• 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 Korean Society of Industrial and Systems Engineering
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• v.41 no.3
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• pp.61-71
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• 2018

The purpose of this study is to analyze the efficiencies of project management offices in large information system construction projects using the data envelopment analysis. In addition, we tried to estimate the confidence interval of those efficiencies using bootstrap DEA to give a statistical meaning. The efficiency by the CCR model is analyzed as eight project management offices are fully efficient and 22 project management offices are inefficient. On the other hand, there are 15 project management offices are fully efficient, but 15 project management offices are inefficient in the BCC model. As the result of the scale efficiencies, of the inefficient project management offices, 13 project management offices are inefficient in scale. It is possible to eliminate the inefficiency in the CCR model by improving their project performances. And, the nine project management offices showed that the inefficiency was due to pure technical efficiency, and these companies should look for various improvements such as improvement of project execution system and project management process. In order that the inefficient project management offices be efficient, it is analyzed that more efforts must be made for on-budget and on-time as a result of examining the potential improvement potentials of inefficient project management offices.

• Journal of Digital Convergence
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• v.11 no.5
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• pp.119-133
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• 2013

This study aims to provide power generating plants with eco-efficiency information. To implement the purposes, of study, both DEA(Data, Envelopment Analysis) model and interview were incorporated in terms of methodologies. To analyze the managerial efficiency, total labor cost and number of employees were considered as input factors. CO2, NOx, and water also were considered as input factors to analyze eco-efficiency. Both annual total power product and annual total revenue were used as output factors. CRS(Constant Return to Scale) and VRS(Variable Return to) model were facilitated in this analysis. According to the findings, most of the power plants were evaluated as 'Efficient'' taking into consideration of average value, both 0.928 from CCR model and 0.969 from VRS model. 7 DMUs including DMU3 and DMU12 are efficient out of 35 DMUs relatively, other DMUs are inefficient. For results of inefficient output factors distribution, it was found that inefficiency for NOx was marked relatively higher than CO2. In order to improve the eco-efficiency in the power plants in the long term, the target amount of Co2 as well as NOx reduction needs to be properly proposed in consideration of particularity of power plants. In the long run, renewable energy, alternative fuels should be adapted to reduce the eco-inefficient.

• The Korean Journal of Financial Management
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• v.25 no.4
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• pp.183-212
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• 2008

The purpose of this paper is to analyze the efficiency change and determinants of the korean non-life insurance companies. we use DEA (Data Envelopment Analysis) model to measure company efficiency change and use GLS, Tobit model, FIixed effect model, Random effect model, GMM to measure efficiency determinants. we utilize ten non-life insurance companies in korea and the panel data for five from 2001 to 2005. The empirical results show the following findings. First, technical efficiency shows that approximately 15.5% of inefficiency exists on the non-life insurance companies 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 efficiency determinants show that increase efficiency is depend on the premium income and real estates.

• International Commerce and Information Review
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• v.19 no.3
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• pp.45-61
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• 2017

The purpose of this study is to examine the efficiency of Korean companies' entry strategy in India through the DEA model and to review the current status and competitiveness of Korean companies in India. To analyze 112 companies that entered India in analyzing the common variables among the major variables related to Korean companies' entry strategy into India. To measure efficiency, 'DEAR 2.1' An output - oriented CCR model and BBC model were used for the analysis to minimize the input and maximize the output factor. The results of the study on the relative efficiency analysis of the investment strategy of the companies in India are as follows. First, six firm was analyzed efficiently in the CCR model and most firms showed inefficiency in management. Second, even with the BCC model, which represents pure technology efficiency, 103 companies were analyzed efficiently as well. Unlike the CCR, overall technology efficiency of firms was high. Third, as a result of analyzing the efficiency of the scale, it was found that six company showed efficient efficiency, and most of the companies showed inefficiency overall. Companies with inefficiencies should increase efficiency by expanding their scale. Based on the above analysis, it is expected that the companies that will enter India in the future should secure the human and material resources to realize economies of scale considering the number of employees, investment scale, investment type and industry.

• International Journal of Contents
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• v.4 no.3
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• pp.1-9
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• 2008

The Korean life insurance industry has undergone profound changes, such as the beginning of the variable insurance in July 2001 and the bancassurance enforcement in August 2003. However, little empirical research has analyzed data that includes the bancassurance of life insurance companies operating in Korea. In response to this lack of research, this paper applies DEA (data envelopment analysis) models to measure and decompose their efficiency. We discovered that life insurance companies operating in Korea are a little different in their composition ratio of inputs and outputs, due to the increased variety of distribution channels and new products. We provided efficiency scores, return to scale, and reference frequencies. We also decomposed CCR, BCC, and SBM efficiency into scale efficiency and MIX efficiency. So, we try to investigate whether the sources of inefficiency were caused by the inefficient operation of DMU, disadvantageous conditions, the difference of the composition ratio in inputs and outputs with reference sets, or any combination of the above. Most companies in the sample display had either constant or decreasing returns to scale. The efficiency rankings were less consistent among models and efficient DMUs. In response to this problem, we used the super-efficiency model to rank them and then compared the rankings of the DMUs among the various models. It was also concluded that the availability of panel data, rather than cross-sectional data, would greatly improve the validity of the efficiency estimates.

• Journal of Fisheries and Marine Sciences Education
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• v.28 no.6
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• pp.1629-1639
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• 2016

This study is to estimate the production efficiency of abalone aquaculture and to find its determinants utilizing the survey data of operating expenses in 2015. The first part of the analysis applied both DEA and Super-DEA for the estimation of efficiency of each aquaculture household as DMU. We used wages, feeding costs and area as inputs and annual profits and sales as outputs of the model. The second part of the study applied both Tobit and OLS for the identification of determinants of the efficiency. We investigated cost-ratio, depreciation costs, careers, value of living seeds, cleaning costs of farming ground and a ratio of 1 and 2 year-old abalone at shipment as potential determinants. The estimation results show us that the average technical efficiency, pure technical efficiency, and scale efficiency score turn out to be 72%, 81% and 85% respectively. The Super-BCC and Super-CCR models reveal their average efficiency scores as 81% and 80%. All of the variables used to identify the determinants of the efficiency. The study results suggests that the production efficiency can be improved by cleaning farming ground and hence lowering the death rate of seeds.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.5
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• pp.59-67
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• 2017

This study analyzes the efficiency of oriental hospitals using DEA(Data Envelopment Analysis). The input variables include the numbers of doctors, nurses, medical technicians, and beds. The output variable iscomprised of the sales account. The analysis tools used are EnPas and IBM SPSS Statistics 19. As a result of efficiency analysis, the private hospitals(establishment), less than 10 years in operation(operating period), containing less than 50 beds (number of the beds), located in the metropolitan area(location) showed high efficiency in the BCC(Banker, Charnes & Cooper) model, but indicated relatively low efficiency in CCR(Charnes, Cooper & Rhodes) model. This contradictory result is caused by inefficiencies in hospital size. The logistic regression analysis conducted to analyze the variables that affect the efficiency of oriental hospitals found that the efficiency decreased by 0.955 with each increase of 1 bed in the hospital.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.15 no.2
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• pp.609-615
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• 2014

Due to the recent global recession, the car industry demand levels have plummeted which led to a crisis in the automotive parts industry for the first time in history. Since the fourth quarter of 2008, the automotive parts manufacturers in America have faced a record loss and those in Japan and Europe who also had a strong track record are facing a weak economy. In addition, the domestic automotive parts industry is also affected by the global economic crisis. This research is that the relative efficiency analysis utilizing the DEA has done on the object of 25 small and medium-sized automotive parts manufacturers publicly listed, As the efficiency analysis result 6 of 25 manufacturers are efficient in CCR model and 12 manufactures have shown efficiency in BCC model, the efficiency analysis in consideration of the manufacturer size. The manufacturers with efficiency 1 in 25 manufacturers are DMU 1, 5, 7, 10, 18, 24 and the relatively benchmarking objects in other manufactures are DMU 1, 10, 24, Based on the results of this research, a direction to the domestic automotive parts manufacturers as well as a significant information will be provided in managing the companies in the future by the improvement of management efficiency through the practical efficiency analysis.

• The Journal of the Korea Contents Association
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• v.12 no.8
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• pp.330-342
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• 2012

Most of professional baseball teams are not good for business condition because of operation costs in spite of support of mother company. This study measured the relative efficiency and productivity change of the Korean professional baseball teams using DEA model and Malmquist Index for 2006-2008. The main results of this study can be summarized as follows. First, in case of efficiency of CCR for 2006-2008, the number of efficient professional baseball teams(CCR value is one) are two(Doosan Bears, Samsung Lions), two(Doosan Bears, SK Wyberns), two(Lotte Giants, LG Twins) respectively. Second, in case of efficiency of BCC for 2006-2008, the number of efficient professional baseball teams(BCC value is one) are three(Doosan Bears, Samsung Lions, LG Twins ), four(Doosan Bears, SK Wyberns, Samsung Lions, Kia Tigers), four(Lotte Giants, LG Twins, SK Wyberns, Samsung Lions) respectively. Third, average of Malmquist Index representing productivity change for 2006-2008 are 1.0615, 1.0293 respectively. These values mean increase of productivity. Results of this study can be used by inefficient professional baseball teams to improve inefficiency.