The citation impact of social sciences and humanities upon patentable technology

This paper examines the citation impact of papers published in scientific-scholarly journals upon patentable technology, as reflected in examiner- or inventor-given references in granted patents. It analyses data created by SCImago Research Group, linking PATSTAT’s scientific non-patent references (SNPRs) to source documents indexed in Scopus. The frequency of patent citations to journal papers is calculated per discipline, year, institutional sector, journal subject category, and for “top” journals. PATSTAT/Scopus-based statistics are compared to those derived from Web of Science/USPTO linkage. A detailed assessment is presented of the technological impact of research publications in social sciences and humanities (SSH). Several subject fields perform well in terms of the number of citations from patents, especially Library and Information Science, Language and Linguistics, Education, and Law, but many of the most cited journals find themselves in the interface between SSH and biomedical or natural sciences. Analyses of the titles of citing patents and cited papers are presented that shed light upon the cognitive content of patent citations. It is proposed to develop more advanced indicators of citation impact of papers upon patents, and ways to combine citation counts with citation content and context analysis.

     

The choice of examiner patent citations for refusals: evidence from the trilateral offices

Utilizing a novel methodology based on international family-to-family patent citation data, this paper directly compares X/Y patent citations (i.e., those cited as grounds for rejections, equivalent to “blocking patents” in the US) between major patent offices. Remarkable discrepancies between the offices were revealed, despite the common patentability criteria of novelty and inventive step to generate citations. This paper then introduces a simple cosine similarity measurement between a family of X/Y patent citations and all citations added globally to the same original application. How the discrepancies of X/Y patent citations at the European Patent Office (EPO) and the US Patent and Trademark Office (USPTO) relate to the characteristics of applications and longitudinal aspects of office actions were also examined. X/Y patent citations from both the EPO and USPTO commonly show that the range of patent application classes is positively correlated with divergent reasons for refusal, suggesting that costly examinations lead to diversified X/Y patent citations. One novel methodological feature of this paper is that examiner citations across jurisdictions are comparable if we employ family-to-family citations and common criteria for the X/Y citation category. Furthermore, unlike the normal citation-generating process where a citing document adds citations to prior art only once, this paper represents the first attempt to analyze a citation network with multiple citing opportunities from separate parties. We find that the variance of citation linkages has a negative relationship with the ease in which different citers evaluate prior art in the same way, thereby providing a new perspective on the notion of breadth in citation impact.     

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.     

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.     

Prediction of emerging technologies based on analysis of the US patent citation network

The network of patents connected by citations is an evolving graph, which provides a representation of the innovation process. A patent citing another implies that the cited patent reflects a piece of previously existing knowledge that the citing patent builds upon. A methodology presented here (1) identifies actual clusters of patents: i.e., technological branches, and (2) gives predictions about the temporal changes of the structure of the clusters. A predictor, called the citation vector, is defined for characterizing technological development to show how a patent cited by other patents belongs to various industrial fields. The clustering technique adopted is able to detect the new emerging recombinations, and predicts emerging new technology clusters. The predictive ability of our new method is illustrated on the example of USPTO subcategory 11, Agriculture, Food, Textiles. A cluster of patents is determined based on citation data up to 1991, which shows significant overlap of the class 442 formed at the beginning of 1997. These new tools of predictive analytics could support policy decision making processes in science and technology, and help formulate recommendations for action.     

Indirect patent citations

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.     

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.     

Patents cited in the scientific literature: An exploratory study of 'reverse' citation relations

This paper reports on a new approach to study the linkage between science and technology. Unlike most contributions to this area we do not trace citations of scientific literature in patents but explore citations of patents in scientific literature. Our analysis is based on papers recorded in the 1996-2000 annual volumes of the CD-Edition of Science Citation Index (SCI) of the Institute for Scientific Information (ISI) and patent data provided by the US Patent and Trademark Office. Almost 30,000 US patents were cited by scientific research papers. We analysed the citation links by scientific fields and technological sectors. Chemistry-related subfields tended to cite patents more than other scientific area. Among technological sectors, chemical clearly dominates followed by drugs and medical patents as the most frequently cited categories. Further analyses included a country-ranking based on inventor-addresses of the cited patents, a more detailed inspection of the ten most cited patents, and an analysis of class-field transfers. The paper concludes with the suggestions for future research. One of them is to compare our 'reverse' citation data with 'regular' patent citation data within the same classification system to see whether citations occur, irrespectively of their directionality, in the same fields of science and technology. Another question is as to how one should interpret reverse citation linkages.     

Citations as a measure of technological impact: A review of forward citation-based measures

The number of forward citations a patent receives accumulates over time and appears to be correlated to the patent‘s (i.e. invention's) technological impact. A dominant theory suggests that highly cited patents contain an important technological advance. However, a variety of citation based measures have been proposed by different authors. This study, via a narrative literature review, identified nine forward citation-based measures that appear of particular relevance. We describe each measure and present them in a comparative format.The measures are divided into two broad categories: firstly the ones that are particularly relevant to the patent level (citation index, forward citation frequency, generality, influence), and secondly the ones that are relevant to the patent portfolio level (current impact index, herfindal-hirschman index, hindrance index, relative patent position, technology strength).We hope research scholars and industrial users find this review helpful for citation analysis and intellectual property analytics, especially when wanting to employ forward citation-based measures to assess technological impact.     

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.     

Citations to the “Introduction to informetrics” indexed by WOS,Scopus and Google Scholar

Google Scholar and Scopus are recent rivals to Web of Science. In this paper we examined these three citation databases through the citations of the book “Introduction to informetrics” by Leo Egghe and Ronald Rousseau. Scopus citations are comparable to Web of Science citations when limiting the citation period to 1996 and onwards (the citation coverage of Scopus)—each database covered about 90% of the citations located by the other. Google Scholar missed about 30% of the citations covered by Scopus and Web of Science (90 citations), but another 108 citations located by Google Scholar were not covered either by Scopus or by Web of Science. Google Scholar performed considerably better than reported in previous studies, however Google Scholar is not very “user-friendly” as a bibliometric data collection tool at this point in time. Such “microscopic” analysis of the citing documents retrieved by each of the citation databases allows us a deeper understanding of the similarities and the differences between the databases.     

Publication activity, citation impact and bi-directional links between publications and patents in biotechnology

The study focuses on publication activity, citation impact and citation links between publications and patents in biotechnology. The European Union (EU), US, Japan and China are the most important global players. However, the landscape is changing since the EU and the US are losing ground because of challenges from a group of emerging economies. National profiles differ between the two groups of main players and upcoming countries; the focus on red biotechnology in the US and Europe is contrasted by propensity for white and green technology in Asia. Furthermore, the subject profile of biotechnology papers citing patents and cited by patents as well as the relationship between patent citations and citation impact in scientific literature is explored. Papers that cite patents tend to reflect propensity towards white biotechnology while patent-cited publications have a higher relative share in red biotechnology. No significant difference concerning the citation impact of publications ??citing patents?? and ??not citing patents?? can be found. This is contrasted by the observation that patent-cited papers perform distinctly better in terms of standard bibliometric indicators than comparable publications that are not linked to technology in this direction.     

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.     

Validation study: Patent citations as indicators of science and foreign dependence

The purpose of this study was to test whether the distribution of citations from issued U.S. patents could be used to measure the science dependence and the foreign dependence of patented technologies. The citations considered were front page references from U.S. patents citing to U.S. and foreign patents, to research papers and to other publications. Rankings based on the number of citations per patent to the scientific literature were compared to peer rankings of the science dependence of the technologies. Rankings based on the number of citations to foreign origin material, including foreign origin U.S. patents, foreign patents and foreign priority statements, were compared to peer rankings of the foreign dependence of the technological areas.For the analysis a total of 24 technologies were chosen. Twelve of these were judged in advance to be science dependent and twelve were judged in advance to be foreign dependent. A peer group of 19 high level R&D managers was asked to rank all 24 technologies in terms of both their science and their foreign dependence. The bibliometric rankings of the technologies, based on their citations, were then compared with the peer rankings of the technologies.Overall, a high degree of agreement was found between the experts' opinion as to the science and foreign dependence of the areas and the corresponding bibliometric rankings. For example, the eight technologies judged most science dependent by experts averaged 0.92 cites per patent to scientific journal papers, while the eight technologies judged least science dependent had only 0.05 references per patent to journal papers. Similarly, large and statistically significant differences were found in the number of cites to foreign origin material for the eight technologies judged most foreign dependent by the experts when compared with the eight technologies judged least foreign dependent by the experts. These findings provide support for the hypothesis that patent citation data can be used in technological indicators development, and in technological policy analysis. They imply that citation-based location and analysis of science and foreign dependent technologies is a valid research tool when applied to the U.S. patent system.     

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.     

Analyzing the value of technology based on the differences of patent citations between applicants and examiners

Patent applicants and examiners do not always have the same point of view when conducting a prior-art search. Although several studies have suggested differences between citations by applicants and examiners, the data and range of empirical studies are too incomplete to generalize the characteristics of relationships between citation types and the value of a technology or invention. To overcome this limitation, it is crucial to compare citations by applicants and by examiners in depth, with diverse perspectives and data, to determine the value of patent information for technological innovation. Thus, this paper suggests that the differences in the composition of technical information and patent quality in patent-level investigations as well as the locus of the knowledge source and knowledge recentness in knowledge-level investigations according to patent citation type (by applicants and examiners) reflect Pavitt’s perspective on the nature, impact, and source of technological innovation. We found that the quality of patents cited by applicants is higher than that of those by examiners in four industries, excluding a supplier-dominated industry. The citation types are related to the locus of the knowledge source in four industries, excluding the supplier-dominated industry. In particular, the patents cited by examiners tended to be more recently issued in all sectoral fields. This research contributes to confirming the technological value of patents based on the citation behaviors of applicants and examiners through empirical analysis. The results can be utilized to investigate signals or noise in technological innovation and improve processes or systems of patent examination. In addition, it can help applicants conduct more thorough prior-art searches by comprehending the examiner’s perspective toward citations to increase the probability of patent registration.     

The bibliographic coupling approach to filter the cited and uncited patent citations: a case of electric vehicle technology

Because some cited references are not relevant to the citing patent and not all the relevant references are cited, the study attempts to use the bibliographic coupling (BC) approach to filter the irrelevant patent citations and supplement the relevant uncited patent citations to construct a patent citation network (PCN). The study selected the field of electric vehicle technology to explore the phenomenon and examined the characteristics of PCNs in terms of the average BC strength and the average citation time lag. Four PCNs were constructed in this study. The aggregated PCN (APCN) excluded the irrelevant patent citations and added the relevant uncited patent citations, which has brought out significant improvement. The APCN became more concentrated and the information which reserved in the APCN was the most current. Additionally, some invisible technology clusters and relationships were also manifested in the APCN.     

Factors affecting the diffusion of patented military technology in the field of weapons and ammunition

In this paper, we carry out an empirical analysis to address some questions concerning the flow of knowledge stemming from military patented technologies. Patented military technology consists of a set of inventions which nature, uses or/and applications have defensive or offensive purposes. In this paper, we focus on the field of weapons and ammunition. Our objective is to identify, why the knowledge embedded in a military technology diffuses into other patented technologies. The methodology relies on a patent citations analysis and involves the specification of several multilevel logit models to identify the individual and country characteristics that determine the citation of military patents in subsequent patents. The data contain 1,756 citations to 582 patents of military origin with a simultaneous Europe–US protection and registered by companies/institutions from 1998 to 2003. The results reveal that military knowledge diffuses more intensively across civil patents, when the original military patent includes diverse technologies (civil and military) and is progressively less specific in terms of weapons and ammunition. Military patents filed by British, French, US, Japanese and German companies are, in this order, more likely to have a larger number of citations in subsequent civil patents. The ownership of the original military patent is not a determining factor for explaining the diffusion into civil patents, but it does influence the diffusion across mixed and military technologies. Finally, the technological capacity of the citing company also affects the type and intensity of the diffusion of the military knowledge.     

Exploring the quality of environmental technology in Europe: evidence from patent citations

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.