Technology cluster coupling and invulnerability of industrial innovation networks: the role of centralized structure and technological turbulence
Li Li,
Haifen Lin and
Yibo Lyu ()
Additional contact information
Li Li: Zhengzhou University of Light Industry
Haifen Lin: Dalian University of Technology
Yibo Lyu: Jiangnan University
Scientometrics, 2022, vol. 127, issue 3, No 2, 1209-1231
Abstract:
Abstract The high failure rate of industrial innovation networks restrains organizations and industries from successfully developing innovation capacity and competitiveness. Given the trend of technology convergence, technology cluster coupling arguably makes a particularly important contribution to network invulnerability. This study examines how technology cluster coupling consolidates network invulnerability at the network level and examines the relevant dynamics under conditions of technological turbulence. Based on a longitudinal patent dataset from the renewable energy industry, we conduct patent network analysis and hierarchical regression analysis. The results show that centralized structure plays a partly negative mediating role in the positive relationship between technology cluster coupling and network invulnerability, and technological turbulence plays a negative moderating role in that relationship. This study responds to the appeal to explore the impact of community interaction on network-level outcomes and risk management in the innovation network, highlighting the critical role of centralized structure and shedding light on the moderating effect of technological turbulence. Our findings offer implications for industrial policymakers seeking to govern technology clusters aimed at strengthening the invulnerability of industrial innovation networks in environments with different degrees of technological turbulence.
Keywords: Innovation network invulnerability; Technology cluster coupling; Centralized structure; Technological turbulence; Renewable energy industry; 54 (search for similar items in EconPapers)
JEL-codes: L52 O39 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)
Downloads: (external link)
http://link.springer.com/10.1007/s11192-022-04269-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:127:y:2022:i:3:d:10.1007_s11192-022-04269-x
Ordering information: This journal article can be ordered from
http://www.springer.com/economics/journal/11192
DOI: 10.1007/s11192-022-04269-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 ().