• Clean Technology
• /
• v.17 no.2
• /
• pp.181-188
• /
• 2011

In this study, the complementary or crowding-out effects of public R&D subsidy on private R&D investment in the cleaner production were analysed between the effects and the major determinants (company size, R&D investment intensity, ratio of government investment, R&D manpower intensity). Among 207 firms' projects, the number of the complementary effect was 95 (45.9%) while that of crowding-out effect was 38 (18.4%). Resulting from logistic regression, the higher the R&D investment of sponsored companies is, the more complementary effect they show, responding to public R&D subsidy, and increase own R&D investment. The other determinants, however, showed no significant effects on firms' R&D investment. To heighten the effect of public cleaner production R&D, it is need to increase the priority of R&D investment intensity among the determinants. And to increase the performance of governmental R&D investment, further studies for the individual public R&D programs are necessary.

• Korean Journal of Construction Engineering and Management
• /
• v.14 no.2
• /
• pp.131-140
• /
• 2013

Econometric forecast models based on past time-series data have been applied to a wide variety of applications due to their advantages in short-term point estimating. These models are particularly used in predicting the impact of governmental research and development (R&D) programs because program managers should assert their feasibility due to R&D program's huge amount of budget. The construction governmental R&D programs, however, separately make an investment by dividing total budget into five sub-business area. It make R&D program managers difficult to understand how R&D programs affect the whole system including economy because they are restricted with regard to many dependent and dynamic variables. In this regard, system dynamics (SD) model provides an analytic solution for complex, nonlinear, and dynamic systems such as the impacts of R&D programs by focusing on interactions among variables and understanding their structures. This research, therefore, developed SD model to capture the different impacts of five construction R&D sub-business by considering different characteristics of sub-business area. To overcome the SD's disadvantages in point estimating, this research also proposed the method for constructing quantitative forecasting model using qualitative data. Understanding the different characteristics of each construction R&D sub-business can support R&D program managers to demonstrate their feasibility of capital investment.

• Proceedings of the Korea Technology Innovation Society Conference
• /
• 2013.10a
• /
• pp.247-260
• /
• 2013

• International Area Studies Review
• /
• v.18 no.3
• /
• pp.175-201
• /
• 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 Korea Technology Innovation Society Conference
• /
• 2017.05a
• /
• pp.291-305
• /
• 2017

대전은 전국에서 R&D투자가 많은 지역으로 이는 출연연 및 출연연 출신 연구원의 기술창업의 증가로 나타나는 현상으로 볼 수 있다. R&D가 많이 투자됨에 따라 이에 따른 효율성에 대한 분석들이 많이 이루어지고 있으며, 주로 R&D 투자가 대한 지역내총생산, 기업의 생산성 등에 미치는 영향 즉 R&D투자의 효율성 분석을 많이 하고 있다. 본고에서는 지역 R&D투자가 기업의 생산성에 어느 정도 영향을 미치는 지를 분석하였다. 특히 지역특화(전략)산업 분야별로 분석하여 지역 R&D 투자의 효율적 배분을 위한 전략방안을 제시하고자 한다. 이러한 분석을 위해서 생산성에 대한 대리변수로 종업원 1인당 매출액 종업원 1인당 부가가치를 종속변수로 설정하였고, 독립변수로 연구개발비, 종업원 1인당 영업이익, 종업원 1인당 자본집약도 등의 변수를 다중회귀모형으로 실증분석 하였다. 분석결과 R&D투자가 매출액과 부가가치에 유의한 영향을 미치지만, 연구개발비가 매출액이나 부가가치 등 생산성 증가에 결정적인 요인으로 나타나지 않았다. 산업별 분석결과 정보통신, 바이오산업보다 부품소재 산업에서 결정계수가 높게 나왔다. 또한 조절회귀모형을 설정하여 조절효과를 분석한 결과 R&D투자는 매출액에 영향을 미치지만, 부가가치는 조절효과가 발생하지 않았다. 이는 지역 R&D투자의 효율적 배분 측면에서 투자의 활성화를 이루고 연구개발 투자가 실질적으로 기업의 생산성 증가에 기여할 수 있도록 견인해야 할 것이다.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
• /
• v.10 no.3
• /
• pp.75-83
• /
• 2015

This article investigates the impact of SMEs' R&D expenditure, government R&D funding, the number of funded by Government R&D programs on the employment growth rate. This study also explores whether government R&D funding and the number of funded by Government R&D programs have interaction effects between SMEs' R&D expenditures and the employment growth rate. The results show that SMEs' R&D expenditure and government R&D funding have a positive effect on the employment growth rate. The rest of variables have no significant direct effects on the employment growth rate. The government R&D funding has a interaction effect between SMEs' R&D expenditures and the employment growth rate. Especially, the firm group of high-level innovation capabilities has a positive effect on the employment growth rate. The results explain that the government R&D funding influences SMEs' employment positively and the impact of the government R&D funding on employment is more effective in the firm group of high-level innovation capabilities. Therefore, Government provides differentiation strategy of R&D funding by innovation capabilities of SMEs and can maximize the employment.

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

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
• /
• v.17 no.6
• /
• pp.39-50
• /
• 2022

Based on the signaling theory, this study examined whether startups are more likely to attract venture investment when receiving government R&D subsidies. First, we reviewed previous studies of the investment decision-making process of venture capitalists and understood the conditions that influence investment decisions. Based on previous studies on the signal effect of government subsidies, particularly government R&D grants, on inducing private fund investment, this study revealed a mechanism to induce venture investment by startups. In addition, in order to verify whether government R&D subsidies have the effect of inducing venture investment, an empirical analysis was conducted based on data from startups under seven years and certified as a venture companies in 2021. This paper used PSM(Propensity Score Matching) method and DID(Difference In Difference) analysis for an empirical study to analyze the average treatment effect on the treated group(beneficiary startups of government R&D grants). As a result of empirical analysis, companies that receive more government R&D subsidies after starting a business are more likely to attract venture investment. From two to three years after conducting the first government R&D project, startups that received government R&D grants attracted more venture investment than those that did not. The results of this paper demonstrate that government R&D projects can also affect the venture investment ecosystem, giving policy implications to government R&D projects targeting startups. It is also expected to suggest strategic implications to startups that need new funding.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2012.05a
• /
• pp.207-210
• /
• 2012

주요 선진국에서는 전통적 생산요소인 노동이나 자본에 비하여 기술 진보가 경제성장에 더 큰 기여를 하고 있다고 판단하고, 기술개발을 위한 R&D 투자를 적극적으로 추진하고 있다. 본 연구에서는 IT부문 R&D 투자액이 IT부문 수출 실적에 미치는 효과를 분석하는 한편, 회귀분석 결과를 활용하여 2020년 우리나라 정부가 목표로 하고 있는 수출 1조 달러 달성을 위하여 IT 부문에서 어느 정도의 R&D 투자가 이루어져야 하는 지를 분석한다.

• Journal of Technology Innovation
• /
• v.21 no.2
• /
• pp.137-167
• /
• 2013

This article estimates the scale of impact of expanding governmental fiscal expenditure for R&D investment on the private business enterprise's investment for R&D, and the relationship between business enterprise and university for expanding investment of R&D. According to my results, first, an expanding fiscal expenditure from government for R&D investment leads to increase R&D investment from business enterprise. However, an expanding expenditure from university rather leads to decrease R&D investment from business enterprise. Secondly, the crowding-out effect of expanding R&D investment from University on business enterprise's is very strong, and it is affected by structural changes such as the country's economic power, fiscal stance and cyclical volatility. Third, the more governmental expenditure on university expansive is, the stronger asymmetric relationship between business enterprise and university is, and investment sources of university from business enterprise is the main factor of this relationship. Finally, it is not easy to solve out this asymmetric relationship even through the governmental subsidy.