• 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.

• Environmental and Resource Economics Review
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• v.8 no.2
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• pp.149-174
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• 1999

본 연구는 1990년대 초 중반의 한국의 화력발전소 자료를 이용하여 발전부문의 생산성 변화를 분석하되, 생산성 변화를 발전소간의 효율성 격차에 의한 부문과 발전부문 전체의 생산함수 이동을 통해 나타나는 기술변화로 나누어 분석하였다. 분석결과, 화력발전소간에는 의미있는 정도의 효율성 격차가 존재하는 것으로 나타났으며, 분석에 포함된 기간 동안 연평균 약 5% 정도의 생산성 증가가 발생하였고, 이 가운데 효율성 격차의 해소를 통한 생산성 증가가 약 2%, 그리고 기술진보에 의한 생산성 증가가 약 3%를 차지하였다.

• Journal of Korean Society of Transportation
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• v.32 no.2
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• pp.93-105
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• 2014

This study evaluated the relative efficiency of mobile emission reduction countermeasures through a Data Envelopment Analysis (DEA) approach and determined the priority of countermeasures based on the efficiency. Ten countermeasures currently applied for reducing greenhouse gases and air pollution materials were selected to make a scenario for evaluation. The reduction volumes of four air pollution materials(CO, HC, NOX, PM) and three greenhouse gases($CO_2$, $CH_4$, $N_2O$) for the year 2027, which is the last target year, were calculated by utilizing both a travel demand forecasting model and variable composite emission factors with respect to future travel patterns. To estimate the relative effectiveness of reduction countermeasures, this study performed a super-efficiency analysis among the Data Envelopment Analysis models. It was found that expanding the participation in self car-free day program was the most superior reduction measurement with 1.879 efficiency points, followed by expansion of exclusive bus lanes and promotion of CNG hybrid bus diffusion. The results of this study do not represent the absolute data for prioritizing reduction countermeasures for mobile greenhouse gases and air pollution materials. However, in terms of presenting the direction for establishing reduction countermeasures, this study may contribute to policy selection for mobile emission reduction measures and the establishment of systematic mid- and long-term reduction measures.

• 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.