• Proceedings of KOSOMES biannual meeting
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• 2006.05a
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• pp.15-20
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• 2006

In this study, we had investigated several input factors and output factors, to maintain safety management, of domestic shipping companies, and then had analyzed the efficiency of performance of performance about each shipping companies' safety management system from 1998 year to 2004 year using DEA method As the result of analysis, the annual mean efficiency of total companies tended downward every year. Analysis was that the cause was increase of the cost of repairing ship, the cost of ship's stores and idle day of ship.

• Korea Journal of Hospital Management
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• v.2 no.1
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• pp.22-47
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• 1997

This paper evaluated the relative efficiency of 33 provincial medical centers using Data Envelopment Analysis(DEA) and compared the DEA efficiency results with those of the current method conducted by the management evaluation team. DEA Was selected as an alternative efficiency evaluation method since it could handle multiple inputs and multiple outputs simultaneously and identify the sources of inefficiency. To analyze the sensitivity of productivity values to the variable sets, four different sets of input and output variables were identified. Results showed that most of the medical centers are operating far away from the efficiency frontier supporting the previous results. Some centers showed 100% efficiency regardless of the selected variable sets. DEA results are compared with current management evaluation results. Some inconsistencies were found for some DMUs between the results of two methods showing the existence of methodology bias. DEA results and ratio analyses results mostly agree for 1992 data.

• IE interfaces
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• v.22 no.1
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• pp.44-55
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• 2009

We propose a method for selection of input-output factors in DEA. It is designed to select better combinations of input-output factors that are well suited for evaluating substantial performance of DMUs. Several selected DEA models with different input-output factors combinations are evaluated, and the relationship between the computed efficiency scores and a single performance criterion of DMUs is investigated using decision tree. Based on the results of decision tree analysis, a relatively better DEA model can be chosen, which is expected to well represent the true performance of DMUs. We illustrate the effectiveness of the proposed method by applying it to the efficiency evaluation of 101 listed companies in steel and metal industry.

• Journal of the Korean Operations Research and Management Science Society
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• v.23 no.3
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• pp.75-90
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• 1998

The improper use of input and output factors in DEA has a critical and negative impact on the efficiency measurement and the discernment of decision making units(DMUs) : hence the proper selection Process of the factors should precede the actual applications of DEA. In this paper, we propose a new approach to selecting proper factors based on Tofallis' partial efficiency evaluation method(1996). With the approach, the factors aye clustered by measuring their respective partial efficiencies and analyzing the rank correlations of them. The method and procedure we propose in this paper are then applied to measure the efficiencies of the public libraries in Seoul District area, and the results show that the proposed approach can provide meaningful information to improve discernment of the DMUs while using less number of input factors (and less information). The proposed method can be effectively used in the situation where the number of the DMUs to be considered is relatively small compared to the number of available input and output factors, which usually lessens the power to identify the inefficient units in DEA.

• Knowledge Management Research
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• v.13 no.5
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• pp.43-64
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• 2012

Emerging technologies have significant implications in establishing competitive advantages and are characterized by continuous rapid development. Efficient benchmarking is more and more important in the development of emerging technologies. Similar input level and importance are two necessary criteria need to be considered for emerging technology's benchmarking. In this study, we proposed a sequential use of self-organizing map(SOM), data envelopment analysis(DEA) and analytical hierarchy process(AHP) method for the stepwise benchmarking of emerging technology. The proposed method uses two-level SOM to cluster the emerging technologies with similar required input levels together, then, in each cluster, uses DEA-BCC model to evaluate the efficiencies of the emerging technologies and do tier analysis to form tiers. On each tier, AHP rating method is used to calculate each emerging technology's importance priority. The optimal benchmarking path of each cluster is established by connecting the emerging technologies with the highest importance priority. In order to validate the proposed method, we apply it to a case of biotechnology. The result shows the proposed method can overcome difficulties in benchmarking, select suitable benchmarking targets and make the benchmarking process more efficient and reasonable.

• Journal of Korean Society for Quality Management
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• v.47 no.1
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• pp.33-46
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• 2019

Purpose: This study proposed a DEA (Data Envelopment Analysis)-based stepwise benchmarking target selection for inefficient DMU (Decision Making Unit) to improve its efficiency gradually to reach most efficient frontier considering resource (DEA inputs and outputs) improvement preferences. Methods: The proposed method proceeded in two steps. First step evaluates efficiency of DMUs by using DEA, and an evaluated DMU selects benchmarking targets of HCU (Hypothesis Composit Unit) or RU (Real Unit) considering resource improvement preferences. Second step selects stepwise benchmarking targets of the inefficient DMU. To achieve this, this study developed a new DEA model, which can select a benchmarking target of an inefficient DMU in considering inputs or outputs improvement preference, and suggested an algorithm, which can select stepwise benchmarking targets of the inefficient DMU. Results: The proposed method was applied to 34 international ports for validation. In efficiency evaluation, five ports was evaluated as most efficient port, and the remaining 29 ports was evaluated as relative inefficient port. When port 34 was supposed as evaluated DMU, its can select its four stepwise benchmarking targets in assigning the preference weight to inputs (berth length, total area of pier, CFS, number of loading machine) as (0.82, 1.00, 0.41, 0.00). Conclusion: For the validation of the proposed method, it applied to the 34 major ports around the world and selected stepwise benchmarking targets for an inefficient port to improve its efficiency gradually. We can say that the proposed method enables for inefficient DMU to establish more effective and practical benchmarking strategy than the conventional DEA because it considers the resource (inputs or outputs) improvement preference in selecting benchmarking targets gradually.

• Journal of Korea Port Economic Association
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• v.25 no.2
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• pp.57-72
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• 2009

The purpose of this paper is to show the empirical measurement way of operation risk evaluation in domestic seaports for overcoming the limitations which the traditional DEA method has by using 13 Korean ports in 2003 for 4 inputs(birthing capacity, cargo handling capacity, number of coastal guard vessel, number o f coastal special guard vessel ) and 5 outputs(Export and Import Quantity, Number of Ship Calls, number of coastal accident, number of coastal crime, number of coastal pollution). Because traditional DEA method has produced the limited set of information, negative DEA mixed with tier, stratification and layering methods should be adopted. The goal of negative DEA is to set up DEA models that will place the poor operating ports on or close to the empirical frontier. The core empirical results of this paper are as follows. First, Donghae ports should benchmark the operation way of Yeasu, Busan, Woolsan ports in terms of the middle and longterm base. Second, 5 ports(ports of Taean, Yeasu, Tongyoung, Busan, Sokcho) which were revealed as the poor operating ports in Negative DEA analysis should benchmark Incheon, Woolsan, Pohan, and Donhae ports. The policy implication to the Korean seaports and planners is that Korean seaports should introduce the new methods like Negative DEA of this paper for predicting the poor operating in the ports.

• Korean Journal of Occupational Health Nursing
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• v.11 no.2
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• pp.108-120
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• 2002

This study analyzed the managerial efficiency of 11 organizations, the branch centers of a occupational health service organization in Korea, using the Data Envelopment Analysis (DEA) method. The DEA is a good method for evaluating health services since it can handle multiple inputs and outputs simultaneously, and also identify the sources and amount of inefficiency. The author approached this study using two efficient models: the monetary value model and the real value model. The DEA method based on the monetary value model included cost factors, while the real value model excluded cost factors. The input variables used were manpower of physicians, medical technicians, nurses, industrial hygienists and administrators; labor, maintenance, and material expenses. The output variables used were the number of medical examinations, workplace evaluations, group health management services and income from each service. The major results were as follows: First, in the monetary value model, 6 out of 11 organizations (54.6%) showed an efficiency score of 1.0, which means that they have been operating in very efficient ways. However, 5 organizations (46.4%) showed themselves to be relatively inefficient. Second, in the real value model, 7 out of 11 organizations (63.4%) showed an efficiency score of 1.0, which means they have been operating efficiently, while 4 organizations (46.4%) showed themselves to be relatively inefficient. Third, the reliability of DEA method were analyzed by comparing the results of the monetary value model and real value model. The results of 8 out of 11 organizations were same in terms of being efficient or not. Thus, the DEA could be a valid application method for occupational health service organizations. Fourth, the organizations that displayed common inefficiency in both the monetary value model and in the real value model 3, 9, and 10, were also considered to be managed inefficiency from expertise opinion. In summary, this study evaluated the efficiency of occupational health service organizations applying the DEA method with different variables, and found that the results of analysis could be valid in terms of both modeling and expert sense. In the future, the DEA method will be used as a useful tool to identify and evaluate the efficiency of occupational health service organizations through more applications and refinements.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.28 no.2
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• pp.18-26
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• 2005

The balanced scorecard(BSC) overcomes the limit of traditional financial statement that focuses on only financial performance. BSC is widely used in government and industry because of the clear representation of the relationship and logic between the key performance indicators(KPI) of 4 perspectives - financial, customer, internal process, and loaming and growth. However, traditional BSC does not consider evaluating the difference between the results measured by BSC. By using relatively small number of inputs and outputs In comparing decision-making units, data envelopment analysis(DEA) can aggregate multiple performance measures. In this research, we propose a methodology named CDB(Combined DEA and BSC) to evaluate the performance of organization considering financial and non-financial perspectives. CDB uses KPI of cause-and-effect relationship on BSC as inputs and outputs of DEA method. In addition, this research proposes a method of converting the KPI of BSC to the input and output variables of DEA, and enhancing discrimination power using the limit number of variables. We illustrate the methodology by giving an example of evaluating aquisition-unit efficiency in a supply chain.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.5B
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• pp.364-378
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• 2008

Data Envelopment Analysis(DEA) models can be used for performance evaluation on governmental funding projects for IT small and medium-sized enterprises associated with multiple-outputs/multiple-inputs. In order to enhance the accuracy of DEA efficiency scores, DEA models with exogenously fixed variables are required where the corporate competency is taken into account. Additionally, it is necessary to use multiple DEA basic as well as extended models so as to relax the restriction on the performance evaluation to relying on a single DEA model. In this study; 1)a DEA data structure is designed including exogenously fixed variables representing corporate asset, revenue and the number of employees at the point in time that the governmental funding project concerned is initiated; 2)DEA basic as well as extended models are established according to the DEA data structure presented abovementioned; and 3)a case study is illustrated with an empirical testbed dataset. As for the DEA basic models, CCR, BCC, Super-efficiency model are adopted. The DEA extended models are developed based on the models associated with noncontrollable and nondiscretionary variables. In the case study, it is explained a comparison of DEA models and also major numerical outcomes such as efficiency scores, ranks derived from each DEA model are integrated using Analytic Hierarchy Process(AHP) weights. Performance significance with DEA efficiency scores between technical categories are tested based not only on parametric but also nonparametric single-factor analysis of variance method.