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Abstract  

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.

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Abstract  

There is a rich literature on how science and technology are related to each other. Patent citation analysis is amongst the most frequently used to tool to track the strengths of links. In this paper we explore the relationship between patent citations and citation impact in nanoscience. Our observations indicate that patent-cited papers perform better in terms of standard bibliometric indicators than comparable publications that are not linked to technology in this way. More specifically, we found that articles cited in patents are more likely to be cited also by other papers. The share of highly cited papers is the most striking result. Instead of the average of 4% of all papers, 13.8% of the papers cited once or twice in patents fall into this category and even 23.5% of the papers more frequently cited in patents receive citation rates far above the standard. Our analyses further demonstrate the presence and the relevance of bandwagon effects driving the development of science and technology.

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Scientometrics
Authors: Gamal Atallah and Gabriel Rodríguez

Patent citations are extensively used as a measure of patent quality. However, counting citations does not account for the fact that citations come from patents of different qualities, and that citations are of variable qualities. We develop a citation index which takes into account the cumulative quality of the citing patents. We apply this index to the 2,139,314 utility patents granted in the U.S. between 1975 and 1999. We study the properties of this index by year and by technological category, and analyse the links between patents.

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networks (Shin and Park 2007 ; Wartburg et al. 2005 ; Yoon and Park 2004 ). A patent citation network consists of groups of related patents in which the largest groups are defined by patent technology categories. The exchange of citations between these

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Abstract  

The emergence of pattent bibliometrics as a new branch of scientometrics necessitates a deeper understanding of the relationship between patents and papers. As this connection is established through the linkage between patents and research papers, one must have a clear idea of similarities and differences between patent and paper citations. This paper will investigate to what extent one can not only apply bibliometric methods to patents but also extend the existing interpretative framework for citations in research papers to the field of patent citations. After pointing out some parallels in the debates about the nature of citations in patents and scientific articles, the paper outlines those parts of bibliometric theory covering scientific citations that could be relevant to patent citations too. Then it highlights the specialties and peculiarities of patent citations. One major conclusion is that the general nature of a common framework for both scientific and patent citations would severely limit its usefulness, but research on academic citations might still be a great source of inspiration to the study of patent citations.

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Abstract  

Patent citation counts represent an aspect of patent quality and knowledge flow. Especially, citation data of US patents contain most valuable pieces of the information among other patents. This paper identifies the factors affecting patent citation counts using US patents belonging to Korea Institute of Science and Technology (KIST). For patent citation count model, zero-inflated models are announced to handle the excess zero data. For explanatory factors, research team characteristics, invention-specific characteristics, and geographical domain related characteristics are suggested. As results, the size of invention and the degree of dependence upon Japanese technological domain significantly affect patent citation counts of KIST.

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Abstract  

In this paper we carry out an empirical analysis to address some questions concerning the production and quality of technology in environmental sectors. The methodology involves patents as a measure of the generation of new knowledge, and patent citations as a proxy for the quality of a technological invention. The sample contains more than 12,000 environmental European patents from firms and government institutions from 1998 to 2004. From our econometric analysis, we found that environmental patents applied by individual inventors present on average less quality that those applied by institutional inventors. The size of family patent is relevant to explain forward patent citation. Furthermore, patents coming from abroad (out of Europe), in particular with US and Japan priority, are more cited on average than local patents (with European priority). Lastly, the specialization in environmental fields of a patent plays a negative role in determining the frequency of forward citation.

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Abstract  

This paper uses bibliographic coupling analysis to plot out a patent citation map. It explores the current research and development in the high-tech electronic companies in Taiwan, and the relationship between companies and industries. Fifty-eight high-tech electronic companies under this study, between 1998 and 2000, obtained 4162 patents from U.S., and cited 24,852 patents during these years. Through the data from bibliographic coupling analysis, the paper categorizes these companies into 6 major groups: semiconductor, peripheral, scanners, notebook / monitor, system, IC design / packaging. This research also uses multidimensional scaling to plot out a patent citation map, graphically displaying the association among the groups. The result shows a higher similarity among companies in semiconductor sector, whereas the distinction between industries grows more and more ambivalent, even overlapping in some cases.

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Abstract  

This paper investigates the impact of large multinational firms on the Dutch technology infrastructure. More specifically, it asks how the structure of the knowledge flows network matters for diffusion of technological knowledge in the Dutch economy. Patent citation analysis based on European Patent applications is used to quantify this network. The paper finds that there are large differences between firms in terms of the density of their 'ego-network', and the amount of knowledge spillovers to the Dutch economy that they generate.

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, technology diffusers. We find that activeness in learning has a significantly positive impact on the relative importance of e-paper display technology within the knowledge network. Firms engaging in intensive patent citation activities with the aim of

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