• Journal of Korea Port Economic Association
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• v.31 no.3
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• pp.155-166
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• 2015

This study selected container terminals of Gwangyang and Busan Ports to evaluate the influence of efficient container terminals. For the study, after data envelopment analysis (DEA) using the CCR and BCC models, the decision-making unit (DMU) system was used to define nodes; and with the use of a reference group in DEA (BCC model) and a lambda value, this study created a social network and analyzed the influences of efficient DMUs through a centrality analysis of eigenvectors. The results are presented as follows: First, as a result of the DEA, CCR efficiencies in PNC, HJNC, and HPNT container terminals of Busan Port were 1 and BCC efficiencies at Singamman Terminal, Wooam Terminal, PNC, HJNC, HPNT, and BNCT container terminals of Busan Port were 1. Second, as a result of undertaking social network analysis (SNA), according to an eigenvector centrality analysis, HJNC Terminal was referred to the most (influence score of 0.515), which indicates that it is the most influential as a container terminal. The influence of PNC Terminal was 0.512, while that of Wooam Terminal was 0.379. CJ Korea Express in Gwangyang Port was ranked fourth in influence, but its influence score of 0.256 indicates that it was the most influential of the container terminals at Gwangyang Port.

• Journal of Navigation and Port Research
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• v.34 no.7
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• pp.577-585
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• 2010

This paper analyzes the efficiency of Korean Ship Component Part Manufacturer firms using DEA model. We evaluated the CCR, BCC efficiency and RTS of 30 Korea Ship Component Part Manufacturer firms. We also suggested the Korean Ship Component Part Manufacturer firms that can be benchmarked based on analyzed information. The result showed five enterprises whose values of CCR efficiency are 1, and eleven enterprises whose values of BCC efficiency are 1. RTS indicated IRS of 1 firms, DRS of 24 firms and CRS of 5 firms.

• Korea Journal of Hospital Management
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• v.15 no.1
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• pp.27-48
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• 2010

The purpose of this paper is to analyze the efficiency change and its determinants of the regional public hospitals. We utilize 34 regional public hospital's panel data for 6 years from 2003 to 2008. We use DEA(Data Envelopment Analysis)-CCR, BCC model, DEA/Window model, and DEA Profiling. The empirical results show the following findings. First, technical efficiency shows that approximately 3.6% of inefficiency exists on the regional public hospitals and it reveals that the cause for technical inefficiency is due to scale inefficiency. Second, DEA/Window results show that the stable dissimilarity by standard deviation, LDP of CCR. Third, the results of partial efficiency by DEA Profiling show that increase efficiency depends on the number of beds, doctors, and nurses.

• The Journal of the Korea Contents Association
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• v.8 no.4
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• pp.173-182
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• 2008

It is hard environment to get a profit without active invest due to the low interest. In this kind of environment, however, it is also difficult to find good company directly. So private investors is hard to succeed in comprehensive financial environment. Analyzing efficiency is necessary to enhance the competitive power of fund companies. This paper analyze the efficiency of fund company using DEA models. We evaluate the CCR and BCC efficiency and RTS(return to scale) of 33 Korean fund companies. We also suggest the fund company which can be benchmarked based on analyzed information.

• The Journal of the Korea Contents Association
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• v.7 no.6
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• pp.195-205
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• 2007

The steel industry plays an important role in the entire Korean Economy. However, little empirical research has analyzed the efficiency of steel companies. The purpose of this paper is to measure and analyze their efficiency using DEA models. We evaluate the CCR and BCC efficiency and the return to scale of 28 Korean steel companies. We also provide their envelopment map and the projection, which are valuable information for inefficient companies to find benchmarking companies and to improve their efficiency.

• 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 Navigation and Port Research
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• v.46 no.2
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• pp.110-120
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• 2022

Spain is Europe's second-largest country with total throughput reaching 16.7 million twenty-foot equivalent units (TEU) by 2020. The purpose of this study was to measure and compare the efficiency of 17 container terminals. As a study method, the DEA-CCR model, undesirable variable, and Malmquist Index (MI) were used for data envelopment analysis (DEA). The study results are as follow: (1) DEA-CCR is used to evaluate basic efficiency. The most efficient terminals are decision-making units DMU 1 (APM Terminals (Algeciras Port)), DMU 2 (Total Terminal International Algeciras (Algeciras Port)) and DMU 5 (Barcelona Europe South Terminal (Barcelona Port)). (2) Undesirable DEA was conducted to suggest inefficiency from the undesirable output. Overall, the efficiency scores were reduced. However, DMU 1, DMU 2, and DMU 5 maintained efficiency scores regardless of the finish factor. (3) Malmquist Index was used to observe technology and efficiency changes dynamically. The changes in TCI affected Spanish container terminals more than the Technical Efficiency Change Index (TECI) in 2018-2019. However, in 2019-2020, the TECI was 2.706, higher than the TCI value, indicating that the change in TECI had more influence on the increase in productivity. This study offers a broader understanding of Spanish container terminals.

• 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.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.06a
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• pp.517-521
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• 1998

DEA(data envelopment analysis) is a non-parametric technique for measuring and evaluating the relative efficiencies of a set of entities with common crisp inputs and outputs. In fact, in a real evaluation problem input and output data of entities often flucturate. These fluctuating data can be represented as linguistic variables characterized by fuzzy numbers. Based on a fundamental CCR model, a fuzzy DEA model is proposed to deal with fuzzy input and output data, Furthermore, a model that extends a fuzzy DEA to a more general case is also proposed with considering the relation between DEA and RA (regression analysis) . the crisp efficiency in CCR modelis extended to an L-R fuzzy number in fuzzy DEA problems to reflect some uncertainty in real evaluation problems.

• Journal of Digital Convergence
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• v.10 no.9
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• pp.159-164
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• 2012

Although the display industry plays an important role in the entire Korean economy, few empirical research has analyzed the efficiency of display companies. The purpose of this paper is to measure and analyze efficiency of korean listed display firms using DEA(Data Envelopment Analysis) models. We evaluate the CCR and BCC efficiency in DEA models and the return to scale of the Korean listed display companies. The benchmarking companies and efficiency value for the display companies with inefficiency are also provided to improve their efficiency. We analyzed the 44 listed companies consisted of 7 listed on KOSPI and 37 listed on KOSDAQ at the end of 2010. The analysis results show six companies whose values of CCR are 1, and fourteen firms whose values of BCC efficiency are 1. In additions, the six companies have the scalability efficiency. Eventually the efficiency analysis can provide the valuable information for inefficient companies to find benchmarking companies and to improve their efficiency.