• Title/Summary/Keyword: 기술적 효율성

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Patterns and Determinants of Productive Efficiency in Korean Manufacturing Firms during Trade Liberalization (우리 나라 제조업의 생산적 효율성 결정요인분석-무역자유화 기간을 중심으로-)

  • 서동석
    • Journal of Technology Innovation
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    • v.3 no.1
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    • pp.157-184
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    • 1995
  • 본 연구는 한국 제조업의 기업별 <패널>자료를 이용하여 확율 적 생산함수를 추정한 다음, 우리 나라의 주종 수출산업인 섬유산업과 전자산업의 기술적 효율성이 1980년대에 하락한 이유를 규명하기 위하여 동종산업내의 각 기업들의 기술적 효율성의 결정요인을 계량분석을 통해 분석하였다. 성장산업인 전자산업과 사양산업인 섬유산업의 산업 내 (intra-industry) 기술적 효율성의 결정요인은 상하였다. 성장산업인 전자산업의 경우, 상대적인 기업의 크기와 노동비용의 상대적 크기는 기술적 효율성과 각각 정의 관계를 보이고 있는데 비해, 사양산업인 섬유산업의 경우, 총 매출액에서 수출이 차지하는 비중과 기술적 효율성과 반의 관계를 보였다. 즉 1980년대 섬유산업의 기술적 효율성이 하락한 중요한 요인은 동 산업의 수출부진과 상대적인 노동비용의 상승을 들 수 있으며, 성장산업인 전자산업의 경우는 일부 대기업의 집중도 심화가 동 산업의 평균적 기술적 효율성의 하락요인이 되었음을 알 수 있다. 따라서 본 연구는 경쟁의 촉진과 기업 집중도의 완화가 기술적 효율성을 향상시키는 데 중요하다는 점을 보여주고 있다.

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An Analysis of the Technical Efficiency of Industrial Water Input in Manufacturing (공업용수의 기술적 효율성 분석)

  • Min, Dong-Ki
    • 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.

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The Study on the Technical Efficiency of Industrial Water in Manufacturing (공업용수 투입의 기술적 효율성 분석)

  • Min, Dong-Ki
    • Journal of Korea Water Resources Association
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    • v.41 no.6
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    • pp.597-603
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    • 2008
  • This paper estimates technical efficiency of industrial water in order to afford some information for improving the efficiency of government water management policy. To estimate technical efficiency, this paper uses data envelopment analysis. The result shows that the average pure technical efficiency of industrial water is 0.407. This estimate is less than the estimates when all inputs are considered as variables in the previous researches. This result means that the managers may have not tried to improve the efficiency of industrial water usage since the cost for industrial water is trivial compared to other inputs. In addition, this result shows that the previous researches which assume that all inputs are used in efficient way may give a biased results.

An Analysis of Technical Efficiency in Korean RCC/RSC (우리나라 RCC/RSC별 운영효율성 분석)

  • Jang Woon-Jae;Keum Jong-Soo
    • Proceedings of the Korean Institute of Navigation and Port Research Conference
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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.

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A performance analysis of R&D in the IT industry sector (IT 기업 R&D 투자의 효율성 분석)

  • 김상태;표경민
    • Proceedings of the Korea Technology Innovation Society Conference
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    • pp.521-532
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    • 2005
  • IT 기업의 기술적 효율성의 정도를 추정하고, 그 결정요인을 알아보기 위해 Coelli(1995)의 확률적프론티어(Stochastic Frontier model) 중 초월대수 변경생산함수(translog stochastic frontier production function)를 설정한다. 분석견과 연구개발투자, 기업의 재무구조, 설비투자효율, 노동소득분배율 등은 기업의 비효율을 감소시키는 역할을 하는 반면, 기업규모, 재고자산증가율, 자기자본증가율 등은 기업의 비효율성을 더 높여주는 것으로 나타났다. 1990년부터 2004년까지 국내 제조업 전체의 생산의 기술적 효율성은 평균 0.5311로 이는 생산효율성이 $53.11\%$임을 의미하고, 비효율성은 $46.89\%$에 달한다고 볼 수 있다. IT 기업의 기술적 효율성은 0.5337회 제조업과 비슷하지만, IT 대기업은 0.61, IT 중소기업은 0.511로 대기업과 중소기업의 격차가 크게 발생하고 있다.

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A Study on the CO2 Reduction Potential by Means of Increased Efficiency of the Electricity (제조업 전력 사용 효율성 제고를 통한 온실가스(CO2) 감축 잠재량 추정에 관한 연구)

  • Min, Dong-Ki
    • Journal of Environmental Policy
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    • v.9 no.3
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    • pp.143-160
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    • 2010
  • This paper estimate the $CO_2$ reduction potential that can be achieved by improving the technical efficiency of input factors in the manufacturing sector. Technical efficiency in each manufacturing firm was estimated using the DEA technique. Depending on the returns-to-scale assumption selected, average technical efficiency was estimated to be between 0.467 and 0.643. These estimates suggest that, when the efficiency of electricity consumption in the manufacturing sector is improved, the overall $CO_2$ emissions can be reduced by 17.1-25.5%. Recently, the Korean government has adopted a low-carbon-green-growth policy with the goal of reducing greenhouse gas emissions by 30% below the BAU level by year 2020. The analysis of the paper suggests that this goal can be achieved through improved efficiency of electricity consumption.

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An Analysis of Technical Efficiency in the Korean RCC/RSC (RCC/RSC별 운영 효율성 분석)

  • Keum Jong-Soo;Jang Woon- Jae
    • Journal of Navigation and Port Research
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    • v.29 no.3
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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.

A Trend Analysis on Scale Efficiency of the Port of Gwangyang: 1994-2004 (광양항의 규모효율성 추세분석: 1994-2004)

  • Park, Ro-Kyung
    • 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.

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International Comparative Analysis of Technical efficiency in Korean Manufacturing Industry (한국 제조업의 기술적 효율성 국제 비교 분석)

  • Lee, Dong-Joo
    • Korea Trade Review
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    • v.42 no.5
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    • pp.137-159
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    • 2017
  • This study divides manufacturing in 18 countries including Korea, China, Japan and OECD countries into 11 areas and estimates and compares the technological efficiency of each industry. The traditional view of productivity is to increase production capacity through technological innovation or process innovation, but it is also influenced by the technological efficiency of production process. A Stochastic Frontier Production Model (SFM) is a representative method for estimating the technical efficiency of such production. First, as a result of estimating the production function by setting the output variable as total output or value-added, in both cases, the output increased significantly in all manufacturing sectors as inputs of labor, capital, and intermediate increased. On the other hand, R&D investment has a large impact on output in chemical, electronics, and machinery industries. Next, as a result of estimating the technological efficiency through the production function, when the total output is set as the output variable, the overall average of each sector is 0.8 or more, showing mostly high efficiency. However, when value-added was set, Japan had the highest level in most manufacturing sectors, while other countries were lower than the efficiency of the total output. Comparing the three countries of Korea, China and Japan, Japan showed the highest efficiency in most manufacturing sectors, and Korea was about half or one third of Japan and China was lower than Korea. However, in the food and electronics sectors, China is higher than Korea, indicating that China's production efficiency has greatly improved. As such, Korea is not able to narrow its gap with Japan relatively faster than China's rapid growth. Therefore, various policy supports are needed to promote technology development. In addition, in order to improve manufacturing productivity, it is necessary to shift to an economic structure that can raise technological efficiency as well as technology development.

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Analysis of Technical Efficiency in Online and Digital Content Industry (온라인 및 디지털 콘텐츠 산업의 기술적 효율성 분석)

  • So, Soon-Hu;Lee, Mi-na
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • pp.128-130
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    • 2016
  • The digital content industry is growing rapidly with the popularity of online content and mobile devices. This study estimates the technical efficiency of the online digital content industry, and identifies factors that could be causing inefficiency. Unlike most previous studies, which adopted input-oriented or output-oriented DEA model, this study employs non-oriented DEA model in order to deal with both input surpluses and output shortfalls. The input variables for the empirical analysis are number of companies and number of workers. The total sales is used as the output variables. The empirical results show that the technical efficiency of the online digital content industry is relatively low mainly due to the scale efficiency rather than the pure technical efficiency. This implies that industry-specific policies should be implemented in order to improve technical efficiency as well as to strengthen technological innovation capability. Therefore, it is expected that the results obtained in this study can be used as a good reference for helping the online digital content industry enhance their competitiveness.

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