• Journal of Korean Society of Rural Planning
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• v.1 no.1
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• pp.99-110
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• 1995

이 연구는 한국 쌀생산의 효율성을 경영규모별로 파악하고, 영농규모 확대를 통한 쌀생산의 효율성 중대 가 가능하다는 가설을 검정해 보고자 하였다. 이 분석에 필요한 기술적 선도농가들의 생산함수인 프런티어(frontier) 생산함수를 구하기 위해서는 교 란항의 정보를 이용할 수 있는 확률(stochastic) 모형아 바람직하고, 아울러 경영규모별로 규모의 효율성을 파악하기 위해서는 레이 동조(ray-homothetic) 함수가 적절하다. 따라서 여기에서는 농림수산부의 1992년도 쌀생산비 자료에서 임의로 추출한 1,203호의 표본 자료를 이용해 앞에서 언급한 두가지 요소를 동시에 감안 할 수 있는 $\ulcorner$레이 동조 확률 생산함수(ray-homothetic stochastic production function)$\lrcorner$를 최우추정법 (Maximum likelilood estimation method)으로 추정하였으며, 이를 토대로 쌀생산의 경영규모별 비효율성 을 순수 기술적 비효율성과 규모의 비효율성으로 나누어 계측하였다. 게측결과에 의하면 쌀생산의 비효율성은 굉균 35.loyo에 이르고 있다. 이 가운데 순수 기술적 비효율성은 12.0%이고, 규모의 비효율성은 24.l%에 달했다. 기술적 비효율성과 규모의 비효율성 모두 경지규모 확대와 더불어 감소하는 것으로 나타나, 경영규모 확대와 더불어 미곡생산의 효율성이 증대될 수 있다는 가설은 기 각되지 않았다. 그러나 대농의 경우에도 규모의 비효율성이 여전히 높은 것으로 나타나 영농규모 확대를 저 해하는 제도적 장벽이 아직도 높다는 것을 알 수 있다. 아울러 대농과 소농과의 효율성 격차가 현저하지는 않은 것으로 나타나 단순히 경지를 중심으로 한 경영규모 확대만으로는 효율성 제고에 한계가 있음을 보여 주고 있다. 이 연구의 결과는 다음과 같은 정책적 함의를 가지고 있다. 첫째, 한국 미곡생산의 효율성 중대 잠재력이 결코 과소 평가되어서는 안된다. 둘째, 영농규모 확대가 쌀생산의 효율성 증대를 위해 필요한 것은 사실이지 만 단순한 경지규모의 확대에 치중하는 것보다 영농규모 확대를 저해하는 제도적 기술적 장애요인을 제거해 나가는 것이 더욱 중요하다. 마지막으로, 새로운 영농기술의 개발은 물론이고 현행 선진영농기술의 보급도 쌀생산의 효율성 중대에 상당한 역할을 할 수 있다는 사실이 간과되어서는 안된다.

• Journal of Korea Port Economic Association
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• v.22 no.3
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• pp.59-78
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• 2006

The purpose of this paper is to analyze the trend on scale efficiency of the Port of Gwangyang from 1994 to 2004 using CCR, BCC, and Malmquist index approaches. The main results are as follows. first, scale efficiency shows a 50% similar [5(94/95, 95/96, 97/98, 2001/2002, 2003/2004) out of 10] pattern to technical efficiency change. Second, total factor productivity increased at 48.57% rate of growth on average in 6 out of 10 periods except 96/97, 97/98, 99/2000, and 2000/2001. 2003/2004 period is the one period experiencing rapid total factor productivity changes, mainly due to technical progress. Third, the ranking order of accumulative indices is scale efficiency change, TFP change, efficiency change, technical change, and pure efficiency change. The main policy implication of this paper is that according to the CCR, BCC, and Malmquist results, the Port of Gwangyang should develop the plan for enhancing the 5 Malmquist indices with following the management way of benchmarking ports.

• Proceedings of the Korea Contents Association Conference
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• 2014.11a
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• pp.429-430
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• 2014

본 연구는 DEA를 이용하여 국내 일반은행(13개)의 상대적 효율성을 분석하였다. 분석결과, CCR모형에 의한 기술효율성이 '1'인 은행은 5개, BCC모형에 의한 순수기술효율성이 '1'인 은행은 9개였으며, 규모효율성이 '1'인 은행은 5개였다. 시중은행과 지방은행의 효율성 평균 차이 분석에서는 기술효율성과 순수기술효율성에서는 유의한 차이가 없었으며, 규모효율성에서만 p<0.1에서 지방은행이 시중은행 보다 다소 높은 효율성을 보였다.

• The Journal of the Korea Contents Association
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• v.13 no.1
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• pp.366-375
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• 2013

Recently, management of Newspaper developmet of the internet news, broadcasting and free newspapers escalated competition between newspaper companies and other media companies as well as competition among newapaper companies. This paper analyzes the efficiency of Korean Newapaper using DEA model. We evaluate the CCR-O, BCC-O efficiency, SE and RTS of 30 Newspaper. We also suggest the Newpaper which can be benchmarked based on analyzed information. The result shows that ten Nespaper whose values of CCR-O efficiency are 1, and Fourteen Nespaper whose values of BCC efficiency are 1. RTS indicates IRS of 1 firms, DRS of 16 firms and CRS of 13 firms. To variables on the effectiveness of newspaper publishing companies for the understanding and performance analysis.

• 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 BIBLIA Society for library and Information Science
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• v.22 no.4
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• pp.301-315
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• 2011

DEA(Data Envelopment Analysis) is useful to measure the relative efficiency of organizational units where the presence of multiple inputs and outputs. This study applied DEA-CCR and DEA-BCC to evaluate the technical, pure technical, and scale efficiency of 29 university libraries. The input variables were number of books, print edition expenses, building space, staff, number of seats. As output variables we estimated: reader visits, number of borrowed items, number of visitors. It was found out that number of libraries with 100% relative efficiency among 29 libraries were 13. Also the results shows that main reason of inefficiency was from scale rather than from pure technical. Many inefficient libraries were operations of increasing return to scale.

• The Korean Journal of Financial Management
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• v.19 no.1
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• pp.133-151
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• 2002

본 연구는 Malmquist지수를 이용하여 1997년 외환위기 때부터 2000년까지 국내은행의 생산성 변화를 순수기술효율성, 규모효율성 및 기술진보의 변화로 구분하여 측정함과 동시에 서울소재은행과 지방은행간의 생산성을 비교하였다. 1997년과 2000년간의 순수기술효율성의 변화는 감소하였지만, 규모효율성과 기술진보의 변화가 순수기술효율성의 하락 부분을 상쇄한 결과로 2000년에는 1997년의 생산성 수준을 회복하였다는 것을 확인하였다. $1997{\sim}2000$년의 서울소재 은행과 지방은행간을 비교한 결과에 의하면 서울소재은행의 생산성이 높게 나타났다. 두 집단간에 이러한 차이는 규모효율성으로부터 기인하였으며, 기술혁신을 의미하는 기술진보의 변화에는 두 집단간에 차이가 없었다. 특히 지방은행의 생산성은 2000년에도 1997년도 수준을 회복하지 못하고 있다.

• The Journal of the Korea Contents Association
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• v.15 no.5
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• pp.475-487
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• 2015

This study measures the managerial efficiency of Korea's 14 public enterprises using bootstrap DEA in 2013. In addition, it examines the factors that affect on the bootstrap bias-corrected efficiency using truncated regression analysis. The results and implications of this study are as follows. First, using bootstrap DEA model analysis, the results showed that the mean technical efficiency was 0.3182, the mean pure technical efficiency was 0.4994 and the mean scale efficiency was 0.6585. The main cause of technical inefficiency was due to pure technical inefficiency. Second, rank test between technical efficiency of general DEA model and bootstrap DEA model was no significant difference under CRS and VRS assumption. Third, the main cause of the inefficiency in 11 DMUs among 14 DMUs were mainly due to the pure technology and three DMUs were because of the scale efficiency. Finally, in the truncated regression analysis, cost of labor, profit, sales, return of equity, and the number of employees appeared as factors affecting the scale efficiency at the 10% significance level.

• The Journal of the Korea Contents Association
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• v.22 no.5
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• pp.165-173
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• 2022

Recently, competition to provide specialized services for the information and communications industry has accelerated in terms of future technology and investment strategy of the Fourth Industrial Revolution. Technological innovations related to information and communications can be seen as increasing productivity, creating added value for companies, and playing a pivotal role in the development of economic growth. Therefore, efficient management of the information and communications industry is important. This study analyzes management efficiency stones for the top 30% of KOSDAQ-listed information and communications companies using dea, presents projected values of companies for efficient operation, and confirms benchmarking company references. We evaluated CCR efficiency, BCC efficiency, ranking, Scale Efficiency(SE), and Return To Scale (RTS) of KOSDAQ-listed information and communications businesses. The analysis showed CCR efficiency of 1, 14 companies, and 1 BCC efficiency, and Nanatan companies were analyzed as ten companies. Scale yield was analyzed by the IRS as four companies, 13 CRS and 13 DRS companies.

• 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.