Examining between-sectors knowledge transfer in the pharmacology field

Arida Ferti Syafiandini (), Jeeyoung Yoon (), Soobin Lee (), Chaemin Song (), Erjia Yan () and Min Song ()
Additional contact information
Arida Ferti Syafiandini: National Research and Innovation Agency (BRIN)
Jeeyoung Yoon: Yonsei University
Soobin Lee: Yonsei University
Chaemin Song: Yonsei University
Erjia Yan: Drexel University
Min Song: Yonsei University

Scientometrics, 2024, vol. 129, issue 6, No 8, 3115-3147

Abstract: Abstract Understanding knowledge transfer patterns is essential in providing valuable insights for shaping innovations and supporting economic growth. Our study identifies the main contributors and patterns of knowledge transfer within the pharmacology field from 2000 to 2019 by analyzing citation linkage and collaborative information between sector categories, affiliated institutions, and biomedical entities in articles from the Web of Science database. Our main contribution is mapping the knowledge transfer flow and identifying the main contributors to knowledge transfer within the pharmacology domain. We manually categorized affiliated institutions into four sector categories to observe knowledge transfer patterns. Subsequently, we performed a citation linkage analysis at three levels: sector categories, institution names, and biomedical entities. The results show that academic institutions are the most significant contributors to knowledge transfer in the pharmacology field, followed by commercial and government institutions. Although the majority of knowledge transfers originated from academic institutions, our study uncovered notable transfers from commercial to academic sectors and from government to academic sectors. Through named entity analysis on diseases, drugs, and genes, we found that research in the pharmacology field predominantly concentrates on subjects pertaining to cancers, chronic diseases, and neurodegenerative disorders.

Keywords: Knowledge transfer; Citation linkage analysis; Pharmacology (search for similar items in EconPapers)
Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://link.springer.com/10.1007/s11192-024-05040-0 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:scient:v:129:y:2024:i:6:d:10.1007_s11192-024-05040-0

Ordering information: This journal article can be ordered from
http://www.springer.com/economics/journal/11192

DOI: 10.1007/s11192-024-05040-0

Access Statistics for this article

Scientometrics is currently edited by Wolfgang Glänzel

More articles in Scientometrics from Springer, Akadémiai Kiadó
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().