Where do breakthroughs originate? Utilizing patent knowledge network to identify breakthrough technological innovations

Bingyi Wu and Wenhao Zhou ()
Additional contact information
Bingyi Wu: Huaqiao University
Wenhao Zhou: Huaqiao University

Scientometrics, 2025, vol. 130, issue 5, No 3, 2576 pages

Abstract: Abstract Breakthrough technological innovations have the potential to disrupt technological paradigms and are crucial drivers of technological progress. Understanding the sources of such innovations requires analyzing their knowledge composition. While previous studies have provided valuable insights into this area, they often overlook the transferability of knowledge, which can impact the accuracy of measuring knowledge novelty. To address this gap, we conceptualize the knowledge flow process of breakthrough technological innovation using the BVSR model and propose a novel method for modeling knowledge networks at the patent level. This approach effectively quantifies the knowledge structure and combination within a patent, enabling the identification of technological novelty and assessment of its impact. In an empirical analysis of 4684 pharmaceutical patents, we identified 723 breakthrough technological innovations across five distinct knowledge structures. Finally, a series of robustness checks further validated the validity and robustness of our identification results.

Keywords: Breakthrough technological innovations; Complex network; Technological novelty (search for similar items in EconPapers)
Date: 2025
References: Add references at CitEc
Citations:

Downloads: (external link)
http://link.springer.com/10.1007/s11192-025-05276-4 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:130:y:2025:i:5:d:10.1007_s11192-025-05276-4

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

DOI: 10.1007/s11192-025-05276-4

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 ().