Investigating the Temporal Association of Biomedical Research on Small Business Funding: A Bibliometric and Data Analytic Approach

Reza Khanmohammadi, Simerjot Kaur, Charese H. Smiley, Tuka Alhanai, Ivan Brugere, Armineh Nourbakhsh, Mohammad M. Ghassemi

Research output: Contribution to journalArticlepeer-review

Abstract

The relationship between scientific innovation in biomedical sciences and its impact on industrial activities is a complex and dynamic process. This article investigates the relationship between science and industrial innovation, focusing on how the historical impact and content of scientific paper abstracts are associated with future funding and innovation grant application content for small businesses. The research incorporates bibliometric analyses along with small business innovation research (SBIR) data to yield a holistic view of the science-industry interface. We quantify the temporal effects and impact latency of scientific advancements on industrial activity across 10 873 topics and take into account their taxonomic relationships, spanning from 2010 to 2021. We find that the impact of scientific advances on industrial projects across different thematic depths consistently exhibited p-values less than 0.05, underscoring the significant predictive power of contemporary scientific activities on future industrial projects. Further, we demonstrate that the semantic contents of scientific paper abstracts within a topic are associated with future industrial project description text embeddings. The frequency analysis reveals that various scientific activities significantly inform future industrial project funding across varying depths of MeSH topic categorization, highlighting the significant role of science in steering industrial innovation. This study demonstrates that the impact of scientific research on industrial innovation extends beyond the mere volume of scientific output, but is greatly influenced by its impact, the broader themes it advances, and the meaningful narratives it presents.

Original languageEnglish (US)
JournalIEEE Transactions on Computational Social Systems
DOIs
StateAccepted/In press - 2024

Keywords

  • Bibliometric analysis for social innovation
  • digital transformation in biomedicine
  • healthcare innovation
  • innovation ecosystems
  • science-industry interface

ASJC Scopus subject areas

  • Modeling and Simulation
  • Social Sciences (miscellaneous)
  • Human-Computer Interaction

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