Prolific inventors—A bibliometric analysis

Patent information on 7392 inventors who received 9 or more U.S. Patents during 1975–84 was obtained. Analysis of the frequency distribution of patents per inventor reveals an approximately logarithmic decline from 9 to approximately 45 patents per inventor. The rate of decline decreases significantly for patent output above 45 patents per inventor. Patent citation analysis on 45 randomly selected inventors was performed. This sample included inventors who received from 9 to over 100 patents. The group received 1.79 citations per patent, 56.8% of the patents received at least 1 citation, and 2.7% of the patents received 10 or more citations. No statistically significant differences for these averages was found across the range of inventor patent output. No significant decline of patent quality with increased yearly patent output was observed.     

Multiple regression analysis of a patent’s citation frequency and quantitative characteristics: the case of Japanese patents

Although many studies have been conducted to clarify the factors that affect the citation frequency of “academic papers,” there are few studies where the citation frequency of “patents” has been predicted on the basis of statistical analysis, such as regression analysis. Assuming that a patent based on a variety of technological bases tends to be an important patent that is cited more often, this study examines the influence of the number of cited patents’ classifications and compares it with other factors, such as the numbers of inventors, classifications, pages, and claims. Multiple linear, logistic, and zero-inflated negative binomial regression analyses using these factors are performed. Significant positive correlations between the number of classifications of cited patents and the citation frequency are observed for all the models. Moreover, the multiple regression analyses demonstrate that the number of classifications of cited patents contributes more to the regression than do other factors. This implies that, if confounding between factors is taken into account, it is the diversity of classifications assigned to backward citations that more largely influences the number of forward citations.     

Measuring science-technology interaction in the knowledge-driven economy: The case of a small economy

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.     

Visualizing patent statistics by means of social network analysis tools

The present paper reviews the literature on social network analysis with applications to bibliometric data, and in particular, patent information. Several approaches of network analysis are conducted in the field of optoelectronics to exemplify the power of network analysis tools. Cooperation networks between inventors and applicants are illustrated, emphasizing bibliometric measures such as activity, citation frequency, etc. as well as network theoretical measures, e.g. centrality or betweenness. In this context it is found that inventors who serve as interfaces or links between different inventor groups apply for technologically broader patents, hence, benefiting from their access to different knowledge through their position. Furthermore, citation networks of patent documents as well as patent applicants were drawn. Here, patent thickets could be identified. The position of applicants within citation networks seems to be useful in explaining behaviour of the applicants in the marketplace, such as cooperation or patent infringement trials.     

Significant difference of dependence upon scientific knowledge among different technologies

Summary The authors have constructed an original database of the full text of the Japanese Patent Gazette published since 1994. The database includes not only the front page but also the body text of more than 880,000 granted Japanese patents. By reading the full texts of all 1,500 patent samples, we found that some inventors cite many academic papers in addition to earlier patents in the body texts of their Japanese patents. Using manually extracted academic paper citations and patent citations as “right” answers, we fine-tuned a search algorithm that automatically retrieves cited scientific papers and patents from the entire texts of all the Japanese patents in the database. An academic paper citation in a patent text indicates that the inventor used scientific knowledge in the cited paper when he/she invented the idea codified in the citing patent. The degree of science linkage, as measured by the number of research papers cited in patent documents, is particularly strong in biotechnology. Among other types of technology, those related to photographic-sensitized material, cryptography, optical computing, and speech recognition also show strong science linkage. This suggests that the degree of dependence on scientific knowledge differs from technology to technology and therefore, different ways of university-industry collaboration are necessary for different technology fields.     

Citation rates to technologically important patents

The purpose of this study was to determine whether the average number of citations received by issued U.S. patents from subsequently issued U.S. patents is higher for patents associated with important technological advances than for a group of randomly selected patents. Analysis of examiners' citations to 100 selected patents showed that these selected patents, which underlay technically important products, were more than twice as frequently cited (significance level of 0.0001) as a randomly selected set of 102 control patents. This finding provides strong evidence for the hypothesis that patent citation data can be used in technological indicators development, and in technological policy analysis, since it implies that the location and analysis of groups of highly cited patents can provide a valid indicator of patent areas of technical importance.     

Knowledge-transfer analysis based on co-citation clustering

Based on co-citation cluster analysis, we propose a knowledge-transfer analysis model for any technology field. In this model, patent data with backward citations to non-patent literature and forward citations by later patents would be analyzed. Co-citation clustering of the cited articles defines scientific knowledge sources, while that of the patents themselves defines technology fronts. According to the citation between the article and patent clusters, the landscape of knowledge-transfer including route and strength between scientific knowledge sources and technology fronts can be mapped out. The model has been applied to the field of transgenic rice. As a result of the analysis, ten scientific knowledge sources and eight technology fronts have emerged, and reasonable links between them have been established, which clearly show how knowledge has been transferred in this field.     

The beauty of brimstone butterfly: novelty of patents identified by near environment analysis based on text mining

The novelty of a patent may be seen as those patterns that distinguishes it from other patents and scientific literature. Its understanding may serve for many purposes, both in scientometric research and in the management of technological information. While many methods exist that deal with a patent’s meta-information like citation networks or co-classification analysis, the analysis of novelty in the full text of a patent is still at the beginning of research and in practice a time-consuming manual task. The question we pose is whether computer-based text mining methods are able to identify those elements of such a patent that make it novel from a technological and application/market perspective. For this purpose we introduce and operationalize the concept of near environment analysis and use a three-step text mining approach on one of the patents nominated as finalist in the 2012 European Inventor Award contest. We demonstrate that such an approach is able to single out, content-wise in a near environment, the novelty of the patent. The method can be used also for other patents and—with adaption of the near environment analysis—for scientific literature.     

What makes the first forward citation of a patent occur earlier?

Identifying the economic value of a patent is crucial to technology management. It also facilitates the commercialization and transactions of patents. As a proxy of patent value, forward citation counting is widely used, but it takes a long time for a patent to be sufficiently cited. In this context, we suggest the first citation lag, namely the time taken until the first citation, as a proxy of patent value, as it is positively correlated with the patent value and considers the fact that important patents with a high economic value tend to receive many citations in a short space of time. We explore the influential patent attributes related to the first citation lag to build a model to predict the patent value. By using the Cox proportional hazard model on green inventory patent data, we find that patents with a shorter technology cycle time and a larger number of IPC four-digit classes, claims, patent family, and backward citations are associated with the shorter first citation lag, while a patent’s science linkage has an inverse U-shaped relationship with the first citation lag. Further, patents having an unconventional technological core have a longer first citation lag and among patents having an unconventional technological core, the presence of a novel element makes the first citation earlier. Our study is expected to help patent evaluation in the early stage of technology transfer.     

The prevalence of weak patents in the United States: A new method to identify weak patents and the implications for patent policy

The presence of patents with dubious validity (i.e., weak patents) has been one of the prominent patent policy issues with undesirable consequences in innovation. The present study empirically examines the prevalence of weak patents in the United States and whether or not the current patent system is capable of correcting weak patent issues. To this end, we propose a new method to identify weak patents by using patent citation information in conjunction with the textual similarity between citing and cited patents. Our method, along with a series of internal validation measures, shows that 13% of U.S. patents filed from 2001 to 2010 are weak patents. By applying this new method, we find that patent owners build a patent portfolio around a weak patent by developing subsequent inventions more than they do for a non-weak patent. Our further analysis finds that a weak patent is more or equally likely to be retained by the patent owner than a non-weak patent. Our findings suggest that patent owners have an incentive to invest in maintaining and appropriating weak patents, and thus, the current patent system is incapable of self-correcting weak patent issues.     

Innovation Subsidies: Does the Funding Source Matter for Innovation Intensity and Performance? Empirical Evidence from Germany

In this paper we analyze the effect of European and national funding on innovation input and output at the firm level. In terms of innovation input, we do not find evidence that one policy crowds out the effect of the other. Instead, the policies are complements. In terms of output, we find that subsidy recipients are more active with respect to patenting. A citation analysis of patents reveals that the subsidy recipients file patents that are more valuable (in terms of forward citations) than those filed in the counterfactual situation of receiving no public support. These results suggest that public funding triggers socially beneficial research projects and that the co-existence of national and European policies does not lead to crowding-out effects when compared to a hypothetical world of a closed economy with no supplemental European policies.     

Can applied science be ‘good science’? Exploring the relationship between patent citations and citation impact in nanoscience

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.     

Inventor's Knowledge Set as the Antecedent of Patent Importance

This paper investigates the antecedents of patent importance by looking at the prior knowledge set of academic inventors. Using independent methodologies, we distinguish between the scientific knowledge set and the technical knowledge set, and separate these from other kinds of prior expertise. We find that the patents of the inventors who have a prior scholarly knowledge of the topic are on average more important (more cited after 6 years). Conversely, we find an inverted U-shape relationship between prior technical relatedness and patent importance. These results are potentially useful to support the work of practitioners such as university technology managers, which often face difficulties in identifying the importance and perspective value of the disclosed inventions, amid high market and legal uncertainty and budget shortages.     

Assessing the foreign control of production of technology: The case of a small open economy

Summary International R&D activities have grown significantly over the last two decades. Both the number of actors involved, as well as the importance of the technological activity carried out abroad, has considerably increased. We aim to quantify the international generation of knowledge for the case of Belgium, using indicators based on EPO and USPTO patent data (1978-2001). We distinguish among Belgian applicants, affiliates of foreign firms located in Belgium as well as Belgian based firms with affiliates abroad. This approach allows to improve existing indicators of internationalisation of technology based on patent data. The results are consistent with what can be expected for a small open economy as Belgium. A large part of patents with Belgian inventors are assigned to Belgian affiliates of foreign firms. Hence our more complete indicator of foreign ownership gives a substantially higher foreign control of Belgian inventors. Relatively more knowledge generated by Belgian inventors flows out of the country towards foreign owners of technology, than that knowledge generated abroad is owned by Belgian patent applicants. But the share of foreign inventors to Belgian assigned patents is considerably increasing over time, especially in the subcategory of Belgian firms with foreign affiliates.     

Small Worlds in Networks of Inventors and the Role of Academics: An Analysis of France

Using data on patent applications at the European Patent Office, we examine the structural properties of networks of inventors in France in different technologies. We find that the higher the presence of inventors from universities and public research organizations (PROs), the more likely the networks are to exhibit small world properties. University and PRO inventors contribute to reduce average path length insofar they are more mobile (across applicants) than other inventors, thus linking up otherwise disconnected cliques. We achieve these results by implementing an original methodology for detecting small world properties in one-mode projections of two-mode graphs.     

Examining the small world phenomenon in the patent citation network: a case study of the radio frequency identification (RFID) network

Despite strategic research has been done in recent years to study how network topology shapes the evolution of competition in various industries, previous researches do not investigate the importance of high betweenness point on the connectivity of patent citation networks. The goal of this report is to examine and characterize the small world phenomenon in the patent citations network by analyzing the data of RFID patents. The results suggest that the patent citation network can indeed be characterized as “small world”. Additionally, the patent citation network resembles the power-law connectivity distribution and exhibits preferential connectivity behavior. In other words, a few key patents have a great many more connections than the majority of patents with few connections. Furthermore, the patents of high betweenness centrality were identified. It is found that 81% of the patent citation activities have relations with the patents of high betweenness centrality. The result of this analysis will provide a specific way for managers to identify key patents, to map their own patent deployment and to derive insight into the best ways to navigate within such networks.     

Discovery of factors influencing patent value based on machine learning in patents in the field of nanotechnology

Patents represent the technological or inventive activity and output across different fields, regions, and time. The analysis of information from patents could be used to help focus efforts in research and the economy; however, the roles of the factors that can be extracted from patent records are still not entirely understood. To better understand the impact of these factors on patent value, machine learning techniques such as feature selection and classification are used to analyze patents in a sample industry, nanotechnology. Each nanotechnology patent was represented by a comprehensive set of numerical features that describe inventors, assignees, patent classification, and outgoing references. After careful design that included selection of the most relevant features, selection and optimization of the accuracy of classification models that aimed at finding most valuable (top-performing) patents, we used the generated models to analyze which factors allow to differentiate between the top-performing and the remaining nanotechnology patents. A few interesting findings surface as important such as the past performance of inventors and assignees, and the count of referenced patents.     

Analysis of the relationship between citation frequency of patents and diversity of their backward citations for Japanese patents

Conventional patent citation analyses have focused mainly on the presence of citation relationships, the number of patents cited by the subject patent, and the number of times the subject patent is cited by others (i.e., the numbers of backward and forward citations of the subject patent). However, most of them have not focused on patent classifications. Assuming that a patent based on a variety of technological bases tends to be an important patent that is cited more often, this study examines and clarifies the relationship between the diversity of classifications assigned to backward citations and the number of forward citations for Japanese patents. The results show notable differences in the number of classifications assigned to backward citations between the often cited and less frequently cited groups. It is considered that the diversity of backward citations can be utilized in the evaluation criteria for grouping that roughly identifies the often cited patents or eliminates a large part of less frequently cited patents.