• Proceedings of the Korean Society for Quality Management Conference
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• 2004.04a
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• pp.9-12
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• 2004

본 논문에서는 기존 프로젝트 선정에 이용되던 COPQ, VOC/VOB 방식대신 기업의 총생산성에 많은 기여를 하는 프로젝트를 도출, 선정할 수 있도록 하는 TP 전개(Deployment) 방식의 프로젝트 도출, 선정 방안을 제안하고자한다.

• Environmental and Resource Economics Review
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• v.5 no.2
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• pp.279-290
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• 1996

정부의 환경규제로 인하여 한국 제조업의 기업들이 공해방지시설을 의무적으로 설치해야할 경우, 이는 생산비증가와 신규투자의 위축 및 생산요소간 조합비율에 영향을 미침으로써 직 간접적으로 생산성의 감소를 초래한다. 본 연구에서는 인과추정법(因果推定法)으로 측정한 그레이 (Gray, 1987)의 모형을 통하여 환경규제가 한국 제조업의 생산성에 미치는 효과를 측정하였다. 측정결과, 규제로 인하여 연평균 0.58퍼센트 포인트만큼의 생산성감소효과가 있었다. 여기에는 생산성증가율 계산상의 '측정효과(測定效果)'만 존재하고 생산과정의 제약, 신규투자의 위축, 다른 생산요소의 생산성감소로 인하여 총생산성이 감소되는 '실질효과(實質效果)'는 발생하지 않았다.

• Environmental and Resource Economics Review
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• v.25 no.2
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• pp.277-297
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• 2016

This study is to analyze the effects of changing pattern of climate vaariables on total factor productivity of Korea manufacture industry. Changes in temperature, rainfalls and humidity which are the representative climate variables are used as main factors. Not only average values of the variables but those highest values are used as independent variables in the model, in order to consider the characteristic pattern of recent climate change, the high volatilities. The OLS results are unlike to previous literature that temperature and humidity had no significant impact on manufacturing productivity. An increase in the amount of precipitation was analyzed that impact negatively impacted. The analysis of panel data showed that temperatures and precipitation all that does not significantly affect the manufacturing. While the increase of the average humidity is shown to increase the total productivity of manufacture industry. In Korea, adaptation capability is important in determining the effects of climate change on productivity of manufacture industry.

• KDI Journal of Economic Policy
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• v.12 no.4
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• pp.3-20
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• 1990

The multisector model is designed to analyze and forecast structural change in industrial output, employment, capital and relative price as well as macroeconomic change in aggregate income, interest rate, etc. This model has 25 industrial sectors, containing about 1,300 equations. Therefore, this model is characterized by detailed structural disaggregation at the sectoral level. Individual industries are based on many of the economic relationships in the model. This is what distinguishes a multisector model from a macroeconomic model. Each industry is a behavioral agent in the model for industrial investment, employment, prices, wages, and intermediate demand. The strength of the model lies in the simulating the interactions between different industries. The result of its simulation will be introduced in the next paper. In this paper, we only introduce the structure of the multisector model and the coefficients of the equations. The multisector model is a dynamic model-that is, it solves year by year into the future using its own solutions for earlier years. The development of a dynamic, year-by-year solution allows us to combine the change in structure with a consideration of the dynamic adjustment required. These dynamics have obvious advantages in the use of the multisector model for industrial planning. The multisector model is a medium-term and long-term model. Whereas a short-term model can taken the labor supply and capital stock as given, a long-term model must acknowledge that these are determined endogenously. Changes in the medium-term can be analyzed in the context of long-term structural changes. The structure of this model can be summarized as follow. The difference in domestic and world prices affects industrial structure and the pattern of international trade; domestic output and factor price affect factor demand; factor demand and factor price affect industrial income; industrial income and relative price affect industrial consumption. Technical progress, as measured in terms of total factor productivity and relative price affect input-output coefficients; input-output coefficients and relative price determine the industrial input cost; input cost and import price determine domestic price. The differences in productivity and wage growth among different industries affect the relative price.

• Journal of Korea Port Economic Association
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• v.25 no.2
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• pp.277-300
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• 2009

By using data envelopment analysis(DEA) this research measures the efficiency of Korea's seven middle-sized seaports and their Malmquist productivity from 1998 to 2007. Under the assumption of CRS(constant returns to scale) and VRS(variable returns to scale), seaports' ranking of efficiency are measured. Kunsan Port is confirmed as a middle-performed port in the various measurements. Important finding facts are as follows. 1)Kunsan Port has the efficiency level from 53% to 57% of efficient ports' level under the assumption of CRS and VRS. 2)In terms of average efficiency level, the gap among these 7 seports' efficiency levels has been widened during the period from 1998 to 2007. 3)Kunsan Port has shown the characteristics of DRS more frequently in terms of returns to scale. 4) Kunsan Port's average total factor productivity has been lower at the rate of 0.7% during the period from 1998 to 2007. 5)Kunsan Port has shown technical progress at the rate of 3.1% in this period. In future research the more and better data will be expected to improve the understanding of Korean seaports' efficiency characteristics.

• The Journal of the Korea Contents Association
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• v.10 no.5
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• pp.303-313
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• 2010

The purpose of this study is to evaluate the performance efficiency and productivity change of the regional public hospital in Korea. We use DEA(Data Envelopment Analysis) for CCR, BCC model, and MPI(Malmquist Productivity Index). DEA is a useful nonparametric technique for measurement of efficiency of a DMU(Decision Making Unit) and MPI is a evaluation method to measure DMU's productivity change. We utilize 34 regional public hospital's time-series data over 6 years from 2003 to 2008.The results of this study were as follows. First, technical efficiency(TE) 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, MPI's results show that regional public hospital made effort to improve total factor productivity change to raise technical efficiency. In order to raise efficiency, the regional public hospitals should deploy internal innovation and the government should support welfare policies.

• Applied Biological Chemistry
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• v.2
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• pp.5-7
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• 1961

근년(近年) 경기도(京畿道)및 충청남북도(忠淸南北道) 일부지방(一部地方)에 ‘벌보리’ (대맥불임중(大麥不稔症)의 발생(發生)이 알려졌고 4293년(年) 봄에는 본장(本場)의 신개간지(新開墾地)에서도 不稔麥이 생겼으므로 이 토양(土壤)을 공시(供試)하여 석회(石灰)를 시용(施用)하고 붕소(硼素)와 용성인비(熔性燐肥), 퇴비(堆肥) 및 저니토등(底泥土等)을 시용(施用)하여 시험(試驗)을 실시(實施)하였다. 한편 같은 현상(現狀)이 산성(産生)된 충청북도(忠淸北道) 농사원(農事院) 의 원내포장(院內圃場) 석회전시(石灰展示) 포적지(圃跡地)에서 이의 방제(防除)를 시도(試圖)코 붕소(硼素)를 대맥생육중(大麥生育中)에 엽면시비(葉面施肥)하여 좋은 결과(結果)를 얻었다. 여기서는 이들 처리(處理)로 얻어진 임실도(稔實度)와 맥간중(麥桿中)의 붕소량(硼素量)을 조사분석(調査分析)하였고 그 결과(結果)는 다음과 같다. 1. 붕소(硼素)의 토양시용(土壤施用)은 추파대맥(秋播大麥)의 총생(叢生)을 억제(抑制)할 뿐만아니라 인실도증가(引實度增加)에 유효(有效)하였으며 붕소(硼素)의 엽면시비(葉面施肥)도 대맥붕실도(大麥硼實度)를 증가(增加)시켰다. 2. 부임도(不稔度)가 높은 각구(各區)의 식물체중(植物體中) 붕소함량(硼素含量)은 1ppm내외(內外)였으며 임실(稔實)이 잘된 붕소구(硼素區)에서는 10mm이였다. 그러나 시용(施用)한 붕소량(硼素量)은 대맥(大麥)의 생육기간중(生育期間中), 엽면(葉面)에 흑색반점(黑色斑點)이 나타날 정도(程度)의 과량(過量)이었다. 붕소(硼素)의 엽면시비(葉面施肥)는 상기(上記)와 같은 현상(現象)이 나타나지 않았으며 붕소함량(硼素含量)은 3.5ppm이였다.