EconPapers    
Economics at your fingertips  
 

Extracting knowledge patterns with a social network analysis approach: an alternative methodology for assessing the impact of power inventors

Massimiliano Ferrara (), Roberto Mavilia () and Bruno Antonio Pansera
Additional contact information
Roberto Mavilia: Bocconi University
Bruno Antonio Pansera: Mediterranean University of Reggio Calabria

Scientometrics, 2017, vol. 113, issue 3, 1593-1625

Abstract: Abstract This paper proposes a new, alternative analysis of patent data in order to extract knowledge patterns from inventors’ collaboration networks. Indeed, moving from a basic network analysis, we provide new developments to map and study co-inventorship. The goal of this research is to provide an overall understanding of the dynamics concerning knowledge flows in inventive activities. We show how the network of inventors is, on average, increasing in size: more and more inventors are contributing to technology innovations and they are more connected to each other. We also show to what extent inventors from different countries tend to cooperate with their local peers or internationally. Furthermore, an analysis of the clustering of inventors is carried out to show differences across countries in the structure of inventors’ communities, with a particular focus on the dynamics of collaboration for power inventors (i.e. star inventors).

Keywords: Patents; Knowledge pattern extraction; Social network analysis; Power inventors (search for similar items in EconPapers)
JEL-codes: O31 O57 D21 F63 L14 (search for similar items in EconPapers)
Date: 2017
References: View references in EconPapers View complete reference list from CitEc
Citations: Track citations by RSS feed

Downloads: (external link)
http://link.springer.com/10.1007/s11192-017-2536-2 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:113:y:2017:i:3:d:10.1007_s11192-017-2536-2

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 2019-11-06
Handle: RePEc:spr:scient:v:113:y:2017:i:3:d:10.1007_s11192-017-2536-2