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Interdisciplinary research and technological impact: evidence from biomedicine

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Abstract

Interdisciplinary research (IDR) has been considered as an important source for scientific breakthroughs and as a solution to today’s complex societal challenges. While ample empirical evidence has suggested its benefits within the academia such as better creativity and higher scientific impact and visibility, its societal benefits—a key argument originally used for promoting IDR—remain relatively unexplored. Here, we study one aspect of societal benefits, that is contributing to the development of patented technologies, and examine how IDR papers are referenced as “prior art” by patents over time. We draw on a large sample of biomedical papers published in 23 years and measure the degree of interdisciplinarity of a paper using three popular indicators, namely variety, balance, and disparity. We find that papers that cites more fields (variety) and whose distributions over those cited fields are more even (balance) are more likely to receive patent citations, but both effects can be offset if papers draw upon more distant fields (disparity). These associations are consistent across different citation-window lengths. We further find that conditional on receiving patent citations, the intensity of their technological impact, as measured as both raw and quality-adjusted number of citing patents, increases with balance and disparity. Our work may have policy implications for interdisciplinary research and scientific and technological impact.

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Notes

  1. https://www.nlm.nih.gov/medline/medline_overview.html.

  2. The lists of qualifying and disqualifying tags can be found at https://icite.od.nih.gov/user_guide?page_id=ug_data.

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Acknowledgements

Part of this work was performed while the author was with Northeastern University and Syracuse University. I acknowledge the data and computing resources provided there. The author was partially supported by the National Natural Science Foundation of China (72204206), City University of Hong Kong (Project No. 9610552), and Hong Kong Institute for Data Science.

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Correspondence to Qing Ke.

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The author declares no competing interests.

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Supplementary file1 (PDF 190 kb)

Appendix

Appendix

See Tables 6, 7, 8, 9, 10, 11, 12.

Table 6 Correlations between variables
Table 7 Logistic regression modeling of whether a paper has patent citations in 5 years
Table 8 Logistic regression modeling of whether a paper has patent citations in 15 years
Table 9 Negative binomial regression modeling of 5-year patent citations
Table 10 Negative binomial regression modeling of 15-year patent citations
Table 11 Negative binomial regression modeling of weighted 5-year patent citations
Table 12 Negative binomial regression modeling of weighted 15-year patent citations

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Ke, Q. Interdisciplinary research and technological impact: evidence from biomedicine. Scientometrics 128, 2035–2077 (2023). https://doi.org/10.1007/s11192-023-04662-0

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  • DOI: https://doi.org/10.1007/s11192-023-04662-0

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