Patent Citations Analysis and Its Value in Research Evaluation： A Review and a New Approach to Map Technology-relevant Research

Purpose： First, to review the state-of-the-art in patent citation analysis, particularly characteristics of patent citations to scientific literature （scientific non-patent references, SNPRs）. Second, to present a novel mapping approach to identify technology-relevant research based on the papers cited by and referring to the SNPRs. Design/methodology/approach： In the review part we discuss the context of SNPRs such as the time lags between scientific achievements and inventions. Also patent-to-patent citation is addressed particularly because this type of patent citation analysis is a major element in the assessment of the economic value of patents. We also review the research on the role of universities and researchers in technological development, with important issues such as universities as sources of technological knowledge and inventor-author relations. We conclude the review part of this paper with an overview of recent research on mapping and network analysis of the science and technology interface and of technological progress in interaction with science. In the second part we apply new techniques for the direct visualization of the cited and citing relations of SNPRs, the mapping of the landscape around SNPRs by bibliographic coupling and co-citation analysis, and the mapping of the conceptual environment of SNPRs by keyword co-occurrence analysis. Findings： We discuss several properties of SNPRs. Only a small minority of publications covered by the Web of Science or Scopus are cited by patents, about 3%-4%. However, for publications based on university-industry collaboration the number of SNPRs is considerably higher, around 15%. The proposed mapping methodology based on a ＂second order SNPR approach＂ enables a better assessment of the technological relevance of research. Research limitations： The main limitation is that a more advanced merging of patent and publication data, in particular unification of author and inventor names, in still a necessity. Practical implications： The proposed mapping methodology enables the creation of a database of technology-relevant papers （TRPs）. In a bibliometric assessment the publications of research groups, research programs or institutes can be matched with the TRPs and thus the extent to which the work of groups, programs or institutes are relevant for technological development can be measured. Originality/value： The review part examines a wide range of findings in the research of patent citation analysis. The mapping approach to identify a broad range of technologyrelevant papers is novel and offers new opportunities in research evaluation practices.

On the framing of patent citations and academic paper citations in reflecting knowledge linkage:A discussion of the discrepancy of their divergent value-orientations

It has been widely recognized that academic paper citations will reflect scientific knowledge linkage.Patent citations are similar to academic paper citations in many aspects:Citation frequency distribution is often skewed; citation frequency varies from one subject field to another and authors' /inventors' preference for citing relevant literature is usually confined to their own native language.However,regardless of these seemingly similarities,the patent citation is unique and special.It is constructed by incorporating information providers from multiple sources,such as from examiners,inventors,attorneys and/or the public.It is driven by a value-orientation for the monopolization of market production under regulations of Patent Laws.It is also practiced under the sway of an industrial culture embedded with a notion of 'creative destruction'.In view of the contextual complexities of patent citations,simply applying the data criteria and citation behavior analysis of academic paper citations to that of patentbibliometrics for the purpose of reflecting knowledge linkage is both conceptually and technically illogical and unreasonable.This paper attempts to delve into the issue of the currently misconceived assertions and practice about 'transplanting' the methodology of academic paper citations en masse indiscriminately into the practice of patent citations.It is hoped that such a study would yield improved result stemming from the practice of patent citations for reflecting knowledge linkage in the future.

The impact of patent citation information flow regarding economic innovation on common stock returns:Volume vs.patent citations

This study examines whether the number of forward patent citations(along with alternative patent data)dwhen used as a proxy for the mixing variabledcould infer the aggregate amount of economic-innovation information arriving at the New York Stock Exchange(NYSE)in the United States.The results show that the number of forward patent citations,when used as a mixing variable,fails to eliminate total volatility persistence in the conditional variance equation of the exponential generalized autoregressive conditional heteroscedastic(EGARCH)model.However,the trading volume successfully eliminates total volatility persistence,thus confirming the validity of the framework used.When the volatility is modeled with an expectation of mean return,the persistence of conditional variance is deterministically increased,and the sum of the volatility coefficients exceeds unity.The inclusion of trading volume with a time trend in the variance equation rectifies the deterministic increase in the conditional volatility.These findings suggest that the form of heteroscedasticity(i.e.,as per the autoregressive conditional heteroscedastic model,ARCH model)in NYSE portfolio returns is based on the type of shocks to volatility(e.g.,deterministic vs.stochastic),which manifests as news arrivals(i.e.,new information arrivals proxied by trading volume)at the stock market.The volume therefore reflects the time dependence in the innovations to the ARCH error generation process.The response of volatility to volume persists over time when the volatility estimates are derived from the EGARCH model with an expectation for the mean of return.Backward patent citations,patent applications,and patents issued have been found to interact somewhat with trading volume,suggesting that each of these variables could play the role of an absorptive capacity variable as the new information flow associated with economic innovation(i.e.,flow of firms’stock of new knowledge)could be picked up by the trading volume.

BACKBONE OF TECHNOLOGY EVOLUTION IN THE MODERN ERA AUTOMOBILE INDUSTRY: AN ANALYSIS BY THE PATENTS CITATION NETWORK

In the automobile industry, especially in its modem era, large amount of technologies have been generated to produce automobiles. The technological evolution in this industry is formed by complicated effects of the emergence of some milestone inventions and interaction, integration, and succession among diverse technologies. It＇s a big challenge to sort out crucial inventions and technologies progresses that mainly form this industry＇s technological evolution. We use patent citation data and apply network analytical techniques to reveal characteristics of the ＂backbone＂ in the automobile industry＇s technological evolution. We employ three algorithms respectively to explore the main path of the technological evolution, the most important subnetwork which outlines the main characteristics of the industry＇s technological evolution, and the most important technological inventions （act as authorities and hubs of the technological evolution） in the industry. Main results are reported in detail by tables, figures and interpretations to disclose the most influential technologically developing path, pivotal transfers in technological trajectories, and important technological convergences and divergences over time, of the modem era automobile industry.

To identify Chinese university patents'transferability:Indicators from the perspective of bibliometrics

It is of great significance to study the indicators of university patents’transferability for improving the efficiency of the University Technology Transfer Office and promoting university patent transfer.Based on the in-depth analysis of the existing research,this paper finds that patent quality is the inherent decisive factor of patent transferability.Combining with the evaluation indexes of patent quality and the bibliometrics characteristics of university patents,9 indicators are proposed to indicate the transferability of university patents.Based on the patent transfer data of 35 Chinese universities,this paper analyzes and verifies the potential indicators of patent transfer using the binary logistic regression method.The results show that the number of inventors and the number of non-patent document citations positively predict the transferability of university patents,while the examination duration negatively predicts transferability.The effects of other indicators on transferability need to be discussed considering the actual situation and specific technology fields.