Technological Impact of Funded Research: A Case Study of Non-Patent References

Abstract

Research funding is essential to expand knowledge, foster innovation, and address the complex challenges that shape our future. The scientific literature has extensively addressed the relationship between research funding and the academic impact of publications. More recently, several studies have analyzed the technological impact of funded research as measured through citations in patents, known as Non-Patent References (NPRs). But there remains much to know about NPRs and the multiplication of case studies is necessary to characterize them. In this study, we analyze a sample of 7065 publications funded by the French Health Research Foundation (FRM) and the citations of these publications in patents. This study shows the high scientific and technological impacts of FRM funding. Indeed, the publications funded by FRM, which are cited in patents, are 3.5 times more frequently cited by other publications than the global average (for funded publications in the entire database, this ratio is 2.6). Furthermore, our results also indicate that USPTO patents citing these publications exhibit high-quality indicators. Moreover, five of these patents have led to approved drug products by the USA Food and Drug Administration (FDA). This study provides further evidence of the positive influence that research funding can have on both scientific and technological advancements.

On the peer review reports: does size matter?

“…The selection of these control variables drew from the literature, considering their potential impact on received citations. These variables encompass the journal's impact factor, the number of countries involved in the publication (indicative of international collaboration) (Ni & An, 2018), the number of funders (Quemener et al, 2023;Yan et al, 2018), the publication's openaccess status (Maddi & Sapinho, 2023), the discipline of the publication (Lillquist & Green, 2010), and the publication year (Bornmann, 2013). These variables were integrated into the model to capture and control for potential effects on our dependent variable, citations.…”