• Journal of Korean Society for Quality Management
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• v.40 no.4
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• pp.631-640
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• 2012

Purpose: This empirical study is focused on the relationship between innovation capability (R&D and Human Resource innovation) and performance in knowledge-based service firms. Methods: We build research model to test how each of innovation capability on technology and human resource is influenced on their financial and non-financial performance in the knowledge-based service industries. Based on the previous research, we hypothesized the factors are regarded innovation capabilities of the firms as the scale of R&D and human resources. Because this study is especially targeted to the performance of knowledge-based service firms. With the survey on 424 main knowledge-based service firms, the multi-regression analysis was performed. Results: The result showed that the scale of R&D and human resources capabilities are main factors for knowledge-based service firms' performance, which reflects the current industrial structure. Conclusion: This study empirically demonstrated that human resources are most important to the growth of knowledge-based service firms.

• Journal of Technology Innovation
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• v.15 no.2
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• pp.1-24
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• 2007

In this study, we estimated a CES production function for the Korean economy. We have found in the empirical results that the elasticity of the factor substitution is less than one and that the Korean economy exhibits labor-saving technological progress. In addition, we obtained the regression coefficient of R&D investment on technological change, i.e., the elasticity of R&D investment with respect to the technological change was 0.26% point. It implies that if R&D stock increases by 1%, labor efficiency increases 0.26% point through technological progress which is Hicksian non-neutral. It confirms that innovation-based growth strategy by increasing R&D investment would be effective on the one hand. Some policy consideration on the other might be needed for an increase in employment which is offset by technological progress.

• International Area Studies Review
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• v.21 no.1
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• pp.201-219
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• 2017

This paper analyzes the economic effects of the S&T Innovation, R&D, human resources and investment on the economic growth using 18 countries. We have obtained the somewhat mixed results on the existence of unit root roots in variables. While most of Pedroni cointegration tests show that there are no panel cointegration among the variables, Kao cointegration test shows that there is the panel cointegration among the variables such as GDP, human capital, R&D investment and patent. Kao cointegration test result shows that human capital, R&D investment, patent economic growth seem to have the panel cointegration or the long-run relationship among them as a whole. The estimation results of individual OLS and panel estimation show that the human capital, R&D investment and technology innovation or patent had positively significant effects on economic growth or GDP.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.16 no.2
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• pp.95-108
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• 2021

Technology innovation activities are very important for companies to secure technological competitiveness and continue to grow. Korea operates a certification system at the national level to promote corporate innovation activities, and strives to enhance SMEs' global technological competitiveness. Among these, the representative system related to technological innovation is the New Excellent Technology (NET) certification. NET is certified through a strict three-stage screening process, and is operated for the purpose of commercialization of new technology, technology trading, and promotion of early market entry by companies. Acquiring NET certification means that the company has a certain level of technological competitiveness. Therefore, this study attempted to conduct an empirical analysis on which technology innovation activities of companies affect the success of R&D projects and improvement of management performance, centering on NET certification system. To verify this, technology strategy, technology planning, systematic R&D process, internal cooperation, and external cooperation activities were set as major variables. As a result of the empirical analysis, it was confirmed that all variables set in this study individually contributed to the success of the R&D project and improvement of management performance. However, when looking at a comprehensive level that considers all variables, it was analyzed that systematic R&D process management and cooperation activities with external organizations have a statistically significant effect on R&D project success, and technology strategy establishment and technology planning activities, which are the initial stages of R&D, have a statistically significant effect on management performance. This study was conducted on innovation-oriented SMEs that have established and operated corporate R&D centers and are actively conducting R&D activities, and multiple regression analysis was used as an analysis method.

• Journal of Korea Technology Innovation Society
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• v.13 no.1
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• pp.124-139
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• 2010

This study analyzes determinants of innovation in Korea manufacturing industries from 2005 to 2007. In order to do this, we use raw data from 'Korea Innovation Survey 2008: Manufacturing Sector' conducted by STEPI, and also collect financial statement data from Korea Investors Service. As an analytical method for the empirical test, we utilize Probit model. Empirical results show that firm size and market concentration have positive relationship with firm's innovation activities. These support the ‘Schumpeterian hypothesis’. This would be the most distinguished feature of this study compared to previous literatures.Our study also shows that R&D personnel ratio, R&D intensity, and advertising intensity have positive effects on firms' innovation. Thus, we can say that R&D activities and consumer orientation are the main determinants of innovation. However, profit ratio and growth rate do not have any statistically significant effect on firms' innovation.

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

• Journal of Information Technology and Architecture
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• v.10 no.1
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• pp.47-62
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• 2013

In this paper, we analyze the comparative advantage of industry innovation (R & D) activities. The method is that companies are classified suppliers dominated- industry, productionintensive industries and science-based industries, and data of Statistical analysis were collected HCCP (KRIVET). The result is that Tipping phenomena of science-based is apparent and suppliers dominated- industry is the lack of comparative advantage. The implications are as follows. suppliers dominated- industries that specialize in R & D capabilities, support R & D capability is required. Second, the policy in terms of support for R & BD (linking technology commercialization support innovation) should be strengthened. Third, SMEs in the leveling down of industry R & D capabilities should be supplemented.

• Management & Information Systems Review
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• v.33 no.2
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• pp.171-188
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• 2014

Previous researches on technological innovation of SMEs have several limitations such as lack of study for industrial cluster system and entrepreneurship in SMEs, and ignoring role of RandD capability. So, this study suggested empirically a new model to SMEs. Major results are as follows. Firstly, system of industry and production had a significant and positive effect on entrepreneurship. Secondly, entrepreneurship had a significant and positive effect on technological innovation. Thirdly, system of science and technology had positive and significant effects on RandD capability and technological innovation. Fourthly, RandD capability had a positive and significant effect on technological innovation. Fifthly, business support system was not significantly related to entrepreneurship, RandD capability and technological innovation. Research results revealed that industrial cluster system(system of industry and production, system of science and technology), entrepreneurship and RandD capability were important for improvement of technological innovation performance in SMEs.

• Asian Journal of Innovation and Policy
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• v.6 no.1
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• pp.45-57
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• 2017

This study aims to analyze the factors that could influence business decisions of in the commercialization of R&D when technology is transferred from government research institutes (GRIs) to small and medium-sized enterprises (SMEs). We examine 353 such cases of technology transfer. The dependent variable is whether the licensee had the intention of following up with R&D after the technology has been transferred. The independent variables, classified into ex-ante factors and ex-post factors, consist of the involvement of SMEs into GRI R&D, technology readiness level, relatedness to existing technologies, and contribution to sales revenue and level-up of existing technologies. The results of the study show that the contribution to existing technologies has a positive impact on R&D commercialization. However, unlike our expectation, contribution to sales revenue, the involvement of SMEs into GRI R&D, technology readiness level, the relatedness to existing technologies of the technology transferred have no impact on follow-up R&D.

• Journal of Technology Innovation
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• v.11 no.2
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• pp.151-173
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• 2003

This paper analyses the efficiency and productivity of R&D system across time (1991${\sim}$2000) and 16 OECD countries using multi-output and multi-input non-parametric frontier methods such as DEA (data envelopement analysis) and Malmquist productivity indexes. Malmquist productivity indexes are decomposed into two components measures, namely technical change and efficiency change. To calculate R&D efficiency and productivity, we used R&D stock and the number or researchers as R&D input proxies and the number of adjusted SCI papers and U.S. patent applications as R&D output proxies. Empirical result shows that Switzerland, Canada, U.S., Australia's R&D efficiencies are the highest and Korea's R&D productivity growth is the highest in the sample for the period. Technical efficiency growth was a more important source of productivity growth than technological innovation.