• Journal of the Korea Society for Simulation
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• v.13 no.4
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• pp.17-29
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• 2004

The focus of this study is to represent a methodology of analysis for integrated logistic system by means of the Evolution Strategies and Data Envelopment Analysis(DEA). The integrated logistic system is composed of AS/RS (Automated Storages and Retrieval System), AGVs(Automated Guided Vehicle System) and Conveyor System. We design the simulation alternatives with choosing the qualitative critical factors for the each subsystem. Evolution Strategies is used to optimize the quantitative critical factors and responses of each alternative. DEA is applied to measure the efficiency of the alternatives in order to select the optimal operation efficiency scheme. The method of analysis which combines Evolution Strategies with DEA can be used to analyze the qualitative and quantitative critical factors in the integrated logistic systems.

• 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.

• 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.

• The Journal of the Korea Contents Association
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• v.10 no.12
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• pp.290-299
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• 2010

This study aims to evaluate the efficiency of superior appraisal corporations using DEA(Data Envelopment Analysis). DEA is known as a method for evaluating relative efficiency of organizations with multiple inputs and outputs. We used CCR-O and BCC-O DEA models to evaluate relative efficiency of superior appraisal corporations. Input variable is number of appraisers, output variables are total sales and net income. Total of 13 appraisal corporations in Korea were selected for this study, and the data were collected from financial reports for 2008 fiscal year. The result of this study is summarized as follows. First, the average of superior appraisal corporation's technical efficiency score is about 88.3% by applying CCR-O model. Second, the average of superior appraisal corporation's pure technical efficiency score is about 90% and scale efficiency score is about 98.2% by applying BCC-O model. According to the result of DEA, the cause of inefficiency is pure technical efficiency.

• Journal of Korean Institute of Industrial Engineers
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• v.40 no.6
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• pp.628-641
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• 2014

Stepwise efficiency improvement in data envelopment analysis (DEA)-based benchmarking is a realistic and effective method by which inefficient decision making units (DMUs) can choose benchmarks in a stepwise manner and, thereby, effect gradual performance improvement. Most of the previous research relevant to stepwise efficiency improvement has focused primarily on how to stratify DMUs into multiple layers and how to select immediate benchmark targets in leading levels for lagging-level DMUs. It can be said that the sequence of benchmark targets was constructed in a myopic way, which can limit its effectiveness. To address this issue, this paper proposes an optimization approach to the construction of a sequence of benchmarks in DEA-based benchmarking, wherein two optimization criteria are employed : similarity of input-output use patterns, and proximity of input-output use levels between DMUs. To illustrate the proposed method, we applied it to the benchmarking of 23 national universities in South Korea.

• Journal of Digital Convergence
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• v.11 no.10
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• pp.255-262
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• 2013

Data envelopment analysis(DEA) is a linear programming procedure designed to evaluate the relative efficiency of a set of peer entities called decision making units which use the same inputs to produce the same outputs. It has been widely employed in a variety of disciplines as an efficiency or performance measurement tool for comparing a set of entities such as firms, banks, hospitals, nations and organizations. The method, however, cant's make the priority of their performance when many units have efficiency score of unity or 100 percent. In this paper, we propose a new approach which combine qualitative method(graphical approach using network analysis) and quantitative method(super-efficient analysis using DEA), and present the results of an empirical analysis using the data of the Korean professional baseball players. As a result, there were 12 DMU that priority is hardly realized through DEA. However, this problem could be solved with super-efficiency analyzing. Also, more in-depth interpretation was able through integrating results of dendrogram and super-efficiency analyzing and prospecting it in qualitative, quantitative ways.

• Journal of Navigation and Port Research
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• v.32 no.1
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• pp.73-80
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• 2008

The purpose of this paper is to measure the productive efficiency and competitive strength of Regional Maritime Affairs and Fisheries Office using the DEA. Using EMS(Efficiency Measurement System) which is LP solver, quantifies in one way or another a "distance" to the efficient frontier of the technology. An input oriented measure quantifies the input reduction which is necessary to become efficient holding the output constant. Symmetrically, an output oriented measure quantifies the necessary to become efficient holding the inputs constant. A non-oriented measure quantifies necessary improvements when both inputs and outputs can be improved simultaneously. According to the analysis result of the DEA method, inefficient Regional Maritime Affairs and Fisheries Office should recommend benchmarking reference Regional Maritime Affairs and Fisheries Office in order to enhance the productive efficiency of port administration and a public institution. Besides data on productive efficiency serves as a tool for policy-makers at all levels of activity and is essential for improving the efficiency with which the various systems operate.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2006.11a
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• pp.187-190
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• 2006

We proposed a new real estate price appra isal model that can appreciate the efficiencies of each criteria that would affect the price. The proposed Real Estate Price Appraisal Model is developed by the DEA-AR model which enhances the DEA-CCR model. We used the unit-cost per criteria method to set the assurance region of each weights of the DEA-AR model. In order to estimate the unit cost of major criteria effecting the price of real estate, we used the Goal Programming so that the price of real estate reaches the actual price being traded in. We expect that this approach could be helpful to make an objective real estate price appraisal.

• 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.

• Journal of the Korea Safety Management & Science
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• v.15 no.1
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• pp.249-258
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• 2013

Data Envelopment Analysis (DEA) is a useful tool to analyze the relative efficiency of decision making units (DMU) characterized by multiple inputs and multiple outputs. This method has been popularly used as an analytical tool to suggest some strategic improvement. To do this, the results of DEA provide decision makers with a single efficiency score, efficient frontier, return to scale, benchmarking decision making units, etc. The purpose of this paper is to evaluate research performance of 38 universities and provide an inefficient university with the way of organizational changes to be an efficient university by using DEA. Various input and output variables are used to identify technical and scale inefficiency. Additionally, we analyze how an inefficient DMU could be changed an efficient DMU based on a case university. This result will give an insight of constructive directions for increasing of research performance to university decision makers.