• Journal of Korea Technology Innovation Society
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• v.17 no.3
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• pp.449-466
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• 2014

There have been various researches on the relationship between a company's R&D investment and the outcome from innovation. However, these studies failed to effectively analyze the decision-making process followed by companies in relation to knowledge production. Especially, in analyzing the patent of companies, the Poisson model has been commonly used, but its limitations have been pointed out. In recent years, many studies have adopted negative binomial models, but they still pose limitations in analyzing the selection process. This paper proposed a hurdle negative binomial model to effectively reflect the company's decision embedded within patent information and conduct an empirical analysis on a survey of businesses' activities. In particular, the study analyzed the selection process of companies in determining the number of patents. As a result of estimation, the presence of over-dispersion was identified. In addition, the Wald-test confirmed that setting up of hurdles was valid, and there was a difference between the results of hurdle models and those of general negative binomial settings.

• Journal of Industrial Convergence
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• v.22 no.8
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• pp.1-17
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• 2024

Recently, interest in edutech has been focused on its fusion with AI technology, and the market in this field is expanding. This study aims to analyze the technological competitiveness and key technological areas of major countries in the AI-edutech field. Additionally, considering that AI-edutech is a convergence of AI technology and edutech, the study seeks to examine the path dependence of AI-edutech in each country to determine whether they are based on existing AI technologies or edutech. To this end, AI-edutech patents were collected and competitiveness was analyzed using patent activity, patent impact, and market acquisition indicators. Path dependence for each country was analyzed using the hurdle negative binomial regression model. The analysis results indicate that the major countries in the AI-edutech field are China, South Korea, the United States, India, and Japan. In terms of patent activity, China had the highest level, followed by South Korea. In terms of patent impact and market securing power, the United States was high in both aspects, Japan had high market securing power, and South Korea had high patent influence. The results of the hurdle negative binomial analysis presented unique findings. The logit part results indicated that the possession of existing AI and edutech did not positively affect the emergence of current AI-edutech, but the count part results showed a positive influence. This suggests that, overall, it is difficult to assert that current AI-edutechs are based on past AI and edutechs. However, once some AI-edutechs based on existing AI and edutechs emerge, they are influenced by the existing technologies. These findings provide implications for future research and technological strategies in this field.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.9
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• pp.427-434
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• 2018

As noted by Pavitt (1984) and Malerbar (2002), previous studies have focused on identifying differences in industry characteristics between the machinery industry and other manufacturing industries. This study considered quantitative and qualitative aspects of performance of product innovation in analyzing what factors determine those outcomes. In particular, this study examined stepwise selection processes embedded in innovation activities by applying a hurdle negative binomial model as well as the Heckman two-step selection model. Results show that factors affecting performance improvement and patents differ, and the threshold effect and the intensity effect of innovation were also distinguished. These results imply that the R&D capability should be enhanced and external innovation is required to be effectively embodied in the organization. Furthermore, motivating employees plays a pivotal role in this technology and skill-intensive sector.