• 시스템엔지니어링워크숍
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• s.6
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• pp.1-3
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• 2005

• Journal of the Korean Operations Research and Management Science Society
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• v.32 no.2
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• pp.163-175
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• 2007

[ $ulcorner$ ]Cost-Effectiveness Analysis$\lrcorner$ has been wifely used to evaluate economic efficiency of R&D projects, but most of cost-effectiveness evaluation systems have some problems such as systematic method for setting and evaluating cost factors, estimation of single effect on each R&D project, and estimation of cross effects among R&D projects. To solve these problems, we have designed a new evaluation indicator called a $ulcorner$Cost-Cross Effect Integration Indicator$lrcorner$ including cross effects developed in this research. The major research findings are summarized as follows : (1) $ulcorner$Coist Estimation Model$lrcorner$, which estimates the cost factors divided into two classes of assembly product and system product and then integrates the total cost values, has been designed. (2) A new method for estimating parameters of cross effects among R&D projects has been developed. (3) $ulcorner$Cross Effects Estimation Model$lrcorner$ to estimate multi-effects and cross effects by completion time among several projects has been designed. (4) $ulcorner$Integration Estimation Indicator$lrcorner$ for setting priority on a project group has been extracted by combination of total cost value and total effect value.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.33 no.3
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• pp.55-62
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• 2010

Currently, cost estimation is very important to the government acquisition programs to support decisions about funding and to evaluate resource requirement as key decision points. Parametric cost estimating models have been used extensively to obtain appropriate cost estimates in early acquisition phase. However, they have many restrictions to ensure the cost estimating result in Korean defense environment because they are developed in the U.S.A. environment. In order to obtain a good R&D cost estimate, developing our own CERs (Cost Estimation Relationships) using historical R&D data is essential. Nevertheless, there has been little research to develop our own CERs. In this research, we established a CER development process and found some cost drivers in the historical movement weapon system R&D data. The R&D CER is developed using the PCR(Principle Component Regression) method to remove multicollinearity among data and to overcome the restriction of the insufficient number of sample. At least, this research is meaningful as a first attempt in terms of defining the CER development process and obtaining our own R&D CER based on the historical data in Korean weapon system R&D environment.

• Economic and Environmental Geology
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• v.42 no.2
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• pp.133-141
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• 2009

For economic impact analysis on a R&D project of high-yield groundwater development in Jeju conducted by KIGAM from 2004 to 2007, benefit/cost ratio(BCR), net present value(NPV), and internal rate of return(IRR) were calculated by contingent valuation method(CVM), production function analysis, domestic water market analysis and technology factor analysis. Measurable direct impact parameters among the major outputs of this R&D project consisted the estimation 4 high-yield and high mineral groundwater reserve in Jeju. Annual use of the reserve by piped water and bottled water was estimated as 12.23 million ton and its monetary value was calculated as 293.4 million dollar in 2006 year value applied of 5.5% discount rate. Economic impact of this R&D project in NPV of year 2006, with applying a discount rate of 5.5%, was identified and estimated as 13.66 million dollar in NPV, 4.05 points in BCR, and 22.74% in IRR, respectively. Additional early launch benefit was 5.58 million dollar. Even increased of the 1% discount rate, NPV of this R&D project was also positive as 12.18 million dollar and BCR was 3.71.

• Journal of Convergence for Information Technology
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• v.8 no.4
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• pp.213-217
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• 2018

The relationship between R&D investment and subsequent change has been mostly confirmed under additional influencing factors, with the form of innovation investments. The research assumes that a firm adjusts its R&D spending in accordance to performance feedback. It is argued that an increased fluctuation of a firm's R&D expense is related to a reduced performance. This hypothesis is tested on SME in World class 300 Projet by SMBA. Using panel data models, instability measured by SD is related to performance levels measured by ROA, ROE & PM. Results support the proposed relationship between R&D expense instability and the subsequent performance. Although a causal link cannot be clearly established, the results indicate that firms with a lower performance have higher R&D investment fluctuations, possibly being more responsive to performance feedback.

• Proceedings of the KAIS Fall Conference
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• 2010.11b
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• pp.870-873
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• 2010

본 연구는 국내 Born Global Firm의 기술요인들이 해외신규시장 진입시기에 미치는 영향에 관한 연구모형을 제시하고, 국내 Born Global Firm을 대상으로 이에 대한 인과관계를 실증 분석하였다. 기존의 해외시장 진입시기에 관한 선행연구를 토대로 기술경쟁력, R&D 네트워크, R&D 정보력을 독립변수로 설정하고, 이러한 요인이 Born Global Firm의 해외신규시장 진입시기에 영향을 미칠 것이라는 가설을 설정하였다. 기존 선행연구를 통하여 기술경쟁력의 대용변수로 지적재산권, R&D 투자비용, R&D 전담기구 기능을, R&D 네트워크는 부서간 협력, 국내외 공동연구, R&D 정보력은 R&D 관련 정보 수집능력(경쟁업체 R&D 동향정보, 관련 주요연구자 정보 등), R&D 관련 정보 분석능력(기술이슈 및 트렌드 분석, 기술수준 분석 등), R&D 정보 활용능력(R&D 기획, 응용 분야 확장 등) 등을 사용하고 기업 내부요인과 수출관련에 대한 가설을 설정하였다. 특히, 해외시장 진입형태 중 FDI, 계약에 의한 해외시장진입 보다는 국내에서 가장 많은 해외진입 형태인 수출에 초점을 맞추었다. 연구결과는 다음과 같다. 국내 107개의 Born Global Firm을 대상으로 다중회귀분석 한 결과, Born Global Firm의 직접수출에 가장 큰 영향을 주는 요인으로는 지적재산권과, 부서간 협력, R&D 정보 활용능력 등으로 나타났다. 특히 기술이슈 및 트렌드 분석 정보력은 해외시장 진입시기를 앞당기는 것으로 나타났다.

• Management & Information Systems Review
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• v.28 no.4
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• pp.109-129
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• 2009

This study aims at investigating the effectiveness of SME's R&D system empirically. Specifically, this study analyze the relationships among R&D inputs(R&D investment, R&D human resource management), process(R&D planning, external network, internal cooperation), and output(technological innovation). A questionnaire was developed to measure the above variables. To test these relations, data were collected from the small and medium-sized IT firms located in Daegu-Kyungbuk region. The survey data of 154 firms were integrated as the empirical base for testing the relations. Most respondents were from the managers. Structural equation modeling analyses were used to examine the relations. Major results are as follows: Firstly, R&D HRM was positively and significantly influenced on the R&D planning. Secondly, R&D planning was positively and significantly affected on the external network, internal cooperation, and technological innovation. Thirdly, the both relations between R&D investment and R&D planning, and external network and technological innovation were not significant statistically. These results suggest the following implications. First, R&D human resource management is very important for IT SMEs. Secondly, internal cooperation mediates R&D inputs and technological innovation by approaching the other department's unique resources and by sharing the cost of new resource development. Several future researches need to overcome the limitations of this research. First, this study's sample was based on the small and medium-sized IT firms just located in Daegu-Kyungbuk region. This limitation may imply that empirical results can not represent overall small and medium-sized firm's situations. Therefore, future research needs to include different samples. Secondly, this study depends on the latitudinal study.

• Journal of Environmental Policy
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• v.14 no.4
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• pp.63-101
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• 2015

Banking and borrowing under the ETS may affect the low carbon technology investment level. If the indirect implementation measures are allowed, firms can gradually adjust their carbon reduction costs between implementation periods based on their carbon reduction costs and emission price forecasts. This implies that banking and borrowing may reduce or increase the level of low carbon technology R&D investment. In an oligopoly market, the effects of the measures are quite different from the ones in a perfectly competitive market. This is because the indirect implementation measures can shift market competition in Cournot competition model. The effects of banking and borrowing on the carbon reduction R&D investments depend on emission reduction costs, marginal production costs, discount rate, initial free allocation, and the cost reduction effects of R&D investment.

• Journal of Technology Innovation
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• v.17 no.1
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• pp.1-48
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• 2009

Recently we have found some symptoms that R&D fiscal incentives might not work well what it has intended through the analysis of current statistics of firm's R&D data. Firstly, we found that the growth rate of R&D investment in private sector during the recent decade has been slowdown. The average of growth rate (real value) of R&D investment is 7.1% from 1998 to 2005, while it was 13.9% from 1980 to 1997. Secondly, the relative share of R&D investment of SME has been decreased to 21%('05) from 29%('01), even though the tax credit for SME has been more beneficial than large size firm, Thirdly, The R&D expenditure of large size firms (besides 3 leading firms) has not been increased since late of 1990s. We need to find some evidence whether fiscal incentives are effective in increasing firm's R&D investment. To analyse econometric model we use firm level unbalanced panel data for 4 years (from 2002 to 2005) derived from MOST database compiled from the annual survey, "Report on the Survey of Research and Development in Science and Technology". Also we use fixed effect model (Hausman test results accept fixed effect model with 1% of significant level) and estimate the model for all firms, large firms and SME respectively. We have following results from the analysis of econometric model. For large firm: i ) R&D investment responds elastically (1.20) to sales volume. ii) government R&D subsidy induces R&D investment (0.03) not so effectively. iii) Tax price elasticity is almost unity (-0.99). iv) For large firm tax incentive is more effective than R&D subsidy For SME: i ) Sales volume increase R&D investment of SME (0.043) not so effectively. ii ) government R&D subsidy is crowding out R&D investment of SME not seriously (-0.0079) iii) Tax price elasticity is very inelastic (-0.054) To compare with other studies, Koga(2003) has a similar result of tax price elasticity for Japanese firm (-1.0036), Hall((l992) has a unit tax price elasticity, Bloom et al. (2002) has $-0.354{\sim}-0.124$ in the short run. From the results of our analysis we recommend that government R&D subsidy has to focus on such an areas like basic research and public sector (defense, energy, health etc.) not overlapped private R&D sector. For SME government has to focus on establishing R&D infrastructure. To promote tax incentive policy, we need to strengthen the tax incentive scheme for large size firm's R&D investment. We recommend tax credit for large size film be extended to total volume of R&D investment.

• Journal of Technology Innovation
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• v.20 no.1
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• pp.45-73
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• 2012

In this paper, we analyse empirically the effects of financial characteristics on the relationship between R&D investment and market value of firms listed on Korea Exchange. The main results of this study can be summarized as follows. Firm size increase the market valuation of R&D investment because it provides economies of scale, easier access to capital market, and R&D cost spreading. Market share also positively effects the relationship between R&D investment and firm value. Alternatively, free cash flow has a negative effect on the relationship between R&D investment and firm value because firms with high free cash flow could be tempted to use the free cash flow to undertake negative NPV projects. The dependence on external finance is a handicap negatively assessed by the market when firms undertake R&D projects due to the higher information asymmetry associated with this kind of project. Labor intensity has a negative effect on the relationship between R&D investment and firm value because the abnormal profits arising from R&D investment are diluted among employees. Capital intensity also has a negative effect on the relationship between R&D investment and firm value due to the greater financial constraints faced by capital intensive firms. In conclusion, several financial characteristics(firm size and market share) positively effect the relationship between R&D investment and firm value, while others(free cash flow, dependence on external finance, labor intensity, and capital intensity) exert a negative effect. Therefore, we conclude that the effectiveness of R&D investment depends on these financial characteristics.