• Korean Association of Arts Management
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• no.58
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• pp.153-177
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• 2021

This study attempted to analyze language networks based on the theory of art policy in the New Normal era triggered by COVID-19 and domestic and foreign policy trends. For analysis, data containing key words of "Corona" and "Art" were collected from Google News and Web documents from March to September 2020 to extract 227 refined subject words, and the extracted subject words were analyzed as indicators of frequency and centrality of subject words through the Netminor program. In addition, visualization analysis of semantic networks has been attempted for the analysis of relationships between each topic languages. As a result of the semantic network analysis, the most frequent topic was "Corona," and "Culture and Art," "Art," "Performance," "Online" and "Support" were included in the group with the most frequencies. In the centrality analysis, "Corona" was the most popular, followed by "the era," "after," "post," "art," and "cultural arts," with high frequency, "Corona," "art," and "cultural arts" also dominated most centrality. In particular, the top-level key words in the analysis of frequency and centrality of the topic are 'online' and 'support' and 'policy'. This can be seen as indicating that the rapid rise of non-face-to-face and online content and support policies for the artistic communities are needed due to the dailyization of social distance due to COVID-19.

• Health Policy and Management
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• v.27 no.4
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• pp.315-323
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• 2017

Background: This study was purposed to analyze the effect of spatial accessibility to the psychiatry department in general hospital on the outpatient visit of mental patients. Methods: Data was provided from the Statistics Korea and Statistical Geographic Information Service, National Health Insurance Service, Health Insurance Review and Assessment Service, and Korea Transport Institute in 2015. The study regions were 103 administrative regions such as Si and Gu. The 103 regions had at least one general hospitals with a psychiatry department. The number of outpatient visit of mental patients in regions was used as the dependent variable. Spatial accessibility to mental general hospital was used as the independent variable. Control variables included such as demographic, economic, and health medical factors. This study used network analysis and multi-variate regression analysis. Network analysis by ArcGIS ver. 10.0 (ESRI, Redlands, CA, USA) was used to evaluate the average travel time and travel distance in Korea. Multi-variate regression analysis was conducted by SAS ver. 9.4 (SAS Institute Inc., Cary, NC, USA). Results: Travel distance and time had significant effects on the number of outpatient visits in mental patients in general hospital. Average travel time and travel distance had negative effects on the number of visits. Variables such as (number of total population, percentage of aged population over 65, and number of mental general hospital) had significant effects on the number of visit in mental patients. Conclusion: Health policy makers will need to consider the spatial accessibility to the mental healthcare organization in conducting regional health planning.

• Health Policy and Management
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• v.14 no.2
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• pp.1-16
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• 2004

The study purpose was to find which factors affect selection of hospital network types. This study used the 1998 American Hospital Association Annual Survey Database from Health Forum. Among these U.S. hospitals, the researcher selected hospitals located in Metropolitan Statistical Areas. Therefore the final observation cases for analysis are 1,971 Metropolitan Statistical Area hospitals in the United States. To identify significant variables influencing hospital network types, the study used proportional odds logistics regression model on population size, Health Maintenance Organization penetration rate, and market competition rate of area including a hospital, types of hospital ownership, hospital bed size, proportion of Medicare patients and Medicaid patients in total hospital patients, and occupancy rate. Contrary to conventional wisdom, selection of hospital network types was influenced by population size of area which a hospital located, types of ownership, hospital bed size, and proportion of medicare patients rather than Health Maintenance Organization penetration. Population size 1,000,000-2,499,999 had the highest probability of selecting type IV (clinical-vertical integration) from an independent hospital, and a religious group owned hospitals and for-profit owned hospitals had the highest probability of selecting Type IV (clinical-vertical integration) from an independent hospital. A bed size had positive relation on selecting Type IV (clinical-vertical integration) from an independent hospital. Unlikely general belief that the selecting types of hospital network was determined by the change of health insurance policy such as Health Maintenance Organizations and Preferred Provider Organizations, the types of hospital network were influenced by community characteristics such as population size, and hospital characteristics.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.6
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• pp.1091-1101
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• 2015

Cache mechanism, which has been a research subject for a significant period of time in computer science, has become realized in the form of web caching in network practice. Web caching has various advantages, such as saving of network resources and response time reduction, depends its performance on cache replacement policy, therefore, analysis and consideration of the environment in which a web cache operates is essential for designing better replacement policies. Thus, in the current web environment where is rapidly changing relative to the past, a new cache replacement policy is necessary to reflect those changes. In this paper we stipulate some characteristics of the web at present, propose a new cache replacement policy, and evaluate it.

• East Asian Economic Review
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• v.28 no.1
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• pp.3-35
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• 2024

This paper utilizes social network analysis to examine the structural characteristics and trade dynamics of the renewable energy (hydropower, wind energy, and solar energy) trade network within the RCEP region from 2011 to 2020. The findings reveal: (1) The renewable energy trade network within the RCEP exhibits dynamism, heterogeneity, and an uneven development. The solar energy network is the most balanced and stable, while the wind energy network lags and shows marked fluctuations, with the hydropower network falling between these two. This demonstrates the diversity of energy trade within the region. (2) China, Singapore, and Japan are identified as the key exporting and importing countries, with Vietnam showing substantial growth potential. Individual analyses shed light on the stark disparities in trade status among nations, reflecting the diverse roles and future potential of member countries. (3) The QAP regression analysis reveals a significant influence of environmental pressure, particularly carbon dioxide emissions, on the renewable energy trade network. This study contributes to promoting environmental sustainability and energy security in the RCEP region and provides empirical evidence for global renewable energy trade strategies.

• Journal of the Korea Safety Management & Science
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• v.11 no.4
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• pp.193-199
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• 2009

Recently, an industrial production-distribution planning problem has been widely investigated in Supply Chain Management(SCM). One of the key issues in the current SCM research area is reverse logistics network. This study have developed a simulation model for the reverse logistics network. The simulation model analysis reverse logistics network issues such as inventory policy, manufacturing policy, transportation mode, warehouse assignment, supplier assignment. Computational experiments using commercial simulation tool ARENA show that the real problems. The model can be used to decide an appropriate production-distribution planning problem in the research area.

• Journal of the Korean Operations Research and Management Science Society
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• v.25 no.4
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• pp.27-44
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• 2000

In this study we consider a spares provisioning problem for repairable items in which a parts inventory system is incorporated. If a machine fails, a replacement part must be obtained at the parts inventory system before the failed machine enters the repair center. The inventory policy adopted at the parts inventory system is the (S, Q) policy. Operating times of the machine before failure, ordering lead times and repair times are assumed to follow a two-stage Coxian distribution. For this system, we develop an approximation method to obtain the performance measures such as steady state probabilities of the number of machines at each station and the probability that a part will wait at the parts inventory system. For the analysis of the proposed system, we model the system as a closed queueing network and analyze it using a product-form approximation method. A recursive technique as well as an iterative procedure is used to analyze the sub-network. Numerical tests show that the approximation method provides fairly good estimation of the performance measures of interest.

• Health Policy and Management
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• v.12 no.3
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• pp.54-76
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• 2002

This study investigated how much EVA which evaluate firm's value can explain hospital bankruptcy prediction as a explanatory variable including financial indicators in Korea. In this study, artificial neural network and logit regression which are traditional statistical were used as the model for bankruptcy prediction. Data used in this study were financial and economic value added indicators of 34 bankrupt and -:4 non-bankrupt hospitals from the Database of Korean Health Industry Development Institute. The main results of this study were as follows: First, there was a significant difference between the financial variable model including EVA and the financial variable model excluding EVA in pre-bankruptcy analysis. Second, EVA could forecast bankruptcy hospitals up to 83% by the logistic analysis. Third, the EVA model outperformed the financial model in terms of the predictive power of hospital bankruptcy. Fourth, The predictive power of neural network model of hospital bankruptcy was more powerful than the legit model. After all the result of this study will be useful to future study on EVA to evaluate bankruptcy hospitals forecast.

• International Journal of Contents
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• v.5 no.3
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• pp.57-64
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• 2009

Korea has relied on top down development method, in which companies, research and education institutions move into the industrial complexes established by the government. However, to improve local competitiveness, the paradigm is shifting from the government initiated industrial complex to the clusters based on the cooperative network of the region. Representative case is 'Samcheok-si Fire & Emergency industry cluster construction project' that begun in 2007. AHP technique analysis results on first-stage showed that priority was on policy and network elements, and the results of second-stage analysis show that priority was on Policy incentives to internationalize the cluster and strengthen link,. Cluster branding, Sharing of organizational culture to cope with changes in environment, Creation of group learning culture. The subject of this research is limited to Samcheok-si's the Fire and Emergency Industry cluster formation project. Therefore, the research area and standard should be expanded to increase generality in further researches.

• Korean Journal of Childcare and Education
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• v.20 no.1
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• pp.91-111
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• 2024

Objective: The purpose of this study is to explore trends in institutional evaluation research in early childhood education through keyword network analysis. This aims to understand trends in academic discourse on institutional evaluation and gain implications for follow-up research and related policy directions. Methods: A total of 6,629 keywords were extracted from 572 dissertations and journal articles published from January 2006 to October 2023 for the purpose of analyzing and visualizing the frequency and centrality of keywords, as well as the structural properties of keyword networks. The analysis and visualization were conducted using the TEXTOM, UCINET6, and NetDraw programs. Results: First, the number of institutional evaluation studies increased steadily from 2006 to 2010 and then decreased, with a higher frequency of studies on daycare centers compared to kindergartens. Second, the most frequently occurring keyword in the analysis was 'daycare center,' and the highest connection strength was found in the term 'daycare-center-evaluation.' Third, network analysis revealed that key terms for institutional evaluation research included 'evaluation certification,' 'recognition,' 'evaluation indicators,' 'teacher,' 'daycare center,' and 'kindergarten.' In the ego network analysis for each institution, 'parent' emerged as a highly ranked keyword. Conclusion/Implications: This study confirmed the perspectives of previous studies by revealing the structure of core concepts in early childhood education institution evaluation research, and provided implications for follow-up and direction of institution evaluation