EconPapers    
Economics at your fingertips  
 

An evolutionary process of global nanotechnology collaboration: a social network analysis of patents at USPTO

Fengchao Liu, Na Zhang () and Cong Cao
Additional contact information
Fengchao Liu: Dalian University of Technology
Na Zhang: Dalian University of Technology
Cong Cao: University of Nottingham Ningbo China

Scientometrics, 2017, vol. 111, issue 3, 1449-1465

Abstract: Abstract Using social network analysis to examine patenting data available at the USPTO, this paper explores an evolutionary process of global nanotechnology collaboration network from the perspective of entry and exit of collaborative organizations (nodes) and network’s preferential attachment process. The results show that the nanotechnology collaboration network evolved through frequent updates of the nodes and their relations (links). Compared with degree centrality and closeness centrality, betweenness centrality of an existing node was a significantly better predictor of the preferential attachment. The nodes with higher betweenness centrality were more influential to attract other nodes. This fact is observed while the network evolved. The results reveal that the core nodes with higher betweenness centrality were mostly large organizations that were equipped with core technology. They played an important broker role attracting more organizations into collaboration.

Keywords: International collaboration; Patenting; Preferential attachment; Nanotechnology; Social network analysis (search for similar items in EconPapers)
Date: 2017
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3) Track citations by RSS feed

Downloads: (external link)
http://link.springer.com/10.1007/s11192-017-2362-6 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:111:y:2017:i:3:d:10.1007_s11192-017-2362-6

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

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 ().

 
Page updated 2019-05-21
Handle: RePEc:spr:scient:v:111:y:2017:i:3:d:10.1007_s11192-017-2362-6