Maturity of knowledge inputs and the breakthrough of key core technology

Xiuping Lai and Libing Nie ()
Additional contact information
Xiuping Lai: Nanjing University
Libing Nie: Hangzhou Dianzi University

Scientometrics, 2024, vol. 129, issue 11, No 3, 6570 pages

Abstract: Abstract Mature knowledge offers worthy technological resources and potential realization paths for key core technology breakthroughs. We conduct an empirical study to investigate the relationship between maturity of knowledge inputs and breakthrough of key core technologies based on the patent data of China’s chip industry from 1985 to 2020. A contingency approach to discuss the moderating role of recombinant frequency and lag is further used to provide insights into the knowledge recombination theory. Compared with merely relying on nascent or overly mature knowledge, moderate mature knowledge inputs can provide greater recombinant value for key core technology breakthroughs. The recombinant frequency could moderate the inverted U-shaped relationship between knowledge maturity and key core technology breakthrough, while the recombinant lag could strengthen the promotion effect of knowledge maturity. This study offers a novel path to achieve self-sustainability and self-improvement of key core technology. It also provides theoretical supports and practical references for the strategy of knowledge recombination and the awakening of dormant research.

Keywords: Knowledge maturity; Key core technology; Recombinant frequency; Recombinant lag (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/s11192-024-05051-x 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:11:d:10.1007_s11192-024-05051-x

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

DOI: 10.1007/s11192-024-05051-x

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 ().