• Journal of the Korean Society of Marine Environment & Safety
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• v.12 no.4 s.27
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• pp.233-239
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• 2006

This paper aims to evaluate the operation efficiency of Korean RCC(Rescue Co-ordination Center)/RSC(Rescue Sub-Center) using DEA(Data Envelopment Analysis). for this evaluation, this paper use the quantitative data for DEA analysis with two inputs and four outputs and a qualitative data analysis with the use of expert assessment. The tool for integrating heterogeneous data is fuzzy logic model to decision support system. In this paper, therefore, RCC/RSC evaluates the priority for operation efficiency. The result are found as order as Inchon, Mokpo, Jeju, Donghae, Busan, Pohang, Yosu, Sokcho, Tongyeong, Ulsan, Taean, Gunsan RSC.

• Journal of Korean Society for Quality Management
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• v.37 no.1
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• pp.80-90
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• 2009

Nowadays, there are many companies which employ the SQI measurement to assess service quality. The purpose of this study is to measure the service efficiency for Bank Industry. In this paper, we tried to measure the efficiency of service quality and overall customer satisfaction by using Data Envelopment Analysis(DEA). Rather than using the usual method of converting the Service Quality Index(SQI) into mean value, we applied CCR/BCC models in DEA to service quality efficiency. Also, DEA/PS Model is recommended as appropriate model for evaluating service efficiency by complementing the shortfalls of the weighted value of DEA Model. In this study, six dimensions of service quality were considered as input variables and output variables(overall customer satisfaction, reusing intention, and word of mouth). The result of this study statistically verifies that 5 DMUs are relatively efficient, and intensive activities for service efficiency are needed for 20 sample branches. Managerial implications based on the analysis were suggested.

• Ocean and Polar Research
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• v.28 no.4
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• pp.439-449
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• 2006

This study was aimed at measuring the fishing capacity of Powered Anchovy Drag Net Fisheries (PADNF) in Korea using Peak-to-Peak(PTP) and Data Envelopment Analysis(DEA) methods recommended by FAO. In the analysis, both fishing capacities of total PADNF and individual PADNF vessels were measured with time series data and cross sectional data, respectively. In addition, the results of the DEA measurement were analyzed in order to determine reduction levels of fishing capacity. In case of total PADNF, the results by rn and DEA methods showed a similar rate of capacity utilization (79%), indicating the capacity was not utilized enough. In addition, the sensitivity analysis suggested that the number of vessels should be reduced by 20%, and the gross tonnage and the horse power should be reduced by 20% and 21%, respectively if the current catch is to stay at the 2004 level. The DEA results on individual PADNF vessels indicated the capacity utilization was 75% on average, showing some differences in capacity utilization among vessels (31%-100%). The results of the study would be useful for measuring production efficiency in PADNF. They would also provide good policy information for efficient use of resources and capacity reduction levels, which are useful far vessel buyback programs of coastal and offshore fisheries.

• Journal of Korea Port Economic Association
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• v.32 no.1
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• pp.165-178
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• 2016

Container port nowadays becomes one of the most vital link of the transportation chain, plays an important role in trading with other countries. Therefore, evaluating the operational efficiency of container ports to reflect their status and to reveal their position in this competitive environment is very important for port development. Although there have been lots of methods used to measure efficiency in the past, the DEA (Data Envelopment Analysis) model is still the most commonly applied approach. However, the data used in the model sometimes is complex and uncertain to handle using the basic DEA model. In this paper, we applied an uncertainty theory to create an uncertainty DEA model (UDEA), which can solve the limitation of the traditional one. This study mainly focuses on measuring efficiency of 41 container ports by applying proposed an UDEA model. The results show that among 41 container ports, only six container ports are regarded to have efficient operation through the clustering, meanwhile others have technical and scale inefficiencies. We found out that an UDEA model is better to analysis efficiency than existing DEA model.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.12B
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• pp.815-825
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• 2007

It is necessary to establish a systematic framework where the performance of governmental funding projects can be evaluated just-in-time as well as objectively regarding IT small and medium-sized enterprises and venture business. In this study, a framework is proposed for the performance evaluation using Data Envelopment Analysis (DEA) and a case study is illustrated with an empirical dataset. Especially, in order to enhance the reliability of optimal solutions, a DEA/AR-I revised model is developed by adding Acceptance Region (AR) Type I constraints into the DEA basic model. Based on the procedure and the models, it is considered that an 'efficiency score' can be calculated as a guideline for conducting successive performance evaluation processes fast. As for major governmental funding projects with respect to 'IT SMERP 2010 Plan', performance evaluations are discussed concerning between projects as well as between corporate entities within each project.

• 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.

• Journal of the Korean Operations Research and Management Science Society
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• v.33 no.4
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• pp.83-100
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• 2008

We propose a new aggressive formulation of cross-efficiency in Data Envelopment Analysis(DEA). In the traditional aggressive formulation, the efficiency score of a test DMU is maximized as the first goal while an average of efficiency scores of peer DMUs is minimized as the second goal. The proposed model replaces the second goal with the minimization of the best efficiency score of peer DMUs. We showed the model is a quasi-convex optimization problem, and for a solution method we developed a bisection method whose computational complexity is polynomial-time. We tested the model on 200 randomly generated DEA problems, and compared it with the traditional model in terms of various criteria. The experimental results confirmed the effectiveness and usefulness of the proposed model.

• Journal of Korean Society for Quality Management
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• v.25 no.2
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• pp.169-188
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• 1997

The purpose of this study is concerned with suggesting a new a, pp.oach to evaluating the overall product quality in the sense of the relative efficiency of products, whose quality is measured with 8-dimensional attributes, suggested by Garvin. The attributes included 8 quality measures, that is, performance, features, reliability, conformance, durability, serviceabilit, aesthetics, and perceived quality. This study, also, introduced DEA(Data Envelopment Analysis) as an evaluation tool to tackle the problem of how to measure one product against another when each product can be measured along a number of dimensions, and given that there exists no a priori satisfactory weighting scheme to combine these dimensions into an overall rating for each products. In order to a, pp.y the DEA to evaluating the products, we must define two concepts, such as DMU(Decision Making Units) and input-output relationship. Finally, the suggested method in this study was validated through a case study of the electric jar, and this DEA a, pp.oach can be used in evaluating the other products with multi-attrribute quality.

• The Journal of Fisheries Business Administration
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• v.39 no.3
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• pp.49-65
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• 2008

In Korea, deep-sea fishing industry is faced with pressure of being thrown out of business, because of the upcoming unfavorable business conditions such as the fishing regulation of coastal countries, Korea-US Free Trade Agreement(KORUS FTA), and the other socio-economic changes. Hence, we present an evaluation of future business competitive for the deep-sea fishing industry so that the government can develop a concession plan for the deep-sea fishing industry by utilizing the results of this study. In efficiency analysis of deep-sea fishing industry, the decision maker may have two problems: (1) how to deal with multiple inputs and outputs of deep-sea fishing industry and (2) how to assign the weights on different inputs and outputs, In this paper, we proposed to use Data Envelopment Analysis (DEA) to estimate efficiency of deep-sea fishing industry with multiple inputs and outputs. In the DEA, The direct impact of KORUS FTA, fishing regulation of coastal countries, fishing charges, and competitive fishing conditions were used as input parameters while the profitability and secured fishing quarters, as outputs. The results of DEA-BCC model indicate that 6 out of 12 DUMs have better efficiency under variable return to scale assumption.

• 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.