• The Journal of Fisheries Business Administration
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• v.46 no.2
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• pp.111-125
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• 2015

This study is to analyze the efficiency of Korean sea food manufacturing using Data Envelopment Analysis. Firstly, based on an output oriented traditional CCR, BCC model, the study estimated the efficiency scores. The average estimates of technical, pure technical, and scale efficiency turned out 0.6517, 0.7184, 0.9074 respectively, which are separated for 50 marine corporations. The 10 DMUs were efficient under CCR model while the 17 DMUs under BCC model. Also, the study suggested that the operating profit of the two output factors should be more increased relatively and averagely from the viewpoint of efficiency improvement. Secondly, super efficiency scores are estimated under super efficiency and SBM model. As a result, it came to be possible to distinguish and rank the efficiency of the efficient DMUs. The highest score was 4.2975 under Super-CCR, was 2.4947 under Super-BCC, was 2.7160 under SBM-Super-CCR, and was 1.5319 under SBM-Super-BCC model. The average estimates of super efficiency were 0.76 and 0.82 under Super-CCR and Super-BCC model respectively, and were 0.61 and 0.67 under SBM-Super-CCR and SBM-Super-BCC model. Finally, the study conducted a rank-sum test, Wilcoxon-Mann-Whitney test, to find a statistical significance of heterogeneity existing in efficiencies among the sample corporations. The result showed that there was a significant difference in average efficiency between Dried, Salted product manufacturing and Frozen product manufacturing under BCC-Super efficiency model at 10% level of significance. Furthermore, TOBIT model was applied to find out the potential factors that might influence the efficiency, Wilcoxonand the results showed debt and sales cost influenced all of the technical, pure technical, and scale efficiency, while net profit influenced only the technical efficiency.

• Journal of Navigation and Port Research
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• v.39 no.6
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• pp.507-514
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• 2015

The purpose of this study is to analyze the efficiency of resident companies in port hinterland logistics that are currently operating. The subjects of the efficiency analysis include 13 logistics hinterland resident companies in Incheon Port and Busan Port. Investment amounts, area, and number of employees were selected as input variables, and volume and sales amounts were selected as output variables. As for the efficiency analysis methods, traditional CCR and BCC models were applied. To overcome the limits of these models, a super-efficiency model and a Super-SBM model were also applied. According to the super-efficiency model analysis, the mean was 0.777 and the standard deviation was 0.54, indicating an approximate 33% difference of efficiency among the companies. According to the Super-SBM model analysis, the mean was 0.649 and the standard deviation was 0.489. When considering residuals in the super-efficiency model, the average efficiency score among the companies decreased by approximately 13%. This means that the efficiency score decrease of DMU, where non-radial residuals exist at about 18% on average. Examining the inefficiency of the inputs, the inefficiency of the number of employees turned out to be largest at -45%, compared to 'area' at -33% and 'investment amount' at -33%.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.8
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• pp.130-139
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• 2020

The defense industry is a future-oriented industry, in which high-tech technologies are concentrated. In addition, it is a key industry for maintaining national security, and the R&D of the defense industry is very important. With the introduction of a competitive system by defense industry companies, the necessity of improving the efficiency and productivity of defense industry companies is emerging. In this study, the efficiency of the defense industry was measured using the CCR and BCC model. In addition, super efficiency was derived using the Super-SBM model. For this study, the 2019 defense industry management analysis data of the Korea Defense Industry Association (KDIA) was used, and the analysis was performed by setting the number of researchers and investments of domestic defense industry companies as the input variables and sales as the output variables. Through this study, it is expected that the defense industry's R&D efficiency will be grasped, which will help establish a policy for fostering the defense industry in the future.

• The Journal of Fisheries Business Administration
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• v.42 no.2
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• pp.15-30
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• 2011

This study is designed to measure the relative efficiency of regional fishery cooperatives based on Data Envelopment Analysis(DEA) methods. Selecting 40 regional fishery cooperatives in Busan as Decision Making Units (DMUs), the study uses their panel data from 2007 to 2008 to rank the relative efficiency of the DMUs. First, the efficiency score of the DMUs are calculated using CCR, SBM, and super-SMB model. Within the model, input variables are the number of employees and area of fishery cooperatives. Output variables are the amount of deposit money, loan and profit. Based on the efficiency scores calculated from super-SMB model, the efficiency ranking of the DMUs is determined. Second, the differences in average efficiency calculated from the three DEA models are tested using a pair-wise mean comparison test. The results based on the efficiency scores evaluated from super-SMB model show that seven out of the forty DMUs are efficient; among the efficient DMUs, the DMUs that can be benchmarked for inefficient DMUs through the frequency analysis of reference set being identified. Third, the differences in average efficiency of the three DEA models between 2007 and 2008 are tested using pair-wise mean comparison test and the study estimates the efficiency change of the DMUs between 2007 and 2008 using Malmquist productivity index(MPI). Finally, the paper suggests an improved composite DMU superior to the inefficient DMUs evaluated by Super-SBM model.

• The Journal of the Korea Contents Association
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• v.12 no.7
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• pp.284-294
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• 2012

In the study, we estimate efficiencies using CCR model of DEA, Super efficiency(AP) model, and super-SBM model with the data of 32 regional public hospitals in Korea from 205 to 2009. With Wilcoxon-Mann-Whitney statistics, we analyze efficiency differences for environmental factors(regions, type of hospital, type of operations, type of education training, relative importance of madicaids) among regional public hospitals. The results can be summarized as follows. Firstly, technical inefficiencies of regional public hospitals range from 15% to 17% in CCR model, 13% to 15% in AP model, 7% to 12.6% in SuperSBM model. Second, we confirm that environmental factors of hospitals cause different inefficiencies among them. The implication of this study is that policy and institutional change may need to improve the efficiencies along with internal managerial reform.

• Industry Promotion Research
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• v.9 no.1
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• pp.259-273
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• 2024

In this study, 31 provincial-level administrative regions in China from 2011 to 2021 were taken as the research objects, and the super-SBM model was used to measure the regional eco-efficiency with capital, labor, land and resource input as input variables, GDP and green coverage as the desirable outputs, and wastewater, waste gas and solid waste emissions as the undesired outputs. Tobit regression was used to analyze the effects of external environmental factors on eco-efficiency. The results showed that the average level of eco-efficiency in China was low, and the eco-efficiency in the eastern region was higher than that in other regions, and there were great differences in the western, northeast and central regions.

• Journal of Korean Society for Quality Management
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• v.35 no.3
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• pp.21-36
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• 2007

This article is to analyze the service efficiency of public sector using Data Envelopment Analysis(DEA). We tried to measure the public service quality and overall satisfaction by using several DEA models, degree of combination and top2box which is a little bit different methodology from traditional ones. We used CCR, Super-efficiency and Slack based measure(SBM) model in DEA to measure public service efficiency of the 16 public institutions(7 City Halls and 9 Provincial offices). Since the traditional method based on the measurement model(CCR, BCC) has the fundamental problems without taking account of the existence of slacks inputs and outputs in several efficient units, we suggest to measure the exact amount of efficiency and inefficiency of the public sector and rank analysis many efficient units exactly through the slacks-based measure model(SBM)

• Journal of Korea Port Economic Association
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• v.26 no.3
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• pp.18-41
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• 2010

The purpose of this paper is to show the empirical measurement way for predicting the seaport efficiency by using Super SBM(Slack-based Measure) with Wilcoxson signed-rank test under CRS(constant returns to scale) condition for 20 Korean ports during 11 years(1997-2007) for 3 inputs(port investment amount, birthing capacity, and cargo handling capacity) and 5 outputs(Export and Import Quantity, Number of Ship Calls, Port Revenue, Customer Satisfaction Point for Port Service and Container Cargo Throughput). The main empirical results of this paper are as follows. First, Super SBM model has well reflected the real data according to the Wilcoxon signed rank test, because p values have exceeded the significance level. Second,Super-SBM has shown about 87% of predicting ratio for the ports efficiency and the optimal size of investment in domestic seaport. The policy implication to the Korean seaports and planner is that Korean seaports should introduce the new methods like Super-SBM method with Wilcoxon signed rank test for predicting the efficiency of port performance and the optimal size of investment as indicated by Panayides et al.(2009, pp.203-204).

• The Journal of Fisheries Business Administration
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• v.41 no.3
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• pp.129-151
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• 2010

This study is to analyze the efficiency of Korean fishing ports using DEA. First, the study calculated the efficiency scores based on a CCR-BCC framework and hence technical, pure technical, and scale efficiency scores are seperated for the 38 fishing ports under study. The Average of technical, pure technical, and scale efficiency are turned out to be 0.6834, 0.8582, and 0.7774 respectively. The 15 fishing ports are fully efficient under the constant returns to scale while 21 fishing ports under the variable returns to scale. Second, the super efficiency scores are also calculated under the radial model without the consideration of slacks. The highest score is turned out to be 4.4984 for the P16 fishing port with the average score of 0.9652 for the entire fishing ports. Nevertheless, P16 fishing port has showed up only once as a reference set. On the other hand, P34 fishing port has showed up 11 times as a reference set, which scored the second highest score of 2.9815. Finally the super efficiency scores are calculated under the non-radial model with the explicit consideration of slacks. Now the P34 fishing port scored the highest score of 2.3424 with even 15 times referred to a bench-mark. Therefore the importance of P34 fishing port is emphasized once again on the field of bench-marking for the efficiency of fishing ports. When the targets for the input factors to improve the efficiency of each DMU are calculated the area of fishing port needs the most adjustment to be reduced for 40.36% on the average, while the cosignment sales area does the least adjustment for 13.70%.

• Journal of Digital Convergence
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• v.16 no.6
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• pp.75-84
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• 2018

Although many logistics companies are interested in project logistics, the existing research has been limited to the growth potential of project logistics market and the high barrier and importance of project logistics. This study analyzes using DEA the operational efficiency of forwarding companies registered in major overseas construction EPC companies and performing logistics services for overseas plant construction projects. For efficiency analysis, Super-SBM analysis and Malmquist analysis are used among DEA analysis techniques. As a result of the Super-SBM analysis, DMU 5 ranked first at 1.807. DMU 5 is more efficient than the other large corporations because it has the stable supply of its parent company H and the smallest input and output variables among the large corporations. As a result of Malmquist analysis, TCI, which is a technological development, showed a fluctuation while TECI showed a relatively stable variation. In addition, there is a difference in scale between major companies and small and medium sized companies. So, it is necessary to identify the efficiency improvement strategy for each group and apply it to the practical work.