• Journal of the Korea Academia-Industrial cooperation Society
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• v.10 no.6
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• pp.1304-1316
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• 2009

This study is for the pursuit of the basic application of the efficient conversion factor in the fee contract. This aims to investigate the effects of DEA efficiency index and conversion factors to identify and group the 60 hospitals with intern and residents education. To achieve the aims, AHP was used to select the inuput and output variables for DEA. It was found that the more inefficient in the technical and scale side, the higher the conversion factors were. Conversion factor and DEA efficiency index can be used very effectively to group and discriminant hospitals into a specialized general hospital and a general hospital. Even if the variables used to calculate DEA efficiency are applied to discriminant analysis, The conversion factor and DEA efficiency index have a significant power to make a function modeling. So, if we can make a more conclusive proof based on the large number samples, We can imagine to introduce a efficiency concept in the insurance fee contracts about a conversion factor in Korea Health Insurance System.

• Journal of Korean Institute of Industrial Engineers
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• v.32 no.1
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• pp.18-28
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• 2006

Some issues which should be considered in an R&D project selection problem are as follows: First, quantitative analysis on the efficiencies of R&D projects is required to guarantee objective validity in the evaluation of the projects. For this reason, the methodology for selecting R&D projects should be based on mathematical models that perform quantitative analysis. Second, in general there are ordinal factors like Likert-scale in the data for evaluating R&D projects. Previous researches, however, couldn't suggest explicit methods incorporating these ordinal factors into models. Third, for the R&D project selection problems with limited resources like budget, it is necessary to decide the perfect ranking of the all projects. This paper develops a mathematical model that can be applicable to the problems of selecting R&D projects with the previous features. In this paper, we improve the original DEA model for evaluating efficiency to incorporate ordinal factors and suggest a new model which can decide the perfect ranking of all projects by merging the improved DEA model and AHP method. Furthermore a web-based R&D project selection system using the DEA/AHP model suggested in this paper is developed and illustrated.

• The Journal of the Korea Contents Association
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• v.11 no.6
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• pp.302-310
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• 2011

Recently, many construction firms fall on hard times because construction business continues to stagnate. In this paper, we analyze the efficiency of the listed construction firms using a combined AHP and DEA model. In order to determine the input and output factors of DEA, the AHP model is applied to evaluate the importance of input and output factors. The benchmarking companies and efficiency value for the construction firms with inefficiency are also provided to improve the their efficiency. We analyzed the 57 listed companies consisted of 36 listed on KOSPI and 21 listed on KOSDAQ at the end of 2009. The analysis results show that eleven companies whose values of CCR are 1, and fourteen enterprises whose values of BCC efficiency are 1. In additions, the eleven firms have the scalability efficiency. Finally, we test the correlation between efficiency and the stock price and the correlation coefficient of efficiency group is 0.7 in the CCR model.

• 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 Library and Information Science Society
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• v.40 no.2
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• pp.491-514
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• 2009

The supply of public libraries in Korea has been rapidly improving because of the recent increase for cultural demands and revitalization of the local culture. This paper aims to analyze the efficiency about 565 public libraries using Clustering DEA/AHP(CDA) model. This model is employed the efficiency analysis in order to incorporate project irreversibility and division due to the limit of resources spending. The results shows that the public libraries are divided into three groups which are large size libraries(Group 1), middle size libraries(Group 2) and small size libraries(Group 3). Their average efficiency was found as 0.89, 0.72 and 0.60 each.

• IE interfaces
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• v.21 no.3
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• pp.302-311
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• 2008

Efficiency evaluation methods of manufacturing processes have relied on absolute measures such as defective rate and throughput per person, ignoring various process characteristics. To overcome the limitation, we propose an evaluation model which reflects characteristics of each process. It is composed of three measures : utilization, performance, and improvement. The suggested model utilizes a combination of DEA and AHP methods. The proposed method has been applied to efficiency evaluation of cellular phone case manufacturing processes.

• Journal of Korea Port Economic Association
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• v.32 no.4
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• pp.73-87
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• 2016

The purpose of this study is to investigate the empirical results of Analytic Hierarchy Process/Data Envelopment Analysis-Assurance Region(AHP/DEA-AR) by using multiple regression analysis during the period of 2009-2012 with 5 inputs (number of gantry cranes, number of berth, berth length, terminal yard, and mean depth) and 2 outputs (container TEU, and number of direct calling shipping companies). Assurance Region(AR) is the most important tool to measure the efficiency of seaports, because individual seaports are characterized in terms of inputs and outputs. Traditional AHP and multiple regression analysis techniques have been used for measuring the AR. However, few previous studies exist in the field of seaport efficiency measurement. The main empirical results of this study are as follows. First, the efficiency ranking comparison between the two models (AHP/DEA-AR and multiple regression) using the Wilcoxon signed-rank test and Mann-Whitney signed-rank sum test were matched with the average level of 84.5 % and 96.3% respectively. When data for four years are used, the ratios of the significant probability are decreased to 61.4% and 92.5%. The policy implication of this study is that the policy planners of Korean port should introduce AHP/DEA-AR and multiple regression analysis when they measure the seaport efficiency and consider the port investment for enhancing the efficiency of inputs and outputs. The next study will deal with the subjects introducing the Fuzzy method, non-radial DEA, and the mixed analysis between AHP/DEA-AR and multiple regression analysis.

• Journal of Digital Convergence
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• v.19 no.2
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• pp.117-133
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• 2021

This study aimed to identify its research trends using social network analysis(SNA). The results of the analysis showed that, for degree centrality, Busan Port(0.223) was the keyword that had the highest centrality, followed by DEA(0.060), AHP(0.056), and container terminal and port competitiveness(0.049). Busan Port(0.245) also had the highest betweenness centrality, followed by DEA(0.048), container terminal(0.044), AHP(0.039), and Busan New Port(0.032). The trend analysis inferred that efficiency analysis(DEA), strategy selection, and competition analysis(AHP) were the keywords with a high centrality for Busan Port to gain a competitive edge with global ports. However, research on the Fourth Industrial Revolution, which is emerging as a key issue, was insufficient. In the future, research using social data, such as mass media and social networks, is necessary.

• Journal of the Korean Operations Research and Management Science Society
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• v.34 no.3
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• pp.105-124
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• 2009

Data Envelopment Analysis (DEA) is a methodology of computing the relative efficiency of each decision making unit (DMU) by comparing it with other DMUs having similar input and output structure. In this paper, we compare the efficiency of Korean rail transit corporations using DEA. To do this, we design a DEA-AR/AHP model, and evaluate efficiency by comparing the subway operating agencies of six big cities. The analysis reveals that Seoul Metro and Seoul city railroad construction turn out to be the most efficient groups. The result of this research can provide helpful information for effective management in a domestic subway operating agency.

• Industrial Engineering and Management Systems
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• v.15 no.1
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• pp.49-62
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• 2016

In this paper, we propose an integrated data envelopment analysis (DEA) and analytic hierarchy process (AHP) methodology in which the information about the hierarchical structures of input-output data can be reflected in the performance assessment of decision making units (DMUs). Firstly, this can be implemented by extending a traditional DEA model to a three-level DEA model. Secondly, weight bounds, using AHP, can be incorporated in the three-level DEA model. Finally, the effects of incorporating weight bounds can be analyzed by developing a parametric distance model. Increasing the value of a parameter in a domain of efficiency loss, we explore the various systems of weights. This may lead to various ranking positions for each DMU in comparison to the other DMUs. An illustrative example of road safety performance for a set of 19 European countries highlights the usefulness of the proposed approach.