• 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)

• Management & Information Systems Review
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• v.31 no.1
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• pp.273-292
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• 2012

This paper attempts to analyze the efficiency of Korean Materials and Components Industry. 48 sample companies are extracted and efficiency analysis for them are accomplished by using DEA model. We use both CCR-I model and BCC-I model and classify the 48 companies into two groups; efficient and inefficient companies. We find the reference set which inefficient companies should benchmark in order to achieve efficiency and present the improving values for input and output variables. We analyze whether the inefficiencies come from scale or inefficient operation by measuring the scale efficiency. Finally the ranking among the efficient companies is derived through the super-efficiency analysis.

• Journal of the Korean Society of Marine Environment & Safety
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• v.23 no.2
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• pp.161-167
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• 2017

This paper measured and evaluated the technical efficiency, pure technical efficiency and scale efficiency of port labor via three inputs and three outputs using Data Envelopment Analysis (DEA). First, the average overall technical efficiency measured about 94.18 %, with 100 % pure technical efficiency being larger than 94.18% scale efficiency. As a result, 7 ports were identified as efficient, and 4 ports were identified as inefficient. Among the 4 ineffiecient ports, Donghae had the highest Increasing Return to Scale (IRS). However, the inefficient ports were all found to be less efficient in terms of resource operation than production scale. On the other hand, the efficient ports established priorities using the super efficiency method. As a result, port efficiency was highest for Incheon, Mokpo, Pyeongtaek-Dangjin, Masan, Yeosu Gwangyang, Jeju, and Gunsan-Daesan Ports, in order. In particular, Busan Port, found to be inefficient, would benefit from using Mokpo Port and Incheon Port as benchmarks to increase trade volume and modernize equipment for full-scale commercialization to improve labor efficiency.

• 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.

• 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.

• Journal of the Korean Society of Marine Environment & Safety
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• v.28 no.3
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• pp.430-440
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• 2022

Shipping companies are key components of the logistics industry, which is extremely significant in enhancing the country's comprehensive national power and promoting global trade development. In the context of the implementation of the new development pattern strategy in China and the impact of the global novel coronavirus (COVID-19), this paper takes 22 Chinese shipping listed companies as the research object and analyses the operational efficiency of them from 2011 to 2020 based on the Super-SBM DEA Model and Window DEA Model. Factors affecting the efficiency are further analyzed with the Tobit model. The research conclude that the operational efficiency of Chinese shipping companies as a whole shows a steady increase from 2011 to 2020. Although most of them are in a relatively ef ective operation state, fewer are absolutely effective companies. Besides efficiency among companies differs obviously, which indicates the potential of further improvement and promotion. What's more, factors such as current economic development level, enterprise size, human resources quality and enterprise turnover speed have significant positive correlation to the operation efficiency of Chinese shipping listed companies, which is significant to improve the operation efficiency of Chinese shipping companies.

• 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.

• 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.

• 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%.