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

Abstract

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 technology-relevant papers is novel and offers new opportunities in research evaluation practices.

Do younger Sleeping Beauties prefer a technological prince?

“…In the foregoing papers (van Raan 2015 , 2017a , b ) we discussed our fast and efficient search algorithm written in SQL which can be applied to the CWTS enhanced Web of Science (WoS) database. With this algorithm we can tune the following four main variables: (1) length of the sleep in years after publication ( s ); (2) depth of sleep in terms of a maximum citation rate during the sleeping period ( cs max ); (3) awake period in years after the sleeping period ( a min and a max ); and (4) awake intensity in terms of a minimum citation rate during the awake period ( ca min ).…”

“…The higher an invention’s economic value estimate was, the more the patent was subsequently cited. For an overview of patent citation analysis studies we refer to van Raan ( 2017b ).…”

Technological competitiveness of the EU member states in the era of the fourth industrial revolution

“…Nevertheless patent statistics have been widely used for assessing the competitive position in various technology fields both at firm and country levels (for an overview of merits and drawbacks of patents and patent-based indicators and databases see: Archibugi & Pianta, 1996;Dernis, Guellec, & van Pottelsberghe, 2002;Archambault, 2002;Kim & Lee, 2015;Dziallas & Blindt, 2019). Scholars apply different techniques and indicators in patent-based analyses of technological change, such as a propensity for patenting (Pantano, Priporas, & Stylos, 2018) modelling-based approach (Wallusch, 2015;Choi & Song, 2018) patent citations counts (Ernst & Omland, 2011;van Raan, 2017;Tijssen & Winnink, 2018) or use patent-based indices: revealed technological advantages-RTA, patent h-index, patent asset index, current impact index, etc. (Marinova & McAleer, 2003;Ernst & Omland, 2011;Huang, Chen, Shen, Wang, & Ye, 2015;Prud'homme, 2016;Wisla & Sierotowicz, 2016;Montresor & Quatraro, 2017;Makhoba & Pouris, 2019).…”

A patentometric assessment of selected R&D priority areas in South Africa, a comparison with other BRICS countries

“…The patents indicators are computed form the bibliographical data of patents including the IPC codes, priority numbers/dates/country, and inventor information such as address and other related data [21]. Additional approaches are claim based indicators such as the once described in the recent article [22], other approaches will be patent citation analysis and using the citation data to map technology areas and the linkages between science and technology [23,24]. Other indicators are the technology cycle time (TCT), science linkage (SL) which consider the time it takes for the patent to be referenced in other patents.…”