• Journal of the Korean Regional Science Association
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• v.33 no.1
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• pp.3-16
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• 2017

This paper analyzed 16 regional total factor energy efficiency (TFEE) of the Korean manufacturing sector using data envelopment analysis method for the period of 2005-2013. According to the empirical results, it is necessary to use TFEE as well as partial energy efficiency defined by the ratio of energy usage to output (energy intensity) when we compare energy efficiency. Secondly, TFEE in the Korean manufacturing sector is quite different across 16 regions. For example, Gangwon province should improve energy efficiency by 55% compared to Seoul, Gwangju, Ulsan, and Gyeongbuk which are located on production frontier. Furthermore, the estimation of panel tobit regression model showed that the higher non fossil fuel using, the higher production share of large-sized firms, the lower energy intensity, and the lower capital-labor ratio could have positive effect on TFEE.

• Proceedings of the Korea Water Resources Association Conference
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• 2011.05a
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• pp.362-365
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• 2011

단위면적당 증발산량 중 일부가 식생의 물질 생산에 이용될 수 있는지를 나타내는 지표인 수분 이용효율 (Water Use Efficiency, WUE)은 총 일차생산성(Gross Primary Productivity, GPP)과 단위면적당 증발산량(Evapotranspiration, ET)의 비로 산출된다. 이전 연구들에서의 수분 이용효율의 적용은 수분 스트레스에 대한 작물의 생산성 차이 분석과 같은 작물학과 농림학 분야의 연구들이 대부분이었지만. 기후 변화가 생태계 생산성 또는 에너지 수지에 영향을 미치는 등의 전 지구적 규모의 수문학적 연구에도 적용할 수 있다. 본 연구에서는, Moderate Resolution Imaging Spectroradiometer (MODIS) 영상자료에서 1km 해상도로 8일 단위의 총 일차생산성과 증발산량을 산정함으로써 수분 이용효율을 구하였다. 향후에는 산정된 이 지표를 남한지역에 적용하여 수분 이용효율에 대한 지도를 작성하고, 실측된 총 일차생산량과 증발산 값을 이용하여 검증한 후 알고리즘을 개선해 나갈 계획이다.

• Journal of Korea Port Economic Association
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• v.24 no.4
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• pp.47-70
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• 2008

The purpose of this study is to estimate total factor productivity(TFP) growth by stochastic frontier function and to grasp contributing factors of its growth rate by decomposing the total factor productivity into efficiency change, technical progress, scale change, and allocation change. Annual growth rate of total factor productivity for 1990-2003 is 0.019 (1.9%), higher than that of overall industry (0.010). The main component of TFP growth is not efficiency change but technical progress. Contributing factors of total factor productivity growth are change of allocation efficiency in port industry, technical progress in sea-transportation industry, and change of scale efficiency in transportation-equipment industry. The change of total factor productivity shows a decreasing trend since late in the 1990s. The annual technical efficiency of port-logistics industry is less than that of overall industry. Capital elasticity for output (0.391) is higher than labor elasticity (0.227), but scale economy of port-logistics industry is 0.618, which is far from optimal scale economy.

• 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.

• Korean Journal of Environmental Agriculture
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• v.28 no.2
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• pp.97-105
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• 2009

A constructed wetland which was composed of aerobic and anaerobic areas was evaluated for 3 years to effectively treat the sewage produced in farming and fishing communities. For 3 years in a constructed wetland, biochemical oxygen demand(BOD), chemical oxygen demand(COD), suspended solids(SS), total nitrogen(T-N), and total phosphorus(T-P) in effluent were 0.2${\sim}$11.8, 1.0${\sim}$41.9, 1.1${\sim}$6.5, 4${\sim}$60 and 0.02${\sim}$3.51 mg/L, respectively. Removal rate of BOD, COD and SS in effluent were 97, 92 and 99%, respectively, in the third year. As time goes by, removal rate of T-N and T-P in treated water in aerobic area and effluent were gradually increased in a constructed wetland. In the third year, removal rate in effluent were 62 and 73%, respectively. By the seasons, removal rate of BOD, COD, SS, T-N and T-P were 97${\sim}$98, 87${\sim}$91, 99, 43${\sim}$61 and 76${\sim}$86%, respectively. Removal rate of BOD, COD, SS and T-P were not affected by the seasons, but that of T-N in winter and spring were decreased than the other seasons.

• The Journal of the Korea Contents Association
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• v.20 no.2
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• pp.27-35
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• 2020

The Korean semiconductor industry is the top export item, and its technological prowess is also higher than that of its competitors. However, the technology gap with rivals will narrow. And the semiconductor industry is facing difficulties due to trade friction. Therefore, semiconductor firms should be more efficient in their production. we study analyzes the efficiency semiconductor firms using DEA model. We evaluate the CCR, BBC efficiency and RTS(return to scale) of 30 Korean semiconductor firms. There are a total of 13 efficient DMUs with a BCC of 1. There are a total of 6 efficient DMUs with a CCR of 1. A total of 10 DMUs were IRS in Scale Efficiency and a total of 9 DMUs were CRS in Scale Efficiency and a total of 11 DMUs were DRS in Scale Efficiency. We also suggest the semiconductor firms which can be benchmarked based on analyzed information.

• The Journal of the Korea Contents Association
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• v.19 no.8
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• pp.151-158
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• 2019

The high-technological in the electric and electronic industries is recognized in overseas markets as well. However, the competition for technologies in these industries is increasing. Therefore, electric and electronic firms should be more efficient in their production. so, This paper analyzes the efficiency of High-growth Electrical and Electronics firms using DEA model. We evaluate the CCR, BBC efficiency and RTS(return to scale) of 20 Korean high-growth Electrical and Electronics firms. There are a total of 12 efficient DMUs with a BCC of 1. There are a total of 4 efficient DMUs with a CCR of 1. A total of 11 DMUs were IRS in Scale Efficiency and a total of 6 DMUs were CRS in Scale Efficiency and a total of 3 DMUs were DRS in Scale Efficiency. We also suggest the Electrical and Electronics firms which can be benchmarked based on analyzed information.

• Environmental engineer
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• s.41
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• pp.28-32
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• 1990

본 실험은 S유가공 공장에서 생성되는 폐수의 각종 오염물질 계절별 처리효율 원유처리량에 따른 폐수량 오염물질간의 상관관계 등을 조사하기 위하여 1998.2월부터 1989.1월까지 1년간 매월 2회씩 총 24회에 걸쳐서 조사분석하였으며 그 결과를 요약하면 다음과 같다. 1. 원 폐수의 총 오염물질량(BOD, COD, SS n-Hexan, nitrogen compound $PO_4P$)은 평균 1870.9 ug/일이며 최종처리후 117.

• Journal of Korean Society of Transportation
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• v.28 no.5
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• pp.43-54
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• 2010

In order to improve the existing evaluation system of bus services and gain more reasonable analysis outputs, the authors evaluate the efficiency of 113 arterial bus routes in Seoul in 2009 using a modified BCC model considering not only desirable outputs but also undesirable outputs. Each Decision Making Unit (DMU) is assumed to use inputs such as possession costs, operating costs, the ratios of median bus stops overlapped route lengths to produce estimates of desirable outputs (the number of passengers and service satisfaction score) and undesirable outputs (CO2 emissions). According to the analysis, the modified BCC model considering both desirable outputs and undesirable outputs shows more appropriate results. DMUs would be more efficient on average to reduce nearly 10% of the 3 inputs (possession costs, operating costs, and overlapped route lengths) and increase by about 160% the ratios of median bus stops. Also, a Tobit regression analysis is conducted to identify the most effective variables for maximum efficiency and discover that the variable of possession costs and the ratios of median bus stops are statistically significant.

• The Science & Technology
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• no.1 s.416
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• pp.100-103
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• 2004