• Industrial Engineering and Management Systems
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• v.1 no.1
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• pp.93-98
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• 2002

It is important to evaluate the performance of candidates mathematically from various aspects, and reflect it on decision making. In decision making, we judge the candidates through two steps, classification of objects and comparison of objects or candidates with plural elements. In the former step, Analytic Hierarchy Process (AHP) is useful method to evaluate candidates from plural viewpoints, and in the later step, Data Envelopment Analysis (DEA) is also useful method to evaluate candidates with plural categorized data. In fact, each candidate has plural elements, nevertheless it has been more important to evaluate from various aspects in IT society. So, we propose a new procedure complementing AHP with DEA.

• Management Science and Financial Engineering
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• v.14 no.2
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• pp.67-87
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• 2008

Data envelopment analysis (DEA) has proven to be a useful tool for assessing efficiency or productivity of organizations which is of vital practical importance in managerial decision making. While DEA assumes exact input and output data, the development of imprecise DEA (IDEA) broadens the scope of applications to efficiency evaluations involving imprecise information which implies various forms of ordinal and bounded data possibly or often occurring in practice. The primary purpose of this article is to characterize the variable efficiency in IDEA. Since DEA describes a pair of primal and dual models, also called envelopment and multiplier models, we can basically consider two IDEA models: One incorporates imprecise data into envelopment model and the other includes the same imprecise data in multiplier model. The issues of rising importance are thus the relationships between the two models and how to solve them. The groundwork we will make includes a duality study which makes it possible to characterize the efficiency solutions from the two models. This also relates to why we take into account the variable efficiency and its bounds in IDEA that some of the published IDEA studies have made. We also present computational aspects of the efficiency bounds and how to interpret the efficiency solutions.

• Proceedings of the KSR Conference
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• 2009.05a
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• pp.730-736
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• 2009

The objective of this paper is to measure the relative technical efficiency of Korean railway transport service. Previous studies on the efficiency in Korean railway service have carried out before the structural reform of Korean railway industry in 2004, whereas this study used the latest data which reflected the impact of reform. We analyzed the efficiency in Korean railway transport by means of measuring the technical efficiencies of other countries, these were estimated with data envelopment analysis. DEA has gained great popularity in measuring efficiency in transport industry, school, government, hospital and so on in recent years. This analysis could serve as peer to help improve performance of the railway management and operation.

• Journal of Korea Trade
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• v.25 no.7
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• pp.19-40
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• 2021

Purpose - This paper's purpose is to investigate how foreign ownership and innovation affect firm value. Design/methodology - Firm innovation is defined as operational efficiency, which is calculated by adopting data envelopment analysis (DEA). Additionally, R&D intensity is included as a measure of innovation in the analysis. We used firm-level data from manufacturing companies in Korea. The sample comprised 3,753 firm-year observations for every year in the period 2003-2017. Findings - We found that foreign ownership and innovation are positively related to firm value (Tobin's Q). Foreign ownership moderates innovation's contribution to firm value, implying that foreign ownership may enhance the value relevance of firm innovation. In addition, we found that firm innovation partially mediates the relationship between foreign ownership and firm value. Originality/value - This highlights the important role of foreign investors' monitoring; wherein foreign investors enhance firm value by facilitating firm innovation. Our results suggest that foreign ownership can be crucial for innovation and may serve to address weak ownership structures.

• Korean Management Science Review
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• v.19 no.1
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• pp.117-128
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• 2002

In this Paper we investigate the performance of the five efficiency estimation methods which include the stochastic frontier model estimated by maximum likelihood (SFML), the stochastic frontier model estimated by corrected ordinary least squares (SFCOLS), the data envelopment analysis (DIA) model, the combined estimation of SFML and DEA (SFML + DEA), and the combined estimation of SFCOLS arid DIA (SFCOLS+ DEA) using Monte Carlo analysis. The results include: 1) SFML provides most accurate efficiency estimates for the sample sloe 150 or over,2) SFML+DEAor SFCOLS + DIA Perform better for the cases with sample sloe 25, 50, and low random errors, 3) SFCOLS performs better for the close with sample sloe 25, 50, and very high random errors.

• Korean Journal of Organic Agriculture
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• v.17 no.1
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• pp.19-33
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• 2009

This paper evaluates the technical efficiency of organic farm management practices and studies its main determinants in Hongdongmyeon of Hongsung county, Chungnam province. The analysis is performed in two stages. First, the efficiency is measured via the nonparametric "Data Envelopment Analysis" (DEA) technique. The DEA models are constructed not only to assess the overall technical efficiency of organic fanning practices but also to evaluate the management efficiencies. In a second stage critical determinants of efficiency are determined using a Tobit model. In this analysis the focus is on technical and socio-economic variables. The analytical results show that technically efficient farms is about 13 percent and the mean technical efficiency is found to be 0.73 indicating that many farms are not operating at an efficient scale.

• Korea Journal of Hospital Management
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• v.13 no.3
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• pp.69-93
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• 2008

Rising healthcare cost is a global phenomenon that justifies governments' introduction of 'incentive regulation' plan for the improvement of hospital efficiency. A number of previous studies tried to evaluate the efficiency of healthcare organization by using Data Envelopment Analysis(DEA), a common efficiency benchmarking method. However, there is a concern that this kind of efficiency evaluation could induce "quantity-quality trade-off". Moreover, as quality aspect is especially important in terms of 'effectiveness' of health care, it should be considered in efficiency evaluation of healthcare organization. A number of different models were tried so far to incorporate quality aspect into DEA, however, none is universally recognized as a standard. Thus, in this study, previous quality-incorporating DEA models were categorized into 6 types according to the way of incorporating quality aspect, and strengths and limitations of each type were reviewed with a set of artificial data as an example. Based on this review, a new quality-incorporating efficiency evaluation model, named Quality-adjusted output DEA(QAO-DEA), was suggested. As an exploratory empirical analysis, technical efficiency of human resource were measured with different quality-incorporating DEA models, using 2004 data from National University Hospitals. In conclusion, Quality-adjusted output DEA(QAO-DEA) model seems to be one of the most desirable alternatives to incorporate quality aspect in efficiency evaluation of hospital, and deserves the consideration as a policy tool to induce simultaneous improvement of both efficiency and quality.

• Industrial Engineering and Management Systems
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• v.15 no.1
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• pp.49-62
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• 2016

In this paper, we propose an integrated data envelopment analysis (DEA) and analytic hierarchy process (AHP) methodology in which the information about the hierarchical structures of input-output data can be reflected in the performance assessment of decision making units (DMUs). Firstly, this can be implemented by extending a traditional DEA model to a three-level DEA model. Secondly, weight bounds, using AHP, can be incorporated in the three-level DEA model. Finally, the effects of incorporating weight bounds can be analyzed by developing a parametric distance model. Increasing the value of a parameter in a domain of efficiency loss, we explore the various systems of weights. This may lead to various ranking positions for each DMU in comparison to the other DMUs. An illustrative example of road safety performance for a set of 19 European countries highlights the usefulness of the proposed approach.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.7
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• pp.1764-1776
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• 2014

This study is the context about an introduction of a bookkeeping by double entry & accrual base accounting which is the turning point of National Accounting and defense integrated financial management which is delivered following system Digital Budget Accounting system, in other words about something to do with the improvement of efficiency of financial information data. National defense Integration Financial Information system (NDIFIS) facilitates Project program management and makes the whole process of Defense financial Business manageable in one system. Also, there is a purpose to increase the credibility and transparency of National defense finances by providing internal and external information users with credible financial statements and cost materials. By using data envelopment analysis (DEA) which is a useful method to measuring the efficiency of organization, this study aims to improve the financial information data efficiency by comparing the efficiency of the same type troops and when it comes to the inefficient troops, by offering the certain objective of efficiency.

• Convergence Security Journal
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• v.23 no.2
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• pp.95-102
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• 2023

The purpose of this paper was to confirm the operational level of the military department of universities, which plays a key role in the officer training process, through empirical research and confirm meaningful results for improvement. There are 11 university military departments operated through the Army, agreements, and semi-agreement, and the Data Envelopment Analysis (DEA) was applied from the perspective of resource input and performance for each university's military department operation to analyze relative efficiency and confirm specific directions for improvement. As a result of operational efficiency analysis, 6 DMUs (Decsision Making Unit) were found to be efficient in the BCC model out of 11 DMUs, and the evaluation results could be confirmed through classification of efficient and inefficient groups through data capture analysis. This paper may be of practical value in that it checks the efficiency of the comparative university military departments and confirms specific information for development through the DEA-Additive model that reflects several evaluation factors at once. Through this, the operators of each university's military department are admitted.