• 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.

• Korean small business review
• /
• v.41 no.1
• /
• pp.75-96
• /
• 2019

This study used age, education, major, working period as CEO's characteristics and examine relationship between these characteristics and R&D Investment. Furthermore this study examined how CEO should react in terms of R&D investment, which is effected by CEO's characteristic in the market. The empirical results are following. (1) When CEO's age are young, they spend much money for R&D investment. And R&D investment which is determined by young CEO has a positive effect on relation of firm value. (2) A higher educational background has a positive effect on R&D investment and will create higher firm value. (3) When CEO's major is competitive in the same industry, it has a positive relationship with R&D investment and its firm value is bigger than though. (4) When CEO working period is long, they showed active to R&D investment. On the other hand, the firm value decreased. This study focused on analyzing the relationship between characteristics of CEO and R&D Investment, furthermore, how R&D investment which effected by CEO's characteristic is contributing in creating the firm value. This results indicate that CEO's characteristics reflect R&D investment and value of venture business. Therefore, CEO's characteristics should be considered financial information and firm value in the market.

• Journal of Technology Innovation
• /
• v.23 no.1
• /
• pp.61-86
• /
• 2015

This study provides an empirical analysis based on 2012 Korea Innovation Survey (STEPI) to investigate the relation between R&D cooperation and in-house R&D investment. The study further analyzes the effect of the R&D cooperation and in-house R&D investment on technical innovation. First, the relation between company's in-house R&D investment and R&D cooperations is estimated with the two equations using SUR models. Second, the effect of in-house R&D investment and R&D cooperation on the company's technical innovation is estimated using Probit model. This study differs from other existing R&D studies using Korean data in that empirical models are based on structural relationships among in-house R&D, R&D cooperation, and technical innovation. The results can be summarized as follows; the R&D cooperation expands the in-house R&D investment and the in-house R&D strengthen the R&D cooperation. Furthermore, In-house R&D investment increases the chances of success in innovation. As we obtain evidence of complementary relation between R&D cooperation and in-house R&D investment, it is necessary to develop environment conducive to this complementarity in order to have more efficient R&D system.

• 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.

• 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 Korea Technology Innovation Society Conference
• /
• 2017.11a
• /
• pp.159-169
• /
• 2017

정부는 R&D 재원의 전략적인 투자를 위해 199년에 국가과학기술위원회를 설치한 이후, R&D 예산 배분 조정을 지속적으로 추진하면서 개별 사업에 대한 예산조정 이전에 투자우선순위를 설정하였다. 그러나 그간의 투자우선순위 설정은 중장기 투자전략, 기본계획 등을 근거로 하기 때문에 중점적으로 투자해야 할 기술분야에 대해 정성적인 언급에만 머무를 수밖에 없고, 현재 연구트렌드를 반영하기 어려위 실제 R&D 예산 배분 시 구체적인 연계성이 부족한 실정이다. 이에 본 논문에서는 나노분야 R&D를 중심으로 키워드를 활용한 트렌드 분석을 통해 정부 R&D 예산 배분의 전략성을 제고할 수 있으며, 사업의 투자규모를 설정하는데 있어 투자우선순위와의 연관도를 높이는 방안을 제시하고자 한다.

• Proceedings of the Korea Technology Innovation Society Conference
• /
• 2017.11a
• /
• pp.189-200
• /
• 2017

본 연구는 국내 지역R&D투자와 지역경제지표 간의 관계를 파악하기 위한 것이다. 연구 방법은 패널VECM을 사용하여 1995~2014년 국내 17개 시 도별 정부 및 민간R&D투자, 고정자본과 고용, 지역내총생산의 상호 간 장 단기 인과관계를 도출하였다. 분석결과, 단기적으로 GRDP의 원인변수는 고정자본, 고용, 그리고 민간R&D투자로 나타났다. 고정자본의 원인변수는 고용, 민간R&D투자로 나타났으며, 고용의 원인변수로는 GRDP와 고정자본으로 나타났다. 장기적으로 고용, 고정자본, 정부R&D투자가 다른 변수들의 장기균형관계로부터 각각 인과관계를 갖는 것으로 나타났다. 이와 같은 결과를 바탕으로 목적과 대상 그리고 시간의 흐름에 따라 지역R&D투자의 직 간접적 효과를 함께 고려할 수 있는 추가적인 분석이 요구된다.

• Journal of Technology Innovation
• /
• v.3 no.1
• /
• pp.185-212
• /
• 1995

전통적인 산업조직이론에서 널리 사용되는 시장구조-행동-성과 분석 도구 (The SCP Paradigm)는 시장성과가 가격정책, 기술개발투자(R&D), 광고투자, 생산설비 변경 등 시장행동의 함수라는 암묵적 가정에 근거한다. 최근 시장행동 중에서 기업의 관심이 크게 높아진 R&D 및 광고투자가 시장성과에 미치는 영향이 크게 부각되었으며, 시장성과를 구성하는 주요요인으로 주목받고 있다. R&D 및 광고 투자의 성격과 행태, 그리고 시장성과에 미치는 영향이 상호 유사함에도 불구하고 두 가지 변수를 동시에 다룬 연구는 매우 드물다. 몇 안 되는 연구들도 기업의 행태를 실증적으로 설명하는데 치중함으로써 이론적 근거를 소홀히 하는 경향을 보이고 있다. 즉, 논리의 전개상 이론적인 근거를 바탕으로 수리모형이 먼저 제시된 후에야 이를 검증하는 방법으로 통계모형을 사용하는 것이 옳을 것이다. 이 논문은 기존의 SCP 분석방법을 사용하여 기업이 한정된 재원을 어떤 원칙아래 R&D 및 광고에 분산 투자하는 가를 설명하기 위해 수리모형을 설정한 후, 정태와 동학, 확실성과 불확실성, 단발성과 균등투자전략의 개념을 도입하여 다양한 분석을 시도하였다. 또 R&D 및 광고투자 함수를 이론적 근거에 의해 도입하되, 각 모형에 균형이 존재하는가를 검증하였다. 수리모형을 이용해 분석한 결과 (1) 기업의 투자는 R&D 및 광고투자간에 한계원리(Marginal Principle)가 지켜지도록 분배할 때에 효율적임이 판명되었고, (2) 동학모형이 정학모형을 포함하는 일반모형의 성격을 가지고 있었으며, (3) 투자는 확실성이 높을수록, 분산시킬수록 투자효과가 큰 것으로 나타났다. 한국을 대상으로 한 실증적 모형추정은 앞의 수리모형 및 그 결과에 근거를 두었으며, 한국기업에 적절한 R&D 및 광고투자함수를 추정한 뒤 이를 이용해 업종, 기업규모, 상품유형별로 적합한 모델(Fixed Effects Model)을 결정하고, 각각에 해당하는 통계모형을 구축하였다. 이 결과 (1) 업종 및 기업규모별로 그룹간에 유의한 특성이 발견되었으며, (2) R&D 및 광고투자는 기업의 시장성과를 설명하는 중요한 변수이나, (3) R&D 투자의 경우는 광고에 비해 불확실성이 존재하는 것으로 나타났고, (4) 수리모형에서 도출된 한계원리가 통계모형에서도 유효한 것으로 드러났다.

• 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 Energy Engineering
• /
• v.6 no.2
• /
• pp.145-151
• /
• 1997

The R&D investment of power industry has significant influences on the social welfare as well as national economy. It is necessary to analyze how efficient the R&D investment has been performed. The objective of this study is to verify the efficiency of the R&D investment in the domestic power industry. A formula was introduced to by calculate the appropriate amount of R&D investment of monopolistic industry under the regulations which are determined by the proportion of R&D elasticity and price elasticity. It has resulted that there would be no economy of scale as the sales of electricity increases at the same rate of the increasing cost. The R&D investment in the present electricity industry has been performed inefficiently by showing the negative impact on price-cost margin of the intensity of R&D investment, which is the extent of R&D investment to reinforce economy of scale.