Research funding and citations in papers of Nobel Laureates in Physics, Chemistry and Medicine, 2019-2020

Abstract

Purpose The goal of this study is a comparative analysis of the relation between funding (a main driver for scientific research) and citations in papers of Nobel Laureates in physics, chemistry and medicine over 2019-2020 and the same relation in these research fields as a whole. Design/Methodology/Approach This study utilizes a power law model to explore the relationship between research funding and citations of related papers. The study here analyzes 3,539 recorded documents by Nobel Laureates in physics, chemistry and medicine and a broader dataset of 183,016 documents related to the fields of physics, medicine, and chemistry recorded in the Web of Science database. Findings Results reveal that in chemistry and medicine, funded researches published in papers of Nobel Laureates have higher citations than unfunded studies published in articles; vice versa high citations of Nobel Laureates in physics are for unfunded studies published in papers. Instead, when overall data of publications and citations in physics, chemistry and medicine are analyzed, all papers based on funded researches show higher citations than unfunded ones. Originality/Value Results clarify the driving role of research funding for science diffusion that are systematized in general properties: a) articles concerning funded researches receive more citations than (un)funded studies published in papers of physics, chemistry and medicine sciences, generating a high Matthew effect (a higher growth of citations with the increase in the number of papers); b) research funding increases the citations of articles in fields oriented to applied research (e.g., chemistry and medicine) more than fields oriented towards basic research (e.g., physics). Practical Implications The results here explain some characteristics of scientific development and diffusion, highlighting the critical role of research funding in fostering citations and the expansion of scientific knowledge. This finding can support decisionmaking of policymakers and R&D managers to improve the effectiveness in allocating financial resources in science policies to generate a higher positive scientific and societal impact.

The General Theory of Scientific Variability for Technological Evolution

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Converging Artificial Intelligence and Quantum Technologies: Accelerated Growth Effects in Technological Evolution

“…One of the fundamental problems in science is how a scientific field and related technology evolve and sustain radical scientific and technological change [1][2][3][4][5][6][7][8][9][10][11][12][13][14][15][16][17][18][19]. The evolution of new research fields and path-breaking technologies, such as ICTs, nanotechnology, quantum computing, etc., can generate a convergence of fields and technologies that supports disruptive innovations with unparalleled effects in science and society [20][21][22][23][24][25][26][27][28][29].…”