• 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.29 no.3 s.99
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• pp.215-220
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• 2005

This paper aim, to measure and evaluates the technical efficiency, pure technical efficiency and scale efficiency with two inputs and four outputs with the use of DEA(Data Envelopment Analysis) in Korean RCC(Rescue Co-ordination Center)/RSC(Rescue Sub-Center). Several conclusion emerge. first the average efficiency of overall technical efficiency measure about $91.03{\%}$ and pure technical efficiency $96.80{\%}$ is much large then scale efficiency $93.83{\%}$. It means that inefficiency has much more to do whit the inefficient utilization of resources rather then the scale of production. second, DRS(decreasing return to scale)is Tongyeong and IRS(increasing return to scale) is Incheon, Taean, Gunsan, Yeosu, Ulsan, Donghae in RCC/RSC finally, inefficiency RCC/RSC have to benchmarking with reference sets.

• 한국경영정보학회:학술대회논문집
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• 2007.06a
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• pp.800-806
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• 2007

IT 벤처기업은 자본 대비 높은 수익성을 가지므로 지식기반 산업환경에서 많은 투자자들의 집중적인 관심을 받고 있다. 이러한 IT 벤처기업의 효율성을 평가하기 위한 방안으로, DEA 와 데이터마이닝 기법을 통합하는 방안을 제시하였다. 국내 코스닥 상장 기업 가운데 IT 에 주력하고 있는 벤처기업들을 대상으로 본 연구에서 제시한 효율성 평가방법을 적용 하였다. 대표적인 비모수적 분석기법인 Data Envelopment Analysis(DEA)를 이용하여 연구대상 기업들을 효율기업 및 비효율기업으로 구분한 후, DEA 의 효율성을 설명하는 모형을 logit 을 이용하여 구축하였다. DEA 는 기업의 상대적인 효율성을 측정하는 데에서 우수하지만, 효율성 정도를 설명하는 모형의 구축에는 한계가 있다. 이를 보완한 DEA 의 결과를 logit 과 통합한 효율성 모형에 대해서 데이터 마이닝 기법인 logit, 판별분석, Support Vector Machine(SVM) 등을 적용하여 IT 벤처기업의 효율성을 사전에 예측하여 평가 및 투자에 활용할 수 있는 방안을 제시하였다.

• 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.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2004.10a
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• pp.661-664
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• 2004

본 연구는 DEA기법을 이용하여 14개의 국내 은행의 상대적 효율성을 평가하였다. 효율성 평가에 있어서 은행을 중개기관 접근방법에서 평가하였으며, 투입물과 산출물을 선정하는 데 있어서 신탁계정과 은행계정별로 구분하여 연구를 수행하였다. 또한 규모의 효율성을 평가하기 위해 CCR모형과 함께 BCC모형을 이용하여 효율성을 평가하였다. 분석결과 신탁계정과 은행계정의 효율성은 차이가 있었으며, 대부분의 은행들이 DRS의 규모의 효율성에 있는 것으로 나타났다.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2004.11a
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• pp.191-196
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• 2004

This paper is to measure and ealuates the technical efficiency, pure technical efficiency and scale efficiency with three inputs and two outputs with the use of DEA(data envelopment analysis) in Korean RCC(Rescue Co-ordination Center/RSC(Rescue Sub-Center). Several conclusion emerge. first the average efficiency of overall technical efficiency measure about $91.03\%$ and pure technical efficiency $96.80\%$ is much large then scale efficiency $93.83\%$. It means that inefficiency has much more to do whit the inefficient utilization of resources rather then the scale of production. second, DRS(decreasing return to scale) is Tongyeong and IRS(increasing return to scale) is Incheon, Taean, Gunsan, Yeosu, Ulsan, Donghae in RCC/RSC. finally, inefficiency RCC/RSC. have to benchmarking with reference sets.

• Korean Journal of Construction Engineering and Management
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• v.6 no.1 s.23
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• pp.151-161
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• 2005

This paper analyzes the technical efficiencies of 38 Korean engineering and construction firms and the efficiency changes from 1999 to 2003 using data envelopment analysis (DEA). Best practice firms in terms of technical efficiency and profit are identified. For inefficient firms, performance targets to be efficient are suggested. Technical efficiencies had been increased over the five year period, and the efficiency difference between firms had been reduced during this period. The differences in efficiency due to the differences in cooperate governance structures are statistically significant. In addition, the technical efficiency is correlated with product portfolios, degree of subcontract, rates of value added, returns on invested capital, and EBITDA.

• Journal of Information Management
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• v.40 no.3
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• pp.41-60
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• 2009

This study utilizes DEA/Window analysis in order to investigate the relative efficiency levels of korea national university libraries during the period of transition 2004-2008. The empirical results show the following findings. Firstly, a technical efficiency was not efficient which was a scale efficiency rather than a pure technical efficiency in 2008. Secondly, a technical and pure technical efficiency has increased steadily from 2004 to 2008(but a technical, pure technical efficiency has decreased since in 2008). As a result, a technical efficiency increase can be explained by a pure technical efficiency increase.

• Journal of Digital Convergence
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• v.10 no.9
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• pp.159-164
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• 2012

Although the display industry plays an important role in the entire Korean economy, few empirical research has analyzed the efficiency of display companies. The purpose of this paper is to measure and analyze efficiency of korean listed display firms using DEA(Data Envelopment Analysis) models. We evaluate the CCR and BCC efficiency in DEA models and the return to scale of the Korean listed display companies. The benchmarking companies and efficiency value for the display companies with inefficiency are also provided to improve their efficiency. We analyzed the 44 listed companies consisted of 7 listed on KOSPI and 37 listed on KOSDAQ at the end of 2010. The analysis results show six companies whose values of CCR are 1, and fourteen firms whose values of BCC efficiency are 1. In additions, the six companies have the scalability efficiency. Eventually the efficiency analysis can provide the valuable information for inefficient companies to find benchmarking companies and to improve their efficiency.