• The Journal of Fisheries Business Administration
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• v.34 no.2
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• pp.109-129
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• 2003

The purpose of this study is to evaluate the managerial efficiency of fisheries cooperatives in Korea by using data envelopment Analysis(DEA). The DEA method is a relative evaluation method on the basis of linear programming. Also, it is known as a useful method for the evaluation of not-for-profit organizations which cannnot be measured by mere monetray units for their performances. The 50 units have been taken for the purpose of analysis. All of the units are homogeneous groups, and the produce multiple services with multiple inputs. Input variables are a number of employee, fixed assets, and business managerial costs. Output variables include a number of deposits, a number of loans, a total deposits, a total loans, and operational income for one year. The empirical results of this study are as follows. First, the average technical efficiency showed 82.35% which revealed about 17.65% of non-efficiency in 2001. Second, in 15 DMUs, the overall inefficiency is mainly attributed to their efficient operations or management. To be opposed, in 18 DMUs, the overall inefficiency is mainly attributed to their scale efficiency. Third, efficiency ranking results by DEA do not agree with the ratio analysis by fisheries cooperatives. Fourth, average efficiency level by year was improving gradually by 0.7408 in 1999, 0.8023 in 2000, and 0.8235 in 2001 at significant 10% level.

• The Journal of Fisheries Business Administration
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• v.47 no.1
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• pp.63-86
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• 2016

The purpose of this study is to investigate production efficiency of Oceans and Fisheries Human Resources Development Programs Efficiency using Bootstrap-DEA. The study extracts 33 officials curriculum, 11 fisheries managers curriculum for its analytical. First, the study estimates technical, pure technical, and scale efficiency of each curriculums based on traditional DEA under the assumption of CRS and VRS. 8(official 7, managers 1) curriculums are identified as efficient DMUs under the CCR-model, and 13(official 10, managers 3) under the BCC-model. We provide inputs that allow inefficient curriculum to be efficient DMUs on a production frontier, and a reference set for their bench-marking. Second, rank test, Wilcoxon-Mann-Whitney test to find a statistical significance of heterogeneity existing in efficiences between Bootstrap-DEA tenical vs Bootstrap-DEA pure technical was no significant difference. We have identified that G10, 11, 12 13, 25, 31, 33, 39 curriculums are the most efficiently produced in the technical and pure technical efficiency. Also we managed to measure the inefficiency which exists in efficiently produced curriculums when estimating the bias corrected efficiency scores. In Technical efficiency, Operation and facility was significant at the 10%. In Pure technical efficiency, facility was significant at the 10%.

• Journal of Fisheries and Marine Sciences Education
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• v.28 no.6
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• pp.1629-1639
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• 2016

This study is to estimate the production efficiency of abalone aquaculture and to find its determinants utilizing the survey data of operating expenses in 2015. The first part of the analysis applied both DEA and Super-DEA for the estimation of efficiency of each aquaculture household as DMU. We used wages, feeding costs and area as inputs and annual profits and sales as outputs of the model. The second part of the study applied both Tobit and OLS for the identification of determinants of the efficiency. We investigated cost-ratio, depreciation costs, careers, value of living seeds, cleaning costs of farming ground and a ratio of 1 and 2 year-old abalone at shipment as potential determinants. The estimation results show us that the average technical efficiency, pure technical efficiency, and scale efficiency score turn out to be 72%, 81% and 85% respectively. The Super-BCC and Super-CCR models reveal their average efficiency scores as 81% and 80%. All of the variables used to identify the determinants of the efficiency. The study results suggests that the production efficiency can be improved by cleaning farming ground and hence lowering the death rate of seeds.

• The Journal of Fisheries Business Administration
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• v.42 no.2
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• pp.15-30
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• 2011

This study is designed to measure the relative efficiency of regional fishery cooperatives based on Data Envelopment Analysis(DEA) methods. Selecting 40 regional fishery cooperatives in Busan as Decision Making Units (DMUs), the study uses their panel data from 2007 to 2008 to rank the relative efficiency of the DMUs. First, the efficiency score of the DMUs are calculated using CCR, SBM, and super-SMB model. Within the model, input variables are the number of employees and area of fishery cooperatives. Output variables are the amount of deposit money, loan and profit. Based on the efficiency scores calculated from super-SMB model, the efficiency ranking of the DMUs is determined. Second, the differences in average efficiency calculated from the three DEA models are tested using a pair-wise mean comparison test. The results based on the efficiency scores evaluated from super-SMB model show that seven out of the forty DMUs are efficient; among the efficient DMUs, the DMUs that can be benchmarked for inefficient DMUs through the frequency analysis of reference set being identified. Third, the differences in average efficiency of the three DEA models between 2007 and 2008 are tested using pair-wise mean comparison test and the study estimates the efficiency change of the DMUs between 2007 and 2008 using Malmquist productivity index(MPI). Finally, the paper suggests an improved composite DMU superior to the inefficient DMUs evaluated by Super-SBM model.

• Journal of Korean Institute of Industrial Engineers
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• v.40 no.2
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• pp.172-183
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• 2014

This paper measures and compares the efficiency of national health technology R&D programs focused on translational research program increasing importance using data envelopment analysis (DEA). Three input variables and three output variables are selected for DEA. Inputs are funds, researchers, and project period and outputs are SCI (E) papers, applied and granted patents, and impact factor. This study uses a three-stage approach. In the first stage, output-based DEA model is applied to evaluate the efficiency of decision making unit (DMU). In the second stage, based on efficiency scores of target diseases high-efficiency group and low-efficiency group are classified. And then strategic portfolio matrix of translational research program is composed of four dimensions combining research types. Mann-Whitney U test is then run to compare average efficiency scores among four groups. In the final stage, Tobit regression model is used to estimate factors likely to influence the efficiency. The results are expected to provide policy implications for effectively establishing investment strategy and managing performance of R&D program.

• Journal of the Korea Institute of Military Science and Technology
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• v.21 no.2
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• pp.217-224
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• 2018

The purpose of this study is to evaluate the future potential value of CTE(Critical Technology Element)s that are evaluated to be low in TRA(Technology Readiness Assesment) and to present investment prioritization technologies in defense R&D(Research and Development) based on them. To do this, we used the DEA(Data Envelopment Analysis) method, which is useful in evaluating the efficiency of the organization. Specifically, we suggest a systematic framework to evaluate the future value of CTEs by setting the CTEs derived from the TRA process to DMU(Decision Making Unit)s, the cost and time required to develop each CTE as the input factor of the DEA and the effects of the development of each CTE as the output factor of the DEA respectively. We also conducted an illustrative case study on radar technologies to demonstrate the usefulness of the proposed approach.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• v.1
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• pp.163-170
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• 2006

This paper presents a approach to the measurement of efficiency. Data envelopment analysis(DEA), as it is called, has particular applicability in the service sector. Applying mathematical programming techniques, DEA enables relative efficiency ratings to be derived within a set of analysed units. This paper investigates the efficiency employing DAE-CCR Model and DEA-BCC Model on data for 15 container terminals covering 1998$^{\sim}$2005 in Korea Results of this paper, suggests to some plan for operation strategy in Container terminals.

• Journal of Korean Society for Quality Management
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• v.37 no.4
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• pp.100-110
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• 2009

The customer-driven efficiency evaluation has been in the mainstream of public administration research, since the 1980s. However, there have been relatively fewer efficiency evaluation research in public administration compared to those of public institutions. This paper is to analyze the service efficiency of public sector using Data Envelopment Analysis(DEA). We suggested two stage DEA model to accomplish efficiency evaluation that an operation and performance characteristic of the public institution were reflected and then the number of the government employee and tax expenditure per residents were used as the input elements at the 1st stage and four integrated service dimensions were used as the output elements. At 2nd stage, four integrated service dimensions and citizen's satisfaction were used as the input and output elements respectively. In addition, we suggested PSEI(Public Service Efficiency Index) which showed the efficiency of the public sector using the two stages efficiency result. According to the results for '07, there were no efficient institutions among 15 DMUs and the most efficient public institution was K(0.9150). In case for '08 analysis, there was only one efficient DMU.

• Journal of Information Technology Services
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• v.22 no.1
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• pp.57-74
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• 2023

It has been pointed out as a limitation that the rank of some efficient DMUs(decision making units) cannot be discriminated due to the relativity nature of efficiency measured by DEA(data envelopment analysis), comparing the production structure. Recently, to solve this problem, a DEA-SNA(social network analysis) model that combines SNA techniques with data envelopment analysis has been studied intensively. Several models have been proposed using techniques such as eigenvector centrality, pagerank centrality, and hypertext induced topic selection(HITS) algorithm, but DMUs that cannot be ranked still remain. Moreover, in the process of extracting latent information within the DMU group to build effective network, a problem that violates the basic assumptions of the DEA also arises. This study is meaningful in finding the cause of the limitations by comparing and analyzing the characteristics of the DEA-SNA model proposed so far, and based on this, suggesting the direction and possibility to develop more advanced model. Through the results of this study, it will be enable to further expand the field of research related to DEA.

• Asian Journal of Atmospheric Environment
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• v.5 no.4
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• pp.228-236
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• 2011

Since most Green House Gases (GHGs) and air pollutants are generated from the same sources, it will be cost-effective to develop a GHGs reduction plan in combination with simultaneous removal of air pollutants. However, effects on air pollutants reduction according to implementing any GHG abatement plans have been rarely studied. Reflecting simultaneous removal of air pollutants along with the GHGs emission reduction, this study investigated relative cost effectiveness among GHGs reduction action plans in Busan Metropolitan City. We employed the Data Envelopment Analysis (DEA), a methodology that evaluates relative efficiency of decision-making units (DMUs) producing multiple outputs with multiple inputs, for the investigation. Assigning each GHGs reduction action plan to a DMU, implementation cost of each GHGs reduction action plan to an input, and reduction potential of GHGs and air pollutants by each GHGs reduction action plan to an output, we calculated efficiency scores for each GHGs reduction action plan. When the simultaneous removal of air pollutants with the GHGs reduction were considered, green house supply-insulation improvement and intelligent transportation system (ITS) projects had high efficiency scores for cost-positive action plans. For cost-negative action plans, green start network formation and running, and daily car use control program had high efficiency scores. When only the GHGs reduction was considered, project priority orders based on efficiency scores were somewhat different from those when both the removal of air pollutants and GHGs reduction were considered at the same time. The expected action plan priority difference is attributed to great difference of air pollutants reduction potential according to types of energy sources to be reduced.