Search Results
) Issue Year, (4) No. of Assignee, (5) No. of Assignee Country, (6) No. of Inventor, (7) No. of Inventor Country, (8) No. of Patent Reference, (9) No. of Patent Citation Received, (10) No. of IPC, (11) No. of UPC, (12) No. of Claim, (13) No. of Non
Summary
This paper addresses the issue of how science-technology interaction can be measured in the knowledge-driven economy. More specifically, it compares the patent citation indicator to another patent-based measure using data on a small European economy. Patent citation patterns will be compared to researcher patents. Comparing the two indicators suggests different patterns of science-technology linkage. An analysis of revealed technology contributions of academic inventors and a survey-based analysis of technological collaboration and knowledge transfer point to a possible explanation. Furthermore the research presents evidence that suggests technology sectors are related to different modes of collaboration in inventive processes amongst academics.
Abstract
In this study, the author tried to demonstrate the linkage between science research and technology development through non-patent citation analysis to reveal that the important knowledge resources from science research had significant impact on technology development. Genetic engineering technology was the field examined in this study. From the references listed in the patents, it was observed that the technology development in genetic engineering was influenced heavily by the research done by public sector. Over 90% of the citations were non-patent literatures, and the majority of non-patent citations were journal articles. Citing preferences, such as country preference and institute preference were observed from the data included in this study.
Abstract
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.
Abstract
The emergence of patent citations as a tool for patent estimation has been subjected to equally vocal champions and critics. In additional to patent citation, this article aims to contribute other factors, including court decisions, claim language, extension cases, patent family and portfolio, which should be deliberated during patent evaluation. It introduces the subject-matter by discussing the specialties and peculiarities of these proposed factors. Furthermore, comparisons between the patent citations and these factors are presented by illustrating several well-known patents. The results of the comparisons reveal that an adverse conclusion might be drawn if a patent is estimated only based on citations. The conclusion supports Meyer’s study that “the general nature of a common framework for both scientific and patent citations would severely limit its usefulness.” Therefore, those factors discussed in the article would be a great asset in patent evaluation. However, it only illustrates their impact on patent estimation using a couple well-known patents. Future research would be needed to investigate these factors in a more detailed manner.
Abstract
Nanotechnology is an emerging field of science with the potential to generate new and enhance existing products and transform the production process. US patent data is used to track the emergence of nanotechnologies since 1978. The nanotechnologies that have undergone the most development are identified using patent citation data and co-citation patterns of patents are examined to define clusters of related nanotechnologies. The potential for economic impact of the emerging nanotechnologies is assessed using a generality index.
Abstract
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.
Abstract
The gender gap in science and technology has received considerable attention by both researchers and policy makers. In an effort to better understand the quantity, quality, and underlying characteristics of female research efforts, I integrate three existing databases to uncover how female patenting activities differ from men’s in the US biotechnology industry. Data on how much science the patents build upon, the author institutions of that science, and who funded the papers in which the science appears are all examined. In addition, using the NBER Patent Citation Data Files, I propose a possible gender-based life cycle model for patenting activity. The policy implications of my findings are also discussed.
Summary
This paper suggests an international benchmarking method of disembodied knowledge flow structure. Using patent citation as a proxy measure of disembodied knowledge flow, national knowledge network is developed. Structural equivalence measure is applied to comparing the knowledge network of Korea and Taiwan with that of USA. Static and dynamic comparison make it possible to benchmark disembodied knowledge flow structure efficiently and identify convergent and divergent industries between developing countries and USA. It is also a meso-study that could be conducive to building a comprehensive analytical framework of national innovation system.
Abstract
By tracing the flows of patent citation to prior patents and scientific journal articles, we investigate the sources of knowledge for innovation output in Singapore, a small, highly open economy that has traditionally been significantly dependent on foreign multinational corporations (MNCs). We found that the local production of new knowledge by indigenous Singaporean firms depends disproportionately on technological knowledge produced by MNCs with operational presence in Singapore and scientific knowledge generated by foreign universities. Locally produced new knowledge by indigenous firms and local universities/ public research institutes constitutes an as yet insignificant, albeit growing, source for innovation in Singapore.
