Time relations between scientific production and patenting of knowledge: the case of nanotechnologies

Knowledge flows from public science to industrial technologies

Scientific research has been acknowledged as an important knowledge resource for developing technologies. However, little is known about the heterogeneous nature of scientific knowledge and the associated contribution to technological advancement. Using nano technology as a case study, this paper investigates what types of scientific research can help improve the quality of technologies. This study uses backward and forward citation analysis, extracted from the Derwent World Patents Index. Non-patent citations from each patent are further connected with records indexed in Web of Science, and the forward citations for the cited articles are collected. On the one hand, our results confirm that there is an important contribution from science to technology. High-quality academic research has significantly contributed to the development of high-quality patents. On the other hand, this study also reveals the heterogeneous pattern of patents citing scientific publications, depending on the organizational type, country, and knowledge origin. Compared to those in the U.S., patents developed by Chinese inventors tend to reply on more recent science but with a narrower scientific scope.

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

PROPOSAL OF METHOD FOR AN AUTOMATIC COMPLEMENTARITIES SEARCH BETWEEN COMPANIES' R&D

Open innovation model is the best choice for the firms that cannot afford R&D costs but intent to continue playing the innovation game. This model offers to any firm the possibility to have companies spread worldwide and in all research fields as partners in R&D. However, the possible partnership can be restricted to the manager's know-who. Patent documents can be the source of rich information about technical development and innovation from a huge amount of firms. Search through all these daily created documents is a cumbersome task that technology managers cannot afford. This paper aims to introduce an automated model to seek matching firms' R&D using data mining techniques applied into patent documents database. The methodology considers the search for patent documents from possible partners and these data treatment through the association technique among IPC fields. An evaluation system was implemented and a sample experiment was made. The results reached are patterns of technological knowledge interdependence that can be used to evaluate four possible types of partnership.