• The Journal of Korean Society for School & Community Health Education
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• v.18 no.3
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• pp.83-95
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• 2017

Objectives: The purpose of the research is understand the priorities of national competency standards vocational key competence factors in nurse who is work in Seoul and Incheon. Methods: The design of this study is descriptive investigation research, and the subjects were 144 nurse. we establish the vocational key competency defined in national competency standards as analytic hierarchy analysis model. The vocational key competency has 10 categories and 34 sub-categories. And based on the survey in nurse, the weight representing relative importance of each factor were calculated by using analytic hierarchy process method. Results: The analytic hierarchy process analysis on 10 categories showed that professional ethics(0.149) was higher than any other categories while that of numeracy(0.040) was at the bottom. And the analysis on sub-categories revealed that the most important factors in each categories included the Ethical community(Professional ethics), Conflict management skills(Interpersonal skills), Problem solving capability(Problem-solving skills), Listening skills(Communication skills), Applicable technical skills(Technical skills), Ability to understand business(Ability to understand organizational structures), Information processing capabilities(Information capacity), Self-management skills(Self-development capability), Ability to manage time(Resource management capabilities), Basic math skills(Numeracy). Conclusions: The results in this study can be used as basic data for the development of liberal arts curriculum for Nursing.

• Journal of Digital Convergence
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• v.18 no.9
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• pp.323-329
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• 2020

There is a system of mandating the allocation of support to small business in certain percentage or more to facilitate technological innovation at small business. Trying to assess small business R&D projects, which receive a budget of three trillion won or more from the government every year, for their possibilities of success, a group of experts perform a technological evaluation with their technologies and their difficulty levels and review closely the possibilities of their commercialization and success. Used in such a review, the Analytic Hierarchy Process technique cannot make an objective judgment of evaluation criteria for evaluation items and guarantee the professionalism and fairness of small business R&D projects due to the inherent ambiguity and uncertainty of the evaluation criteria. This study proposed an R&D evaluation system based on Fuzzy-AHP for small business to provide objective weight for the evaluation items and assess the possibilities of such projects' success. The evaluation criteria were make objective as they were applied as section values based on triangular fuzzy numbers. Weight was assigned and applied according to the management guidelines of supportive projects for small business' technological development so that it could be reflected on actual assessment. The findings of the study will be helpful for reflecting the scoring weight of these evaluation items again when an expert is appointed for a new project and guaranteeing the professionalism and fairness of small business R&D project based on them.

• The Korean Journal of Food & Health Convergence
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• v.8 no.6
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• pp.19-29
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• 2022

Business intelligence (BI) is a process for turning data into insights that inform an organization's strategic and tactical decisions. BI aims to give decision-makers the information they need to make better decisions Patient safety analysis, illness surveillance, and fraud identification are just a few healthcare decision-making processes that can be supported by data mining. Thus, the purpose of the current research is to outline the need if BI as an essential factor in the healthcare sector by reviewing various scholarly materials and the findings. The present author conducted one of the most famous qualitative literature approach which has been called as PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analysis) statement. The selecting criteria for eligible prior studies were estimated by whether studies are suitable for the current research, identifying they are peer-reviewed and issued by notable publishers between 2017 and 2022. According to the result based on the PRISMA analysis, BI plays a vital role in the healthcare sector and there are four business intelligence factors (Data, Analytic, Reporting, and Visualization) that will ensure that the healthcare sector provides the right healthcare services to the customers to be addressed in this section include; data, analytics, reporting, and visualization.

• The Journal of Asian Finance, Economics and Business
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• v.9 no.6
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• pp.363-372
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• 2022

The purpose of this study is to investigate COVID-19's impact on firm survival, as well as the management accounting system's role in adjusting operation efficiency for business survival. Two sets of data comprising small enterprises in the service sector were used. The first business group serves customers who have changed their lifestyle to a new normal. The second business group serves customers who are affected by social distancing measures. The data was collected based on an in-depth interview method. The data was then evaluated using content analysis and analytic comparison. The results show that the COVID-19 situation positively impacts the business survival of the service businesses group that serves customers who have changed lifestyles. However, COVID-19 has a negative effect on the survival of service business groups that serve customers affected by social distancing measures. In addition, the management accounting used during COVID-19, small enterprises have analyzed the operating environment and used the information stored in the database to determine goals for the operation. This study provides comprehensive economic effects and the utilization of management accounting systems. The accounting systems helped to decide to adjust the operation process during the quick changing of the environment of the small enterprise in the service sector.

• Asia pacific journal of information systems
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• v.32 no.4
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• pp.945-963
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• 2022

With the widespread use of social media, online social platforms like Twitter have become a place of rapid dissemination of information-both accurate and inaccurate. After the COVID-19 outbreak, the overabundance of fake information and rumours on online social platforms about the COVID-19 pandemic has spread over society as quickly as the virus itself. As a result, fake news poses a significant threat to effective virus response by negatively affecting people's willingness to follow the proper public health guidelines and protocols, which makes it important to identify fake information from online platforms for the public interest. In this research, we introduce an approach to detect fake news using deep learning techniques, which outperform traditional machine learning techniques with a 93.1% accuracy. We then investigate the content differences between real and fake news by applying topic modeling and linguistic analysis. Our results show that topics on Politics and Government services are most common in fake news. In addition, we found that fake news has lower analytic and authenticity scores than real news. With the findings, we discuss important academic and practical implications of the study.

• 한국경영정보학회:학술대회논문집
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• 2008.06a
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• pp.114-120
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• 2008

While ubiquitous healthcare (u-health) services were expected to propagate along with conventional healthcare services, recent progress indicated rather limited market acceptance. In this paper, we investigated the fundamental causes of why the consumer acceptance level of u-health services has been low. We draw upon innovation adoption theories to analyze the consumer readiness of the typical u-health services. The comparative analysis between innovative u-health services and conventional services was performed using analytic hierarchy process (AHP). Subsequently, policy and business implications including technological breakthrough insights were discussed based on the customer perspective comparative adoption analysis. The propositions captured through this study provide useful insight to further studies on u-health services.

• Industrial Engineering and Management Systems
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• v.13 no.1
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• pp.15-28
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• 2014

Evaluation of the implementation and performance of a firm's green supply chain management (GSCM) is an ongoing process. Balanced scorecard is a multi-criteria evaluation concept that highlights implementation and performance measures. The literature on the framework is abundant literature but scarce on how to build a hierarchical framework under uncertainty with dependence relations. Hence, this study proposes a hybrid approach, which includes applied interpretive structural modeling to build a hierarchical structure and uses the analytic network process to analyze the dependence relations. Additionally, this study applies the fuzzy set theory to determine linguistic preferences. Twenty dependence criteria are evaluated for a GSCM implemented firm in Taiwan. The result shows that the financial aspect and life cycle assessment are the most important performance and weighted criteria.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2005.10a
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• pp.338-341
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• 2005

In this paper, we present analytic forms of the ordered weighted averaging (OWA) operator weighting functions, each of which has properties of rank-based weights and a constant level of orness, irrespective of the number of objectives considered. These analytic forms provide significant advantages for generating OWA weights over previously reported methods. First, OWA weights can be efficiently generated by use of proposed weighting functions without solving a complicated mathematical program. Moreover, convex combinations of these specific OWA operators can be used to generate OWA operators with any predefined values of orness once specific values of orness are α priori stated by decision maker. Those weights have a property of constant level of orness as well. Finally, OWA weights generated at a predefined value of orness make almost no numerical difference with maximum entropy OWA weights in terms of dispersion.

• KIEAE Journal
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• v.10 no.4
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• pp.123-130
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• 2010

A lot of construction companies in overseas markets of construction try to change 2D CAD to 3D CAD for improving business ability and change to Building Information Modeling(BIM) for integrating information produced from construction life cycle. In America, GSA(General Service Administration) requires a design drawing planed by BIM and in Singapore and Europe, the government encourages architectures to use this tool. Recently in the domestic market, many organizations related construction industry are aware of importance of 3D CAD integrated information, and try to use BIM. Therefore, this research would analyze how does BIM affect construction industry and derive influence factors and provide basic data for using BIM.

• Journal of the Korea Safety Management & Science
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• v.11 no.2
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• pp.153-158
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• 2009

An optimal selection problem of SCM system is one of the critical issues for the company's competitiveness and performance under global economy. This paper presents a hierarchy model consisted of characteristic factors for introducing SCM system and an AHP (Analytic Hierarchy Process) based decision-making model for SCM system evaluation and selection. The proposed model can systematically construct the objectives of SCM system selection to meet the business goals. This paper focuses on selecting an optimal SCM system considering both all decision factors and sub-decision factors of a hierarchy model. Especially, the benefit/cost analysis is applied to choose SCM system. A case study shows the feasibility of the proposed model and the model can help a company to make better decision-making in the SCM system selection problem.