• Journal of Technology Innovation
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• v.22 no.1
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• pp.1-22
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• 2014

R&D investment also has a gestation period similar to other investments in economics. The gestation period originates from time lag effect of input and output. Thus it is necessary to consider time lag effects when analyzing the relationship between firms' R&D investment and R&D performance. The main objective of this research is to estimate the length of time lag effect of R&D investment. The Almon distribution lag model was applied to estimate the time lag effect. The firm level panel dataset was established from 2002 to 2009. The net value of R&D investment and the number of patent applications were used to measure R&D input and output, respectively. This method found the estimated time lag to be 1~2 years across all datasets. The same analyses were applied to chemical, metal, electronic, exact science, and machinery industries' data. And we found there were differences among sectors in regard to the time lag effect.

• The Journal of the Korea Contents Association
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• v.22 no.8
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• pp.287-296
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• 2022

The purpose of this study is to verify the effect of government subsidies and R&D investment on the increase in profits of Chinese environmental protection companies. The research method for this was empirically analyzed using the Chinese CSMAR database for 161 Chinese environmental protection companies and using statistical data obtained from 805 samples. The analysis results are as follows. First, government subsidies had a positive effect on the increase in profits of Chinese environmental protection companies. Second, government subsidies had a positive effect on R&D investment by Chinese environmental protection companies. Third, R&D investment had a positive effect on the increase in profits of Chinese environmental protection companies. Fourth, R&D investment through government subsidies has a partial mediating effect on the effect on the increase in profits of Chinese environmental protection companies. In this study, based on the results of the study, a plan was proposed to promote the increase in profits of Chinese environmental protection companies by expanding government subsidies to Chinese environmental protection companies and focusing on R&D investment.

• Journal of Technology Innovation
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• v.24 no.3
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• pp.81-105
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• 2016

The purpose of this study is to estimate the cost-saving effect of R&D investment in the ICT industry. As is well known, the R&D investment induces both the product innovation and the process innovation, in turn leads the effect of creating profit and cutting cost. However, it appears that studies concerned with the cost-saving effect of R&D investment have been unproductive, while most existing studies concentrate on the topic involved with the creating profit of R&D investment. Therefore, we extend the effect of R&D investment to a framework of the cost-saving focusing on the ICT industry. To empirically analyze the effect, we built a simultaneous three-equation model comprising a translog cost function and two cost share equations, and employed the SUR analysis. As a result, we found out that the cost-saving effect on the total cost is statistically significant. In addition, we examined relationships between the R&D investment and each cost of production elements. The results show that on the one hand, the R&D investment and the intermediate good cost have the substitution relationship. On the other hand, the complementary relationship is observed between the R&D investment and each labor or capital cost.

• Korean System Dynamics Review
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• v.15 no.2
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• pp.27-50
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• 2014

Korea government established the energy technology development plan (2011-2020) and declared to be a leader of the green energy technologies. The plan aims for 10% market share in the green energy industry, 12% energy efficiency improvement, and 15% greenhouse gas reduction. In order to achieve these goals, the government has tried to calculate the whole scale of national energy R&D investment, annual budget and specific expenditures for new technologies by computer simulation. The simulation modules include the R&D investment model, GDP model, energy consumption and $CO_2$ emission model by System Dynamics. Based on these simulation modules, I tested various scenarios for effectiveness of energy R&D investments until 2020. The results show that Korea should increase national energy R&D investment to 2.3 billion U.S. dollars, and switch the investment from electricity and nuclear power to the renewable energy.

• Proceedings of the KSR Conference
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• 2009.05a
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• pp.791-794
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• 2009

Each nation of the world is intensively propelling the R&D investment to solve the financial crisis and worldwide economic recession occurred from last year. This means the world economic is under economic system based on the knowledge. So, The R&D is continuously propelled for possession of the technology through the R&D stock and which is core in the knowledge based economic system. In this world stream, our government is also increasing the R&D investment and checked the technology level through surveying the R&D stock and corn parison of each industry or world. The R&D investment of the railroad is continued but there is no data of the R&D stock. So, surveying the railroad R&D stock and comparing with korea industry is processed.

• International Area Studies Review
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• v.18 no.3
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• pp.175-201
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• 2014

This paper analyses the effect of R&D investment on local economies. R&D investment contributes to the regional local economy by increasing employment and production activity of the investees. The investees may end up with increased productivity, sales and employment. At the regional R&D level, the central government R&D fund and firm self R&D budget will be the source of R&D investment. Further positive effects are inter-related with local industries. This study carried out an empirical analysis on the effect of R&D investment on local economies using Korean panel data after comparing international literatures. The dynamic panel estimator is used to estimate an autoregressive model with lagged dependent variable. Using the Da Silva method, mixed variance-component moving-average error process is estimated and selected. R&D investment is very important factor to improve the productivity of a region and the size of the effect is dependent on the time periods within the Korean economic history.

• Proceedings of the Safety Management and Science Conference
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• 2003.05a
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• pp.245-253
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• 2003

In general, manufacture of medicine has demerit of long period in investment effect, high risk, expensiveness through new drug development. At empirical test, R&D investment for new drug development positively affects on profit in manufacture of medicine. In Korea, effect on R&D investment in manufacture of medicine occur faster than previous period. Manufacture of medicine is value added industry, compared to other industries. Moreover, U.S & Japan in R&D expenditure on sales respectively has 10.1%, 8.07%. This is 3-4 times, compared to R&D expenditure on sales of Korea. Conclusionally, the importance of R&D investment increase more and more in future. So, manufacture of medicine and Companies related this will care for R&D investment.

• Korean Management Science Review
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• v.16 no.1
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• pp.63-74
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• 1999

This paper presents a R&D investment model for the Information and telecommunications(l&T) technology using multiple objective linear programming(MOLP). The MOLP model involves the simultaneous maximization of three linear objective functions associated with three criteria, which are social, technological, and economic criterion. This model is different from the traditional one which only involves the maximization of economic criterion. It yields a suitable R&D investment ratio to each technology field. Its application to the National R&D Project in l&t Industry is also presented. In this application, the Analytic Hierarchy Process(AHP) is proposed to estimate the weights, which used as the coefficients in each objective function of the MOLP model. Then the problem is solved using the interactive method STEM. It is showed that with the aid of STEM, the MOLP model can be useful decision aid in formulation R&D investment plan in l&t industry. It is expected that the MOLP model works as the basis for planning R&D investment strategy in l&T industry.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.12 no.7
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• pp.3053-3061
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• 2011

This study examines the relationship between R&D(research & development) investment and market value among KOSDAQ firms in the Korea Stock Exchange. We investigate the effect of R&D investment on firm value in both total sample and sub-samples classified by firm characteristics based on types of firms. And we study the impact of a major economic disruption as the global financial crisis triggered by sub-prime mortgage problem in the US on R&D investment relative to the firm value. We find that R&D investment positively affects firm value and the squared term of R&D investment is found to be significant and negatively correlated with market value. This suggests the presence of nonlinear relationship like a reverse U-shape between R&D investment and market value in total sample and most of sub-samples. And we find firm characteristics and global financial crisis partially affect the contribution of R&D investment to market value in some of sub-samples.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.42 no.2
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• pp.62-68
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• 2019

The growth and employment effects of R&D investment were analyzed according to business size, export value and manufacturing sectors so as to suggest improvement directions for effective industry policies. The effect of R&D investment was considered simultaneously from the two perspectives of growth and employment effect, and the causality analysis was carried out by using a path analysis. The result of the path analysis confirmed significant differences in the growth effect of R&D investment depending on business size. However, the effect of increasing employment was difficult to obtain statistically significant results for any various combinations of business size and export value. This is a mixture of directions for the effects of R&D investment on employment, which could be due to the failure to consider appropriate time lags between investment and effect. Efficiency analysis by industry sectors confirmed significant differences in efficiency depending on business size, but differences depending on export value were difficult to identify. In order to derive improvement policy by industry sector according to business size and export value, the direction of selective support policy and universal support policy was derived for six industry groups by combining the return to scale in the efficiency analysis and R&D concentration. Hirschman-Herfindahl index is used for calculating R&D concentration.