Ke-Chiun Chang

The relationships between the patent performance and corporation performance

This study utilizes panel regression model to explore the relationships between corporate performance and the patent performance measured from patent H index, current impact index (CII), and essential patent index (EPI) in the pharmaceutical company. The results demonstrate that patent H index and EPI have positive influences upon corporate performance. Furthermore, this study developed a classification for the pharmaceutical companies to divide them into four types, and provided some suggestions to them.

Exploring the nonlinear effects of patent citations, patent share and relative patent position on market value in the US pharmaceutical industry

This study applied artificial neural networks to explore the influences of the quantitative and qualitative patent indicators upon corporate market value in the US pharmaceutical industry. The results showed that US pharmaceutical companies should not concentrate most of their R&D resources on one particular technological field, but create wider technological capabilities to avoid missing new technological opportunities and to decrease the risk of the lock-in effect. Moreover, in order to enhance their market values they should invest more resources in R&D activities to increase their advantage in their most important technological fields. In addition, this study found out that patent citations have an inverse U-shaped influence upon corporate market value and there exists an optimal value for patent citations. If patent citations are below the optimal value, they are positively associated with corporate market value. However, if patent citations are beyond the optimal value, they are negatively associated with corporate market value because of the significant spillover effect of R&D in the pharmaceutical industry.

Analyzing the nonlinear effects of firm size, profitability, and employee productivity on patent citations of the US pharmaceutical companies by using artificial neural network

This study utilized artificial neural network (ANN) to explore the nonlinear influences of firm size, profitability, and employee productivity upon patent citations of the US pharmaceutical companies. The results showed that firm size, profitability, and employee productivity of the US pharmaceutical companies had the nonlinearly and monotonically positive influences upon their patent citations. Therefore, if US pharmaceutical companies want to enhance their innovation performance, they should pay attention on their firm size, profitability, and employee productivity.

Using neural network to analyze the influence of the patent performance upon the market value of the US pharmaceutical companies

This study applies the artificial neural network technique to explore the influence of quantitative and qualitative patent indicators upon market value of the pharmaceutical companies in US. The results show that Herfindahl-Hirschman Index of patents influences negatively market value of the pharmaceutical companies in US, and their technological independence positively affects their market value. In addition, this study also finds out that patent citations of the American pharmaceutical companies have an inverse U-shaped effect upon their market value.

The nonlinear nature of the relationships between the patent traits and corporate performance

This study utilizes neural network to explore the nonlinear relationships between corporate performance and the patent traits measured from Herfindahl-Hirschman Index of patents (HHI of patents), patent citations, and relative patent position in the most important technological field (RPPMIT) in the US pharmaceutical industry. The results show that HHI of patents and RPPMIT have nonlinearly and monotonically positive influences upon corporate performance, while the influence of patent citations is nonlinearly U-shaped. Therefore, pharmaceutical companies should raise the degrees of the leading position in their most important technological fields and the centralization of their technological capabilities to enhance corporate performance.

Using the entropy-based patent measure to explore the influences of related and unrelated technological diversification upon technological competences and firm performance

This study applies the entropy-based patent measure to explore the influences of related technological diversification (RTD) and unrelated technological diversification (UTD) upon technological competences and firm performance. The results show that RTD has a monotonically positive effect on technological competences and UTD has an inverse U-shaped effect on technological competences. Besides, the results demonstrate that the extent of the positive influence of RTD upon technological competences is better than that of UTD upon technological competences. If American pharmaceutical companies would like to adopt technological diversification, this study suggests that they should undertake RTD, rather than UTD. In addition, this study finds out that technological competences mediate the relationship between firm performance and both of RTD and UTD. Although RTD and UTD cannot significantly influence firm performance directly, they can positively affect firm performance indirectly through technological competences.

Exploring the nonlinear effects of patent H index, patent citations, and essential technological strength on corporate performance by using artificial neural network

This study utilizes the artificial neural network to explore the nonlinear relationships between patent performance and the corporate performance of the pharmaceutical companies. Patent performance measured from patent H index, patent citations, and essential technological strength (ETS). The result shows that patent H index, patent citations, and ETS has the nonlinear effect on the corporate performance of the pharmaceutical companies.

Patent Deployment Strategies and Patent Value in LED Industry

This study applies two variables in the measurement of company patent deployment strategies: patent family depth and earn plan ratio. Patent family depth represents the degree to which certain fields and markets are valued by the patent owner. Earn plan ratio defined as the ratio of the number of patent forward citations to patent family size. Earn plan ratio indicates the degree to which a patent family could be cited by later innovators and competitors. This study applies a logistic regression model in the analysis LED industry data. The results demonstrate that patent value has a positive relationship with the patent family depth, and earn plan ratio.

Research Performance and University–Industry–Government Funding Sources in Taiwan’s Technological and Vocational Universities

Research funding in Taiwan’s technological and vocational universities is mainly sourced from those scientific and technological projects which were assigned by government, industries or other organizations. It plays an important role in influencing innovation activities, development of new knowledge, and advancement of new-generation technologies. As technology dynamics over time, technological and vocational universities have missions to associate with that. To achieve their missions, more funding supports from university/industry/government are demanded. By analyzing data for Taiwan technology and vocational universities, the object of this study is to investigate a series of indices such as number of patents, patent nationality, number of paper publications, category of paper publications, and their funding sources. We also examine whether and how the faculties’ age, education level, academic level, and research performance affect the three types of funding sources from governments, industries, and other organizations. The results have indicated that funding sources in Taiwan’s technological and vocational universities are closely referred to the number of patents and paper publications, suggesting that the faculties needs to justify their paper publication and patenting strategies accordingly. Moreover, faculties’ age, and academic level have played a positive influence on obtaining funding. Policymakers and universities could consider the general distribution and tendency of the three types of research funding investment and give proper incentives to guide their faculties’ research interests and achievements.

Threshold effects of the patent H-index in the relationship between patent citations and market value

This study employs a panel threshold regression model to test whether the patent h–index has a threshold effect on the relationship between patent citations and market value in the pharmaceutical industry. It aims to bridge the gap in extant research on this topic. This study demonstrates that the patent h–index has a triple threshold effect on the relationship between patent citations and market value. When the patent h–index is less than or equal to the lowest threshold, 4, there is a positive relationship between patent citations and market value. This study indicates that the first regime (where the patent h–index is less than or equal to 4) is optimal, because this is where the extent of the positive relationship between patent citations and market value is the greatest.