• International Journal of Advanced Culture Technology
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• v.11 no.1
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• pp.171-180
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• 2023

This study is to develop a performance analysis model for SMEs.Based on similar performance indicators through previous studies, performance indicators for SMEs were rewritten.Through the Korean Journal Citation Index (KCI), 75 related data were classified and a comprehensive SME performance analysis model was developed.Performance analysis was divided into two axes and classified into tables.The horizontal axis is the spatial performance range, which is divided into three areas: performance management by department/function, integrated performance management for the entire organization, and governance performance management requiring policy feedback. The vertical axis is subdivided into short-term, mid-term, and long-term by time and growth stage, and is divided into three parts: technical performance according to technological input, economic performance as organizational performance, and social performance for policy utilization. Then, performance indicators were mapped to each column. As a result of the survey, 28% of technical performance was analyzed as a result of frequency analysis, and performance indicators were organized into five categories: IT, R&D, certification, patent, and innovation. Economic performance was divided into 29%, BSC, HRD, logistics, production quality management, financial support, asset management, etc. 6 categories, social performance 43%, ESG, marketing, export, policy support, consulting, cooperation, etc. 7 categories.Limitations of the study include the narrowness of the survey that derived only performance indicators despite being a meta-analysis, and the performance model was mapped and classified according to growth stage and support period.however Insufficiency of validity due to lack of evidence, performance indicators were developed, but there were limitations in utilization for practical use.

• Proceedings of the Korean Society for Information Management Conference
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• 2002.11a
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• pp.23-65
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• 2002

This study is to consider varying factors of internal/external informational and operational environments in libraries, and develop a new evaluation indicators for university libraries in digital environments. In order to do this research, the previous works have been investigated, and the Delphi study and our own analysis have been performed. The main research results are as follows. First, the results through the Delphi method that was to adopted to verify evaluation items and indicators determined by the literature review show that the repressed values for each evaluation category is greater than 3.00. overall average is 4.02. and standard deviation is ranged from 0.40 to 0.62 for each category. This means that the evaluation indicators are valid. Second, the factor analysis was performed to verify the construct validity of evaluation indicators. As a result. the cumulative variance of evaluation indicators consisting of 11 dimensions per factor is 72.733%. In turn, this result shows that the validity of these indicators is very reliable. Third, t-test and one way ANOVA are performed within significance probability 0.05 in order to verify differences in each librarians point of views for the degree of importance in evaluation indicators. The results show that these evaluation indicators are verified to be appropriate since there is no significant difference. Based on the Delphi study and our own analysis. we developed a new evaluation indicators that consists of 7 evaluation categories, 35 evaluation items, and 92 evaluation indicators.

• Korean Journal of Organic Agriculture
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• v.21 no.4
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• pp.501-522
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• 2013

This study has performed comparative analysis on benefit indicators in agricultural irrigation and drainage project cases between Korea and Japan. The irrigation and drainage project with publicity should do economic analysis of direct benefit factors as well as indirect benefit factors. However, traditional economic evaluations are used that benefit factors are lack of consistency and focused on direct benefits. Therefore, the purpose of this study was to develop indicators for the economic evaluation of irrigation and drainage projects. We conducted a case study between Korea and Japan. The resulting benefit factors was divided into direct factors and indirect factors. The direct benefit factors were increase in income, cost savings. The indirect benefit factors were protection of property due to flooding, agricultural promotion, aesthetic improvement. The implications of this study are that the indicators of economic analysis can be evaluated and easily applied. Moreover, these indicators could promote the feasibility of economic analysis.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.8
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• pp.2016-2029
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• 2023

Accurate prediction of critical illness is significant for ensuring the lives and health of patients. The selection of indicators affects the real-time capability and accuracy of the prediction for critical illness. However, the diversity and complexity of these indicators make it difficult to find potential connections between them and critical illnesses. For the first time, this study proposes an indicator analysis model to extract key indicators from the preoperative and intraoperative clinical indicators and laboratory results of critical illnesses. In this study, preoperative and intraoperative data of heart failure and respiratory failure are used to verify the model. The proposed model processes the datum and extracts key indicators through four parts. To test the effectiveness of the proposed model, the key indicators are used to predict the two critical illnesses. The classifiers used in the prediction are light gradient boosting machine (LightGBM) and eXtreme Gradient Boosting (XGBoost). The predictive performance using key indicators is better than that using all indicators. In the prediction of heart failure, LightGBM and XGBoost have sensitivities of 0.889 and 0.892, and specificities of 0.939 and 0.937, respectively. For respiratory failure, LightGBM and XGBoost have sensitivities of 0.709 and 0.689, and specificity of 0.936 and 0.940, respectively. The proposed model can effectively analyze the correlation between indicators and postoperative critical illness. The analytical results make it possible to find the key indicators for postoperative critical illnesses. This model is meaningful to assist doctors in extracting key indicators in time and improving the reliability and efficiency of prediction.

• International Journal of Contents
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• v.18 no.3
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• pp.34-48
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• 2022

The purpose of this study was to develop indicators for quality management of educational institutions, and to achieve this, literature analysis and expert interviews were conducted. Through literature analysis, the components of TQM were derived focusing on factors to improve the quality of education, engineering education accreditation standards, and a representative education accreditation system, were considered. Additionally, seven areas as well as 32 indicators required for education quality management, were derived by comparing the EFQM excellence model and the MBNQA education model, applied for quality management of companies and institutions. By comparing and synthesizing these results, a draft was developed for the quality management index of educational institution. Next, opinions on correction and supplementation of quality management indicators derived from literature analysis, were collected from five education experts. From the comparisons and integration of these results, eight criteria (leadership, strategy, customers, people, facilities and environment, curriculum management, curriculum improvement, and performance management) and 34 indicators, were proposed for quality management indicators for educational institutions. Curriculum management, people, and performance management criteria were considered more significantly in quality management of educational institutions, and several implications are suggested based on the study results.

• Korean Management Science Review
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• v.28 no.2
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• pp.63-74
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• 2011

As business environment has become more competitive, the R&D strategies of firms have been regarded more important. Patent has information about technology which affects a firm's profit and it is considered as resources which have provided appropriate data for research of innovations and trends in technology. And patent indicators are known as qualitative representation of technology quality in an objective view. Also, they are available for the continuous and systematic analysis. However, most previous studies have focused on developing patent indicators to investigate patent value and characteristics. Furthermore they have limitations that most results is not significant that patent indicators have effect on firm performance-Tobin's q, Intangible assets based on balance sheet, sales and etc. Thus, the purpose of this paper is to propose proper a factor to represent a firm performance and to analyze causal relationship between patent indicators and firm performance. Intangible assets based on market value are employed as one of most significant firm performance indicator. The results indicate that intangible assets are appropriate for analyzing causal relation between patent and a firm performance with 7 significant indicators among 10 patent indicators. Considering firm's exogenous factors, regression analysis of each data for five years is performed. This result is similar to regression analysis of full data for all years.

• Quality Improvement in Health Care
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• v.8 no.2
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• pp.186-207
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• 2001

Background : This study presented an analysis of healthcare quality indicators using data mining and a development of decision support system for quality improvement. Method : Specifically, important factors influencing the key quality indicators were identified using a decision tree method for data mining based on 8,405 patients who discharged from a medical center during the period between December 1, 2000 and January 31, 2001. In addition, a decision support system was developed to analyze and monitor trends of these quality indicators using a Visual Basic 6.0. Guidelines and tutorial for quality improvement activities were also included in the system. Result : Among 12 selected quality indicators, decision tree analysis was performed for 3 indicators ; unscheduled readmission due to the same or related condition, unscheduled return to intensive care unit, and inpatient mortality which have a volume bigger than 100 cases during the period. The optimum range of target group in healthcare quality indicators were identified from the gain chart. Important influencing factors for these 3 indicators were: diagnosis, attribute of the disease, and age of the patient in unscheduled returns to ICU group ; and length of stay, diagnosis, and belonging department in inpatient mortality group. Conclusion : We developed a decision support system through analysis of healthcare quality indicators and data mining technique which can be effectively implemented for utilization review and quality management in a healthcare organization. In the future, further number of quality indicators should be developed to effectively support a hospital-wide Continuous Quality Improvement activity. Through these endevours, a decision support system can be developed and the newly developed decision support system should be well integrated with the hospital Order Communication System to support concurrent review, utilization review, quality and risk management.

• Journal of Advanced Navigation Technology
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• v.25 no.6
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• pp.456-465
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• 2021

For predictive aviation safety management, the establishment of safety performance indicators to measure and manage the safety performance of service providers must be preceded. In particular, leading indicators are significant in that they play an important role in identifying and managing the causes of accident/incident in advance. However, the current safety performance indicators of the domestic aviation industry have limitations in that they focus on lagging indicators based on events that have already occurred. Therefore, the purpose of this study is to construct Korean leading indicators for preventive safety management. In addition, we verify the validity and importance of the indicators based on review of the experts and AHP analysis. This study is meaningful in that it can support the proactive safety management of the domestic aviation industry through the development of leading safety indicators, which have been relatively lacking in research.

• Journal of the Korea Institute of Building Construction
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• v.14 no.4
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• pp.329-335
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• 2014

This study suggests architect specialty contractors' strategies by interaction analysis between construction business indicators and business performance indicators. To do this, a database was compiled for construction orders and business performance indicators of specialty contractors with KRW 7 bil. or more of assets of 1997 through 2010. The causal relationship verification and actual proof-oriented analysis were performed for architect specialty contractors. The result is analyzed that their turnover ratio of total liabilities and net worth are affecting obtention of construction orders, ultimately increasing the operating profits. Therefore, this type of specialty contractors is determined to be able to secure corporate stability by establishing a specific operation plan for the total assets.

• Journal of the East Asian Society of Dietary Life
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• v.18 no.6
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• pp.1089-1098
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• 2008

The principal objective of this study was to reveal the relationship between the menu management indicators and menu performance indicators in contract-foodservice operations. Menu indicators differed according to the type of business, type of contract, type of serving, and number of service lines. In accordance with the results of our correlation analysis, we noted significant correlations between menu performance indicators and menu management indicators. The first of these was the correlation between the food cost ration and meal counts, food loss, and the use of prepared vegetables. The second of these was the correlation between food cost per meal and forecasting error, food loss, and inventory turnover. The last of these correlations was the negative correlation between menu CSI(customer satisfaction index) and the use of prepared vegetables. According to the results of our canonical correlation analysis, 2 significant functions were identified. In the first function, we noted significant correlations between meal counts, use of prepared vegetables, food loss, and food cost ratio. Additionally, we noted significant correlations between forecasting error, inventory turnover, food loss, and food cost per meal in the second function. Menu management indicators had no influence on customer satisfaction.