• International Area Studies Review
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• v.14 no.2
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• pp.43-60
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• 2010

This paper measures R&D efficiency and productivity changes of 24 nations including Korea, Japan and China by the non-parametric Malmquist productivity index. The principle findings of this study are as follows. First, R&D efficiency scores of Korea and Japan are 0.837 and 0.834 respectively. Meanwhile China shows 0.420, the worst performance among the selected countries. Second, Korea marked annual productivity increase of 25%, highest among the selected countries', for 2000-2005. R&D productivity in Japan and China, however, decreased 1.9% and 0.9% respectively. Third, annual rates of technology change and technical efficiency change in Japan are 0.6% and -2.5%. Therefore decrease of productivity in Japan is mainly due to technical inefficiency. In case of China, improvement of technical efficiency is the main contributor to productivity growth but technical progress has edged downward in the sample period. In Korea, with annual rate of technology change and technical efficiency change being 5.2% and 18.2% respectively, both efficiency improvement and technical progress has pulled the R&D productivity growth.

• 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.

• 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.

• 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 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.

• Journal of Digital Convergence
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• v.17 no.12
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• pp.129-137
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• 2019

The purpose of this study is to analyze the efficiency of budget utilization of science and technology by the Chinese autonomous province and to present the direction of improvement. Data were obtained from the 2013-2017 statistical yearbook of higher education published by the Ministry of Education of China, and efficiency was analyzed using the malmquist analysis method. The analysis found that the low technological progress caused changes in the productivity MPI index, and that cities affected by technological efficiency needed to improve internal factors such as internal coordination and restructuring of universities in the region to increase efficiency. And it was found that areas affected by technological change needed proper response to external factors such as government policy, economic environment, social environment or technological development. This study is meaningful in that it presented reference data in enhancing efficiency of budget utilization of science and technology by autonomy of China, and it is necessary to establish strategies and study essential factors to increase efficiency of inefficient areas in the future.

• Journal of Environmental Policy
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• v.8 no.4
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• pp.37-49
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• 2009

While water management policies in Korea have focused on industrial water demand during the last decade, the amount of industrial water usage has decreased significantly. This paper estimates the technical efficiency of industrial water in order to test whether the reduction of industrial water usage is a result of improving the level of technical efficiency of industrial water. This paper shows that the technical efficiency of industrial water use slightly decreased from 0.5183 in 1998 to 0.4853 in 2003. In addition, these estimates are much less than those of other inputs and so, there is still much room for reducing the amount of industrial water use through improving technical efficiency even though the average productivity of industrial water has improved during this period.

• Journal of Technology Innovation
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• v.29 no.3
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• pp.33-62
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• 2021

This study compares and analyzes the efficiency of R&D activities of technology-innovative small and medium-sized enterprises(SMEs) between industries and proposes ways to improve efficiency. The research samples are 6,708 technology-innovative SMEs, which have received a guarantee by the KIBO from 2008 to 2011. Input variables are the level of R&D personnel, R&D investment, and output variables are patent applications, prototype. Efficiency is measured by the DEA model, and indirect comparisons that are individually measured by industry are performed. As a result of the analysis, the CCR for determining the optimal returns to scale is 0.19, the BCC for determining the optimal input distribution is 0.70, and the SE for determining the optimal output is 0.30. By industry type, the medium and low-tech industries have high CCR and BCC, while the high-end and high-tech industries have high SE. R&D activities need to be operated on an optimal scale through managing R&D performance because there is the inefficiency of scale across the industry. The contribution of the study is to analyze the R&D efficiency of each industry of technology-innovative SMEs by the technology evaluation data of the KIBO.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.5 no.2
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• pp.191-196
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• 2004

Allocative efficiency measures the extents to which the technically efficient units falls shorts of achieving minimal cost. By using this measure manager can make decision about how to redistribute organizational resources to improve price efficiency. Allocative and overall efficiency are derived on the basis of budget line and cost minimization concept. The purpose of this study is to introduce the concept of allocative efficiency and propose two modified DEA models. Examples are provided to illustrate the similarities and the application procedure of the two model. By providing example and tracing the data application procedure, we found the same results but some cautions are needed to interpret the valuation.

• Journal of Korean Library and Information Science Society
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• v.41 no.4
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• pp.35-50
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• 2010

The purpose of this study was to analyse the ralative efficiency of 15 public libraries over a time period(2006-2008) by Data Envelopment Analysis(DEA). The selected input variables were total staff, total area and total holdings. And the selected output variables were total circulations and total user. The results are as followed. First, a technical efficiency trend of public libraries has been improved since 2006. Second, a technical efficiency increase can be explained by increase of a pure technical and scale efficiency both.