• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.12
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• pp.8719-8727
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• 2015

The purpose of this study is to examine the production efficiency of Rose farm and to explain the factors of the inefficiency. To analysis the production efficiency, SFA(Stochastic Frontier Analysis) and DEA(Data Envelopment Analysis) methods are measured, and then, Tobit regression model is used to analysis the influential factors on the production efficiency. As a result, first, the production efficiency by SFA is 88.4%, and by DEA, results are 78.5% and 85.2% in the CRS and VRS model, respectively. In particular, the production efficiency of the measurement results of the two methods are complementary, it is described in the same order of efficiency of each management body. Second, the results of tobit model shows that 6 input-factors are significant, and seed/nursery and material costs, which have the largest regression coefficient value and positive effect on production efficiency, are the most influential factors. Therefore, the results of this study indicates Rose farm can enhance their management efficiency by increasing amount of the seed/nursery and material costs.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.13 no.4
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• pp.1551-1556
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• 2012

This study proposes an efficient portfolio selection methodology for the listed corporations in KOSPI with consideration of managerial efficiency. For each industrial sector classified by KRX(Korea Exchange), the proposed method carries out an efficiency analysis using DEA (Data envelopment analysis) approach and for the efficient corporations filtered by DEA, construct portfolio using Markowitz's Model. In order to show the effectiveness of the proposed method, we constructed annually portfolios for 4 years (2007-2010) out of 600 listed corporations in KOSPI and KOSDAQ, and proved that our portfolios are superior to benchmark portfolios in terms of rate of returns.

• Journal of Korea Port Economic Association
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• v.28 no.2
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• pp.179-194
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• 2012

In this study, we compared the efficiency of container terminals using DEA. To do this, we designed an AHP/DEA hybrid model using AHP and DEA, and evaluated the efficiency by comparing the container terminal operation company in Gwangyang(KEC, KIT, GICT) and Busan(HBCT, DPCT, KBCT, UPT, Gamman, PNC, PNIT, HJNC, HPNT). The proposed model can control the number of selected promising container terminal by applying DEA-AR model. This model can also improve the credibility of analysis by using objective weights through the AHP application to efficiency evaluation data and normalizing the evaluation data to apply AHP and DEA. The model assumes inputs to be container crane, transfer crane, yard tractor, and reach stacker and output as container traffic. The result shows that DPCT was an efficient DMU.

• Journal of the Korean Society for Library and Information Science
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• v.36 no.3
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• pp.275-286
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• 2002

This paper estimates the relative efficiency of 29 university libraries in Seoul by data envelopment analysis. We employed library space, staff and book collection as inputs, and book circulation and reader visits as outputs. The result shows that average efficiency score is 0.5248 and only 3 libraries are efficient. Inefficiency is estimated to be 47.52%. Reorganization may be necessary in order to achieve greater efficiency.

• The Journal of the Korea Contents Association
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• v.19 no.7
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• pp.99-109
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• 2019

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, some features of DEA remain bothersome. For example DEA is good at estimating "relative" efficiency of a DMU(Decision Making Unit), it only tells us how well we are doing compared with our peers but not compared with a "theoretical maximum." Thus, in order to measure efficiency of a new DMU, we have to develop entirely new DEA with the data of previously used DMUs. Also we cannot predict the efficiency level of the new DMU without another DEA analysis. We aim to show that DEA can be used to evaluate the efficiency of ports and suggest the methodology which overcomes the limitation of DEA through hybrid analysis utilizing DEA along with C5.0. We can generate classification rules C5.0 in order to classify any new Port without perturbing previously existing evaluation structures by proposed methodology.

• Journal of Korea Port Economic Association
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• v.37 no.3
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• pp.75-91
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• 2021

Due to increased competition in supply side to reduce operational costs, port professionals have experienced extreme pressure, which demanded academicians to develop the model for efficient port operations from the industry perspective. Among many ports in the world, U.S. ports are our primary interest to analyze in our study for its high volume of cargoes transacted in the U.S. ports. We primarily employed DEA (Data Envelopment Analysis) technique to research the productivity of U.S. ports and applied the algorithm of double bootstrapped DEA proposed by Simar & Wilson (2007) to further investigate the driving forces of the performance of U.S. port operations. The external variables employed in our study comprise onDock Rail, Channel Depth, Location, Area, Acres, ForeignCargoRatio, and TEUChange, out of which onDock Rail, Acres, ForeignCargoRatio, and TEUChange were significant. In order to evaluate the effects of methodology selection, we conducted the same analysis applying the Censored model (Tobit) and contrasted the outcomes drawn from the two different techniques. Based on the findings from this work we proposed managerial implications and concluded.

• Journal of Digital Convergence
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• v.9 no.6
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• pp.1-11
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• 2011

It is time to review the direction of R&D investment which is the source of change in knowledge information ages. The DEA(Data Envelopment Analysis) is a efficient method by using the ratio of input and output elements. In this paper, we analyzed industry relationship and efficiency by DEA in order to analyze ripple effect of the regional industry technology development project. According to these results, we found the primary affected factor in performance of this project was human resource, and the turnover of participated company was not on the rise yet. On types of the project, we could find the efficiency quotient of critical technique development project was higher than of common technique development project because project period or budget scale infected to project performance. We expect the enhancement of technique developer, tenn and budget, and it is necessary the project results should lead performance such as sales force and employee growth.

• Journal of the East Asian Society of Dietary Life
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• v.17 no.5
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• pp.727-737
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• 2007

The aims of this study was to suggest a new efficiency measurement indicator for evaluating the management efficiency of decision making units(DMUs) in the contract foodservice industry. The data envelopment analysis(DEA) model which considers multiple inputs and outputs and looking for benchmarks, was used to compare the productivity of DMUs. We considered sales, profits, and customer satisfaction as output variables and it adopted food cost, labor cost and administrative expense as input variables. The results of applying DEA revealed relatively efficient types of business and service types. The efficiency of school units was highest and the mired service type was the most efficient one. In this study the CCR model efficiency was analysed with profit and the customer satisfaction index by the matrix method. DEA efficiency was correlated with profit but there was no correlation between DEA efficiency and the customer satisfaction index.

• The Korean Journal of Financial Management
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• v.17 no.2
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• pp.277-292
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• 2000

본 연구는 Charnes, Cooper와 Rhodes에 의하여 고안된 DEA기법을 이용하여 서울지역에 소재하고 있는 지역신용협동조합의 운영효율성을 평가하였다. 여기에서는 금융기관은 금융서비스를 제공하는 생산체로 보아 예수금은 산출물로 취급하여, 투입물은 직원수 영업장의 면적(또는 업무용부동산), 경비 등으로 하고, 산출물은 신규예금취급건수, 신규대출건수, 예수금기말잔액, 대출금기말잔액, 영업이익 등으로 하여 DEA모형의 데이터로 사용하였다. DEA에 의한 연구 결과는 기존의 경영평가방법이 제공할 수 없는 유용한 정보를 제공하고 있으며, 이러한 정보를 이용하여 투입물과 산출물을 효율적으로 관리할 수 있다는 것을 보여 준다. 그러므로 DEA에 의한 분석정보와 기존의 경영평가방법에 의한 정보를 적절하게 사용하면 조합들의 운영효율성을 개선하는 데 도움이 될 것이다.

• Proceedings of the Korea Association of Information Systems Conference
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• 2005.12a
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• pp.334-346
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• 2005

The purpose of this paper is to introduce the concept of worst practice DEA, which aims at identifying worst performers by placing them on the efficient frontier. This is particularly relevant for our application to credit risk evaluation, but this also has general relevance since the worst performers are where the largest improvement potential can be found. The paper also proposes to use a layering technique instead of the traditional cut-off point approach, since this enables incorporation of risk attitudes and risk-based pricing. Finally, it is shown how the use of a combination of normal and worst practice DEA models enable detection of self-identifiers. The results of the empirical application on credit risk evaluation validate the method which is proposed in this paper.