• Journal of Digital Convergence
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• v.11 no.10
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• pp.255-262
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• 2013

Data envelopment analysis(DEA) is a linear programming procedure designed to evaluate the relative efficiency of a set of peer entities called decision making units which use the same inputs to produce the same outputs. It has been widely employed in a variety of disciplines as an efficiency or performance measurement tool for comparing a set of entities such as firms, banks, hospitals, nations and organizations. The method, however, cant's make the priority of their performance when many units have efficiency score of unity or 100 percent. In this paper, we propose a new approach which combine qualitative method(graphical approach using network analysis) and quantitative method(super-efficient analysis using DEA), and present the results of an empirical analysis using the data of the Korean professional baseball players. As a result, there were 12 DMU that priority is hardly realized through DEA. However, this problem could be solved with super-efficiency analyzing. Also, more in-depth interpretation was able through integrating results of dendrogram and super-efficiency analyzing and prospecting it in qualitative, quantitative ways.

• Journal of Korea Port Economic Association
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• v.32 no.2
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• pp.123-135
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• 2016

This study uses Data Envelopment Analysis(DEA) to investigate the management efficiency of Korean shipping companies based on business administration costs such as corporate entertainment, advertisement, and labor costs. We analyze shipping enterprises listed on the Korean stock market of the period of 2010-2014. Corporate entertainment, advertisement and labor costs are used as input variables and sales and net income are used as output variables. We use technical efficiency, pure technical efficiency, scale efficiency and returns to scale to propose a plan to improve the efficiency of inefficiency decision-making units (DMUs). The results of the efficiency analysis show that six of the DMUs in the technical efficiency of CCR model and eight of the DMUs in the pure technical efficiency of BCC model are in efficient state. In terms of return to scale, six of the DMUs(24% of all DMUs) show increasing returns to scale, while 13 DMUs(52% of all DMUs) showdecreasing returns to scale. Because multiple efficient state for DMUs exist in the technical efficiency analysis, we conduct a super efficiency analysis. The results show that the efficient state of the twomost efficient DMUs are 1.314 and 1.243, respectively. This implies that these DMUs could maintain their current levels of the efficiency if they increase the amount spent on advertisements, corporate entertainment and labor costs by 31.4% and 24.3%. respectively. We conclude this study by providing the efficiency states of each DMU and target for improving the inefficiencies in each case.

• 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 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%.

• International Area Studies Review
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• v.22 no.2
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• pp.61-91
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• 2018

Credit Guarantee scheme is one of the most effective tools for the small business policy. The performance analysis on domestic institution level is relevant in terms of various factors of assisting tools factor. This study measured comparative global efficiency by DEA model and Super-efficiency model among 70 credit guarantee institutions in Japan, Taiwan, and Korea who are operating the schemes. At the result of the analysis, Korean credit guarantee institutions are comparatively efficient than Japanese institutions, and the DMU shows moderate in operation efficiency. The Super-efficiency ranked by Hiroshima, Taiwan SMEG, Pusan, Chiba, Shizuoka, Ulsan, and KOTEC. Most of the Credit Guarantee Institutions showed increasing returns to scale, and it indicates increasing input strategy. The statistical difference of efficiency level in Japan and Korea shows very meaning numbers. This research suggest that (1)Periodical Analysis are needed on Japanese Schemes, (2)The analysis on the impact of credit guarantee scale to the national economy and SME policy, (3) Analysis on the conclusive factors of the efficiency, (4)The policy direction has to be made by inefficient factor analysis, (5) The measurement tools of efficiency of the schemes in various aspects.

• Journal of Digital Convergence
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• v.12 no.6
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• pp.181-192
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• 2014

This study suggests consulting directions for non-profit private organizations which were found to be inefficient in the efficiency analysis for the public activities support projects on those organizations performed by the Korean government. An ANOVA analysis on seven types of public activities support projects showed that there were differences among those types. By applying CCB-I, BCC-I, Super efficiency models among DEA, performance efficiencies were analyzed. Four input elements (age of the organization, supported amount, number of members, and the number of workers) and three output elements (project scores, financial scores, and comprehensive scores) were analyzed, and high efficient organizations were found as benchmarking objects, and, through super efficiency analysis, those objects were classified into short, mid, and long-term objects. Through such methods, this research provided organizations with the best information on other organizations to learn from and improve themselves.

• Journal of Korea Port Economic Association
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• v.26 no.4
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• pp.188-206
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• 2010

Data Envelopment Analysis(DEA) is an operations research-based method for measuring the performance efficiency of decision units that are characterized by multiple inputs and outputs. DEA has been applied successfully as a performance evaluation tool in many fields. However, it has not been extensively applied in the shipbuilding industry. This paper applied the input-oriented DEA model, and Malmquist indices to the 7 shipbuilding firms to measure the efficiency and productivity changes during the period of 2004 to 2009. The Malmquist indices will be decomposed into three components such as pure efficiency change, scale efficiency change, and technical change. The empirical results show the following findings. First, the DEA findings indicate that main source of inefficiency is scale rather than pure technical. Second, the Malmquist indices show that an overall decrease in productivity.

• Journal of Energy Engineering
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• v.9 no.4
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• pp.319-327
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• 2000

산업분야의 여러공정에서 배출되는 휘발성 유기화합물은 1차적인 작업자에 대한 유해성뿐만이 아니라 대기중에 배출시의 제 2차 오염물질의 생성 때문에 최근 들어 이러한 물질의 처리에 큰 관심이 집중되고 있다. 본 연구에서는 휘발성 유기화합물로서 프로판을 사용하여 이러한 초 희박 혼합기의 제거를 위해 재생열산화법이 제안되었다. 실험장치에는 중앙에 연소실과 전기적 열량공급장치를 장착하였다. 초 희박 혼합기의 연소실에서의 산화과정과 열사화 장치의 폐열회수 특성을 연구하기 위하여 혼합기의 농도, 유속 및 연소실 최대온도와 같은 다양한 작동조건을 고려하였다. 그 결과. 재생열산화장치가 초 희박 혼합기의 산화에 적절하게 사용될 수 있음을 알았으며 최대 96%의 제거효율 얻을 수 있었다. 산화과정중에 발생하여 배출되는 CO는 운전조건을 변화시킴으로써 그 농도를 낮출 수 있었으며 열적 NOx는 배출되지 않았다. 페열회수효율은 전 운전영역에서 높게 나타났으며 그 값이 최대 98%에 이르렀다.

• 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.

• Journal of Korea Port Economic Association
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• v.29 no.2
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• pp.159-171
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• 2013

This paper aims to analyse the relative efficiency of logistics facilities and suggest the policy alternatives for exploring and activating them. This study also divides the logistics facilities into airport terminals, logistics complexes, container terminals, and trucking freight terminals. For this purpose, the CCR-DEA as well as the BCC-DEA techniques are employed to show which part explains the primary cause of inefficiencies of each DMU(Decision Making Unit). The empirical results indicate that the efficiency of logistics complex is the lowest of all, while freight trucking terminal has the highest efficiency. This study also reveals that operation inefficiency is greater than scale inefficiency in most of DMUs, showing that much more effort be done for alleviating the cost resulting from irrational management.