participating. Results: The results of this study revealed the significant role of information quality in helping customers' decision processes while using food delivery apps. Specifically, it was found that platform-oriented information positively influences decision quality, while customer-oriented information significantly affects both the reduction of evaluation cost and the enhancement of decision quality. Additionally, the study indicated that lower evaluation costs and higher decision quality lead to increased platform loyalty. However, a reduction in screening cost did not have a significant impact on platform loyalty. Conclusion: While previous studies have overlooked the existence of two sides, service provider and user, in a platform, this research holds significance in its analysis of how information quality impacts loyalty by utilizing the two kinds of information quality. Practitioners can enhance customer loyalty to the platform by enriching customer-oriented information, thereby reducing customers' evaluation costs and encouraging more loyal usage of the platform.

• Journal of Korean Institute of Industrial Engineers
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• v.36 no.4
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• pp.230-242
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• 2010

In this paper, an environmental monitoring and diagnosis system based on ubiquitous computing technology, shortly u-Eco Monitoring System, is proposed. u-Eco Monitoring System is designed to: 1) Collect information from the manufacturing processes via ubiquitous computing technology, 2) Analyze the current status, 3) Identify the cause of problem if detected by rule-based and case-based reasoning, and 4) Provide the results to the operator for proper decision making. Based on functional modeling, a generic architecture is derived, followed by application to a manufacturing system in iron and steel making industry. Finally, to show the validity of the proposed method, a prototype is developed and tested. The developed methods can be used as a conceptual framework for designing environmental monitoring and diagnosis system for industrial practices by which monitoring accuracy and response time for abnormal status can be significantly enhanced, and relieving operator pressure from manual monitoring and error-prone decision making.