• 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.

• International journal of advanced smart convergence
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• v.11 no.2
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• pp.171-184
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• 2022

The purpose of this paper is output oriented, in order to maximize the output level of sustainable development efficiency of foreign trade in western China with limited input. This paper adopts the relevant input-output indicators of sustainable foreign trade development of 11 provinces and cities in western China from 2016 to 2020, and uses DEA model to measure their technical efficiency, pure technical efficiency and scale efficiency. Malmquist index was used to calculate the total factor productivity change index of each province in western China from 2016 to 2020. We found that, on the whole, the average values of technical efficiency, pure technical efficiency and scale efficiency of provinces and cities in western China from 2016 to 2020 are greater than 0.8, indicating that the western region has high technical efficiency, relatively high management and institutional level and high existing scale level. Scale efficiency is lower than pure technical efficiency on the whole, indicating that the current sustainable development efficiency of foreign trade in western China is mainly limited by its scale level. The technological progress index is higher than the technological efficiency change index, indicating that the total factor productivity of the sustainable development of foreign trade in western China is mainly driven by technological progress and more influenced by external factors. We think the conclusion of this study can provide important reference information for the sustainable development of foreign trade of provinces and cities in western China.

• The Journal of Fisheries Business Administration
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• v.47 no.1
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• pp.63-86
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• 2016

The purpose of this study is to investigate production efficiency of Oceans and Fisheries Human Resources Development Programs Efficiency using Bootstrap-DEA. The study extracts 33 officials curriculum, 11 fisheries managers curriculum for its analytical. First, the study estimates technical, pure technical, and scale efficiency of each curriculums based on traditional DEA under the assumption of CRS and VRS. 8(official 7, managers 1) curriculums are identified as efficient DMUs under the CCR-model, and 13(official 10, managers 3) under the BCC-model. We provide inputs that allow inefficient curriculum to be efficient DMUs on a production frontier, and a reference set for their bench-marking. Second, rank test, Wilcoxon-Mann-Whitney test to find a statistical significance of heterogeneity existing in efficiences between Bootstrap-DEA tenical vs Bootstrap-DEA pure technical was no significant difference. We have identified that G10, 11, 12 13, 25, 31, 33, 39 curriculums are the most efficiently produced in the technical and pure technical efficiency. Also we managed to measure the inefficiency which exists in efficiently produced curriculums when estimating the bias corrected efficiency scores. In Technical efficiency, Operation and facility was significant at the 10%. In Pure technical efficiency, facility was significant at the 10%.

• Environmental and Resource Economics Review
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• v.14 no.3
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• pp.595-626
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• 2005

The purpose of this paper is to estimate technical efficiency, scale efficiency, and environmental efficiency by income level of Korean farms, and analyze the factors to decide three efficiencies. Depending on the non-parametric methods, we estimate technical using inputs and outputs of total farms without assuming of goods or behavior of optimization. The average technical efficiency of total firms under constant return to scale and strong disposability is 0.437. The technical inefficiency was caused by 47.7% in pure technical inefficiency, 11.3% in scale failure, and 3.2% in environmental inefficiency. The number of firms under increasing return to scale occupied almost 70% and 27% of total firms respectively. Higher are income class, middle debt & long debt per asset, and N effluents per cultural land, higher technical efficiency. The increases of BOD discharges per cultural land and machines per cultural land deteriorate environmental efficiency.

• Korean Journal of Agricultural Science
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• v.37 no.3
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• pp.509-514
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• 2010

The purpose of this study is to analyze the technical efficiency and its determinants for Korean Apiculture farming by using from door to door and e-mail inquiry data. The analysis was implemented through the Cobb-Douglas stochastic frontier production function (SFPF) model including the technical inefficiency effect model for cross-sectional data. To measure the SFPF model, honey production was used for a dependent variable, and for input variables labor cost, preventive cost, material cost, feeding cost, depreciation cost were used. Farmer's age, farmer's career, farming scale, full-time or half-time firm and movement or fixed firm variables were used to measure the inefficiency effect model. The average technical efficiency on apiculture farming in Korea is estimated to be 0.8112. It means that there were technical inefficiency of about 18.88% in Korea apiculture farming. In this study there are some suggestions which could increase the technical efficiency of Korean apiculture farming.

• 한국IT서비스학회:학술대회논문집
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• 2007.11a
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• pp.679-684
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• 2007

This paper proposes a scheme to estimate the technical efficiency of trucks in logistics as performance measure by Data Envelopment Analysis (DEA). The result of technical efficiency estimation shows that there exists a substantial opportunity for improvement in technical efficiency of trucks and also the heterogeneity in the technical efficiency among trucks.

• Korean Journal of Organic Agriculture
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• v.17 no.1
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• pp.19-33
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• 2009

This paper evaluates the technical efficiency of organic farm management practices and studies its main determinants in Hongdongmyeon of Hongsung county, Chungnam province. The analysis is performed in two stages. First, the efficiency is measured via the nonparametric "Data Envelopment Analysis" (DEA) technique. The DEA models are constructed not only to assess the overall technical efficiency of organic fanning practices but also to evaluate the management efficiencies. In a second stage critical determinants of efficiency are determined using a Tobit model. In this analysis the focus is on technical and socio-economic variables. The analytical results show that technically efficient farms is about 13 percent and the mean technical efficiency is found to be 0.73 indicating that many farms are not operating at an efficient scale.

• The Journal of Fisheries Business Administration
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• v.41 no.3
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• pp.21-44
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• 2010

The paper estimates changes in total factor productivity and technical efficiency change index and technical change index using Malmquist productivity index(MPI) in fisheries wholesale products over the time period of 2006 through 2008. The model considers a number of employees and operating costs as input factors, and sales and EBIT(earnings before tax and interest) as output factors. The results indicate that, between 2006 and 2007, there is in general technical progress in which TCI(Technical Change Index) indicates 2.7994 in the sale scale of 50 million won through 100 million won, while there are no efficiency in TECI(Technical Efficiency Change Index), PECI(Pure Efficiency Change Index) and SECI(Scale Efficiency Change Index) which are estimated to be around 1. Between 2007 and 2008 technical efficiency and technical progress are generally declined, compared to those of 2006 and 2007. Wilcoxon's rank-sum test shows that there are statistically significant difference of TCI and MPI between two periods at the level of 5%, while there are statistically significant difference of TECI, PECI and SECI between two periods at the level of 5%.

• The Journal of Fisheries Business Administration
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• v.41 no.3
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• pp.45-58
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• 2010

This study estimated the technical efficiency of coastal composite fishery in Korea by using the data envelopment analysis (DEA) and the stochastic frontier analysis (SFA) methods, and the results on the respective method were compared. In the DEA method, the constant returns to scale (CRS) and the variable returns to scale (VRS) output-oriented DEA models were separated and technical efficiencies were estimated, respectively. The average estimated value of technical efficiency by the SFA method (0.633) was found to be lower than that by the VRS-DEA method (0.738), while it was higher than that by the CRS-DEA method (0.479). It was found that strong correlation exists between the SFA method and the VRS-DEA method. The method which can utilize both methods in mutually complementing way for the estimation of technical efficiency was also considered.

• 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.