• Journal of Information Technology Applications and Management
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• v.21 no.4_spc
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• pp.331-344
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• 2014

This study attempts to explore the difference of innovation sources between high-tech industry and mid-tech industry through patent analysis. After extracting 119 corporates, commonly surveyed in 2007 HCCP(Human Capital Corporate Panel) and 2005~2006 Korea Innovation Survey, their patents applied for the Korean Intellectual Property Office in 2007~2012 are analysed mainly through negative binomial regression model. Analytical results shows that external information source could be opposite effects to technological innovation depending on technological level and industrial characteristics. The current results are still bounded in the statistical significance, mainly due to the limited observations and information.

• Asian Journal of Innovation and Policy
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• v.1 no.1
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• pp.50-70
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• 2012

This paper analyzes the factors that determine technology innovation in Korean manufacturing firms, focusing on the role of intra-firm knowledge diffusion and market strategy in patent production. For empirical analysis, zero-inflated negative binomial (ZINB) regression is applied to the 2009 Human Capital Corporate Panel data. The empirical findings confirm the critical role of intra-firm knowledge-sharing processes in technology innovation; firms with a market-leading strategy oriented to new product development also tend to be prolific in patent production.

• Journal of Technology Innovation
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• v.26 no.4
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• pp.29-56
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• 2018

The purpose of this research is to examine whether investment portfolio composition affects the technological performance of corporate venture capital (CVC). The stages of investment are categorized from "start-up/seed", "early", and "expansion", to "later" stage. We posit and test that the investment stage composition in a portfolio is highly correlated with the growth potential and downside risk of the portfolio, which in turn influences an investor's innovation performance. To test this hypothesis, we used negative binomial panel regression with 21 years of deal data from 70 cases of CVC. The results show that there is an inverted U shaped relationship between investment portfolio composition and technological performance. This means that the more seed or early stage investment within the investment portfolio, the higher the innovation performance; however, if the amount of seed or early stage investment is over a certain level, the performance decreases. Further, this study finds that the external partners of a venture negatively moderate the inverted U shaped relationship between portfolio composition and innovation performance. We believe that corporate planners, venture capitalists, and policy makers will be helped by these results showing that companies can maximize their investment performance by considering the investment stage and progress of investments.

• Journal of Technology Innovation
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• v.25 no.3
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• pp.83-113
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• 2017

This paper constructs panel data of inventors listed on patents applied for the KIPO during 1991-2005 and analyzes the effects of network characteristics on inventor productivity. The findings are as follows: ⅰ) Strong ties within a network have positive effects on inventor productivity. ⅱ) An inventor with high centrality shows high producitivity. ⅲ) Technological diversity of a network enhances inventor productivity. ⅳ) An inventor belonging to a network of good quality shows higher productivity. ⅴ) Network size is positively related with inventor producitvity. ⅵ) A lone inventor shows the highest productivity among types of inventors, and a co-inventor with the experience of standalone invention is more productive compared to an inventor with only the experience of co-invention. ⅶ) The productivity effects of network variables differ across regions. ⅷ) Differences among regions do not decrease though geographical boundaries become less important.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.15 no.2
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• pp.19-32
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• 2020

The purpose of this study was to investigate the influence factors of the university level centering on the entrepreneurial performance of the university students and full-time faculties in the situation of increasing interest in entrepreneurial university. In order to achieve the purpose of the study, a panel data was established from 2015 to 2018 on the basis of the university notification data. The panel data included universities with data on the number of university students and full-time faculty founders for at least two years. Through this, four year data from 154 universities were used for analysis. As an analysis method, frequency analysis and descriptive statistics were conducted to understand the characteristics of the university. Since then, panel negative binomial regression analysis has been conducted in consideration of the longitudinal features and distribution of the data. Also, based on the Hausman test results, the results were interpreted based on random effect model. The results of this study are as follows. First, as a result of the analysis of the entrepreneurial performance and the change trend of the domestic university from 2015 to 2018, the entrepreneurial performance of the university has been steadily increasing in the last four years, and the increase in the number of university student entrepreneurs was relatively higher than the full-time faculties. Second, economic and educational approaches need to be combined to promote university students' start-ups. The university factors that promote the start-up of university students were found to be scholarships, start-up grants, startup lectures, and startup clubs. Third, the openness and regional characteristics of the univeristy can promote the establishment of university students. Fourth, the establishment of a research environment and support for start-ups for full-time faculty members can enhance their start-up performance. The university factors that promote the start-up of full-time faculty were research funds and staffes who support start-up. The conclusions drawn from these findings are as follows. First, overall efforts are needed to develop into an entrepreneurial university. Second, in order to change into an entrepreneurial university, direct support for entrepreneurship is needed. Third, as an entrepreneurial university, it is necessary to find a way to bridge the gap by university according to region and size. Fourth, it is necessary to reinforce the support for linking the research results of universities to start-ups. Fifth, it is necessary to improve the atmosphere for full-time faculty members to be entrepreneur.

• Journal of Technology Innovation
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• v.22 no.1
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• pp.149-175
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• 2014

This study analyzed the effect of corporate innovation strategies on patent production and ultimately on technological change and new product development of firms in South Korea. The intent was to derive efficient strategies for enhancing technological performance of the firms. For the empirical analysis, three sources of data were combined: four waves of the Human Capital Corporate Panel Survey (HCCP) data collected by the Korea Research Institute for Vocational Education and Training (KRIVET), corporate financial data obtained from the Korea Information Service (KIS), and corporate patent data provided by the Korean Intellectual Property Office (KIPO). The patent production function was estimated by zero-inflated negative binomial (ZINB) regression. The technological performance function was estimated by two-stage regression, taking into account the endogeneity of patent production. An ordered logit model was applied for the second stage regression. Empirical results confirmed the critical role of corporate innovation strategies in patent production and in facilitating technological change and new product development of the firms. In patent production, the firms' R&D investment and human resources were key determinants. Higher R&D intensity led to more patents, yet with decreasing marginal productivity. A larger stock of registered patents also led to a larger flow of new patent production. Firms were more prolific in patent production when they had high-quality personnel, intensely investing in human resource development, and adopting market-leading or fast-follower strategy as compared to stability strategy. In technological performance, the firms' human resources played a key role in accelerating technological change and new product development. R&D intensity expedited new product development of the firm. Firms adopting market-leading or fast-follower strategy were at an advantage than those with stability strategy in technological performance. Firms prolific in patent production were also advanced in terms of technological change and new product development. However, the nexus between patent production and technological performance measures was substantially reduced when controlling for the endogeneity of patent production. These results suggest that firms need to strengthen the linkage between patent production and technological performance, and take strategies that address each firm's capacities and needs.