• Management & Information Systems Review
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• v.36 no.2
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• pp.307-327
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• 2017

Ecological efficiency is an important index measuring and reflecting the sustainable development level of economy, resources and environment in a region. This paper makes an empirical study on the ecological efficiency of 31 provinces in China in 2014 with the three-stage DEA model. The results show that the three indexes, the total investment in environmental governance (Unit: hundred million Yuan), the second industry proportion(%), and per capita automobile ownership (car/ten thousand people) functioning as the external environmental variables have significantly impacted the regional ecological efficiency. Excluding the impact of the external environment and statistical noise, the technical efficiency of regional ecological efficiency has increased from 0.526 to 0.639, and the pure technical efficiency has increased from 0.650 to 0.858, with the scale efficiency decreased from 0.833 to 0.740, accurately reflecting the regional ecological efficiency level. 31 Chinese provinces are classified into four different types according to the pure technical efficiency and scale efficiency. Every region shall, according to the characteristics of its efficiency, emphasize differently on improving the management level or expanding the scale of production so as to improve the ecological efficiency.

• Journal of the Korean Society for Railway
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• v.12 no.4
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• pp.542-547
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• 2009

The objective of this paper is to measure the relative technical efficiency of Korean railway transport service. Previous studies on the efficiency in Korean railway service have carried out before the structural reform of Korean railway industry in 2004, whereas this study used the latest data which reflected the impact of reform. We analyzed the efficiency in Korean railway transport by means of measuring the technical efficiencies of other countries, these were estimated with data envelopment analysis. Using data from 22 railway operators over the period $2000{\sim}2006$, the results indicate that the Korean railway transport has been operated efficiently as compared with others.

• International Journal of Fluid Machinery and Systems
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• v.4 no.1
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• pp.150-160
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• 2011

This study focuses on the Achard turbine, a vertical axis, cross-flow, marine current turbine module. Similar modules can be superposed to form towers. A marine or river hydropower farm consists of a cluster of barges, each gathering several parallel rows of towers, running in stabilized current. Two-dimensional numerical modelling is performed in a horizontal cross-section of all towers, using FLUENT and COMSOL Multiphysics. Numerical models validation with experimental results is performed through the velocity distribution, depicted by Acoustic Doppler Velocimetry, in the wake of the middle turbine within a farm model. As long as the numerical flow in the wake fits the experiments, the numerical results for the power coefficient (turbine efficiency) are trustworthy. The overall farm efficiency, with respect to the spatial arrangement of the towers, was depicted by 2D modelling of the unsteady flow inside the farm, using COMSOL Multiphysics. Rows of overlapping parallel towers ensure the increase of global efficiency of the farm.

• Journal of the Korea Safety Management & Science
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• v.15 no.1
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• pp.249-258
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• 2013

Data Envelopment Analysis (DEA) is a useful tool to analyze the relative efficiency of decision making units (DMU) characterized by multiple inputs and multiple outputs. This method has been popularly used as an analytical tool to suggest some strategic improvement. To do this, the results of DEA provide decision makers with a single efficiency score, efficient frontier, return to scale, benchmarking decision making units, etc. The purpose of this paper is to evaluate research performance of 38 universities and provide an inefficient university with the way of organizational changes to be an efficient university by using DEA. Various input and output variables are used to identify technical and scale inefficiency. Additionally, we analyze how an inefficient DMU could be changed an efficient DMU based on a case university. This result will give an insight of constructive directions for increasing of research performance to university decision makers.

• Korea Journal of Hospital Management
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• v.15 no.1
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• pp.27-48
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• 2010

The purpose of this paper is to analyze the efficiency change and its determinants of the regional public hospitals. We utilize 34 regional public hospital's panel data for 6 years from 2003 to 2008. We use DEA(Data Envelopment Analysis)-CCR, BCC model, DEA/Window model, and DEA Profiling. The empirical results show the following findings. First, technical efficiency shows that approximately 3.6% of inefficiency exists on the regional public hospitals and it reveals that the cause for technical inefficiency is due to scale inefficiency. Second, DEA/Window results show that the stable dissimilarity by standard deviation, LDP of CCR. Third, the results of partial efficiency by DEA Profiling show that increase efficiency depends on the number of beds, doctors, and nurses.

• Korean Journal of Organic Agriculture
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• v.26 no.1
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• pp.33-41
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• 2018

The paper aims to estimate efficiency of watermelon by using a bootstrapping approach to generating efficiency estimates through Monte Carlo simulation resampling process. We use the input-output data for watermelon 107 farmers. The main results are as follows. The estimates of efficiency depends on the methodology. The estimates of general DEA is greater than the bootstrapping method. The technical efficiency and pure technical efficiency measure of watermelon is 0.72, 0.82 respectively. However the bias-corrected estimates are less than those of DEA. We know that the DEA estimator is an upward biased estimator. According to these results, the DEA bootstrapping model used here provides bias-corrected and confidence intervals for the point estimates, it is more preferable.

• Journal of Korean Society for Quality Management
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• v.48 no.3
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• pp.453-462
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• 2020

Purpose::This study aims to analyze the management performance and production efficiency of medicinal crop farmers. Methods: We conducted an empirical survey of medicinal crop farmers and analyzed production efficiency using DEA method. Results: First, The crops that increased the number of farms during 2010 and 2018 were Angelica tenuissima and Salvia miltiorrhiza, which was attributed to higher income per hour than other crops. Second, As for the efficiency of Liriope platyphylla, the average was 0.376, and the coefficient of variation was the lowest, 0.566. Third, Salvia miltiorrhiza and Atractylodes japonica had the highest technical efficiency after Liriope platyphylla, but the variation coefficient was high and the efficiency was relatively high. Fourth, As a result of performing variance analysis to find out the difference of each crops on the value of medicinal crop efficiency, the technical efficiency, pure technical efficiency, and scale efficiency were all statistically significant. Conclusion: Based on the results above, following policy suggestions are offered. First, It is necessary to provide information on crops with high income compared to the input of labor, and to develop labor-saving cultivation technologies for each crop. Second, A stable labor supply system will be needed in rural areas. Third, Efforts should be made to close the technological gap between farmers through a lot of education and consulting for farmers who grow medicinal crops.

• Proceedings of the Korean Magnestics Society Conference
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• 1994.10a
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• pp.78-79
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• 1994

• Journal of Korean Society for Quality Management
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• v.38 no.3
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• pp.463-474
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• 2010

In this study, we evaluate the efficiency of Construction Industry using Data Envelopment Analysis(DEA). Since the Construction Industry has been traditionally operated through competition, it is important to measure the efficiency. In this paper, we empirically analyze the Efficiency of the 50 Korean Construction Industry. In detail, we used the scale of efficiency in order that efficiency cannot be affected by the total technical efficiency of each company and the scale of DMU by applying CCR or BBC model. Also, we analyzed the changes of measurement DEA model score. we adopted the basic DEA, RTS Region and MPSS(Most Productive Scale Size) method which are combined with efficiency measurement model in order to analyze the operational status. Furthermore, by complementing the shortfalls of the scale efficiency value of the DEA Model, RTS Region Model can be recommended to be appropriate in the evaluation of ideal input/output Quantity. In particular, input variables are total assets, construction capacity, the technical staff and output variables are sales volume, operating income. The result of RTS Region and MPSS shows that 9 DMUs of the efficiency frontier in the Construction Industry are analyzed to be relatively efficient DMUs, and 41 DMUs are analyzed to be inefficient DMUs, and finally inefficient DMUs are separated with Region 1 and Region 6.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.31 no.2
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• pp.94-103
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• 2008

This study measured technology transfer efficiency for public institutes. The study made use of DEA being one of the non-parametric linear programming to evaluate technology transfer efficiency for public institutes and to measure technology efficiency, pure technical efficiency and scale efficiency. The measurement of the technology transfer efficiency for public institutes was as follows: The cause of the technology transfer inefficiency was affected by pure technical inefficiency more than by scale inefficiency. Public institutes' RTS(Return To Scale) value varied depending upon the features of the organizations than the features of the regions. Public research institutes' RTS value is more effective than universities' RTS value. We compared the RTS group with the RTS of Projected DMU groups. The RTS group had constant returns to scale effect while the RTS of the Projected DMU had increasing returns to scale effect. The technology transfer efficiency of public institutes varied depending upon the features of the organizations and regions : The technology transfer efficiency of public institutes were as follows : public research institutes at the metropolitan area, public research institutes at the local areas, universities at the metropolitan area and universities at the local areas. In other words, the technology transfer efficiency was affected by organizational characteristics more than by regional characteristics at the place where public institutes were located.