• Journal of Environmental Science International
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• v.32 no.8
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• pp.573-583
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• 2023

This study was conducted to verify the effectiveness of improving indoor environmental awareness, relieving stress, and improving learning efficiency in school indoor green space, and suggest desirable ways to develop indoor green space in the future. As part of the study, a survey was conducted among 225 individuals across six schools in a metropolitan area with garden and panel-type indoor gardens inside the school building. The survey comprised the current status and use of indoor green spaces, the perception of indoor green spaces, improvement measures in indoor green spaces, and basic properties. Semantic Differential (SD) was used to investigate the impression of school indoor spaces. Resultantly, the more frequent the use of green spaces in the school, the more they feel the positive effects of indoor green spaces, such as improving the school's indoor environment, reducing stress, and improving learning efficiency. In addition, it appears that the more frequent contact with the natural environment, the more they feel the positive effects provided by indoor green space at school. Therefore, it is suggested that educational conditions must be improved by revitalizing various green welfare, including indoor green areas, at the school level.

• Journal of Korea Trade
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• v.26 no.4
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• pp.83-97
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• 2022

Purpose - In this paper, we, taking South Korea's foreign direct investment in RCEP partners as an example, will examine its investment efficiency in these countries and analyze the main influencing factors, making suggestions for further liberalizing and facilitating its investment in and even for promoting its trade and economic cooperation with them. Design/methodology - In this study, we look at the panel data of South Korea and the other 13 RCEP countries (Brunei excluded) from 2000 to 2019 and apply the stochastic frontier analysis to measure its foreign direct investment efficiency and explore the influencing factors in RCEP countries. We examine the investment potential of South Korea in these places. Findings - We find that South Korea's average investment efficiency in RCEP countries reached 0.62, indicating large investment potential. We also find that its investment efficiency in RCEP partners was heterogeneous. Our study reveals that South Korea's foreign direct investment is significantly positively correlated with the market size and population of the two countries, as well as with whether the host country has a coastline and rich natural resources, while negatively with geographic distance. It shows that free trade agreements, economic freedom, and regulatory quality play significant roles in improving investment efficiency. Originality/value - Through theoretical and empirical analysis, we deal with the efficiency and influencing factors of South Korea's direct investment in RCEP partners, proposing new drivers for facilitating its trade and investment in these countries and comprehensively evaluating the efficiency and revealing the trend of its FDI in these countries. In this paper, we put forward a solid theoretical basis for empirical analysis of the future economic and trade development between South Korea and its RCEP partners and give objective insights for further improving its foreign direct investment efficiency and tapping its investment potential.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2000.04a
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• pp.365-373
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• 2000

Data Envelopment Analysis (DEA), a non-parametric productivity analysis tool, has become an accepted approach for assessing efficiency in a wide range of fields. Despite of its extensive applications and merits, some features of DEA remain bothersome. DEA offers no guideline about to which direction relatively inefficient DMUs improve since a reference set of an inefficient DMU, several efficient DMUs, hardly provides a stepwise path for improving the efficiency of the inefficient DMU.In this paper, we aim to show that DEA can be used to evaluate the efficiency of life insurance companies while overcoming its limitation with the aids of machine learning methods.

• Korea Journal of Hospital Management
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• v.24 no.4
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• pp.57-69
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• 2019

Purpose: This study aimed to analyze the job performance efficiency of nurses in the Neonatal Intensive Care Unit (NICU) by using the Data Envelopment Analysis (DEA). Additionally, the study aimed to provide a detailed method to improve the currently inefficient way in which nurses perform their jobs by differentiating the reference group of more efficient nurses, and to compare the characteristics of the more efficient group of nurses to those of the less efficient group of nurses. Methodology: This study evaluated the relative job performance efficiency of nurses by applying DEA to 43 nurses in the NICU. The input variables for the efficiency analysis were working career (years), time spent in direct nursing care (hours), overtime (hours), and job-related training (hours); the output variables were the job performance scores of professional practice, research, leadership, and education. Data were analyzed using SPSS IBM 23.0 and Open Source DEA (OSDEA). Findings: The relative job performance efficiency of the 43 nurses was 0.933, and 20 nurses were evaluated as more efficient. In addition, the study confirmed the possibility of improving the overall job performance efficiency by improving leadership, while controlling the current input variables. Lastly, the more efficient nurses had significantly higher job performance scores for research (t=2.028, p=0.049), leadership (t=2.036, p=0.048), and education (t=2995, p=0.005) than those who were less efficient. Practical Implications: It is suggested that job performance be evaluated using DEA to improve the overall job performance efficiency of NICU nurses. The analysis results from DEA for nurses becomes evidence in support of establishing individualized goals for each nurse, thus resulting in a foundation for systematic human resource management of nurses, and ultimately contributing to increase in the job performance efficiency of nurses.

• Journal of the Korean Operations Research and Management Science Society
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• v.40 no.1
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• pp.75-89
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• 2015

In recent years, attention to the high debt ratio in public institutions has pushed the government to make efforts in reducing the debt ratio. However, in order to stimulate the economy, the government needs drastically innovative measures that reduce debt by improving efficiency rather than moderate approaches that focus solely on debt reduction. Despite this need, no study has yet systematically analyzed the overall efficiency of domestic public institutions and identified the source of inefficiencies in each public entity. Therefore, largely two research questions are examined. First, this study compares the efficiency levels by types of public institutions. Second, this study identifies the cause of inefficiencies in each public institution and proposes directions for improving efficiency. Based on a 5-year data of 302 public institutions published in public business information systems and organizational websites from 2009 to 2013, Data Envelopment Analysis (DEA) was performed. The input variables include the number of employees and total costs while the output variables include sales and net income. Reflecting the characteristics of public institutions, the input-oriented CCR model and input-oriented BCC model were utilized. Analysis results are as follows. First, market-oriented public institutions showed the highest efficiency while fund management quasi-governmental agencies showed the highest inefficiency. Second, scale efficiency score was measured by applying the CCR model and the BCC model on the organizations with the lowest efficiency level, fund management quasi-governmental agencies. Based on these analysis results, the source of inefficiency and detailed directions for improvement were proposed for Decision Making Units (DMUs) with low CCR and BCC scores.

• 한국정보디스플레이학회:학술대회논문집
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• 2006.08a
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• pp.1339-1342
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• 2006

We focused on improving of the optical efficiency in the direct BLU. We could achieve the optical efficiency by reducing the thickness of BLU and processing the prism shapes on a reflection sheet. And we were able to reduce the Lamps.

• Journal of Korean Society for Quality Management
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• v.32 no.2
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• pp.77-92
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• 2004

It is difficult but very necessary to measure the productivity of container terminals as logistics service provider. It is meaningful to find the appropriate inputs and outputs of the logistics service delivery systems and to measure the relationship between these inputs and outputs. This study proposes a model of evaluating the efficiency of container terminals. The evaluation consists of three phases. First, DEA(Data Envelopment Analysis) phase, determines the efficiency score and weights of DMUs(Decision Making Unit). This phase performs through four steps : selection of DMU, selection of DEA model, determination of input and output factors, calculation of efficiency score and weights for each DMU. Secondly, CEM (Cross Evaluation Model) phase, is to calculate the cross-efficiency scores of DMUs. This phase performs through three steps: selection of CEM, determination of cross-efficiency score for each DMU and development of cross-efficiency matrix. Finally, average cross-efficiency analysis phase is to compute the average cross-efficiency score. The proposed model discriminates among DMUs and ranks DMUs, whether they are efficient or inefficient.

• 한국항공운항학회:학술대회논문집
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• 2007.12a
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• pp.49-52
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• 2007

• 대한임상약리학회:학술대회논문집
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• 2003.06a
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• pp.25-25
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• 2003

• Proceedings of the Materials Research Society of Korea Conference
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• 1998.08a
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• pp.38.2-38
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• 1998