Measuring knowledge persistence: a genetic approach to patent citation networks

Arianna Martinelli and Önder Nomaler

Journal of Evolutionary Economics, 2014, vol. 24, issue 3, 623-652

Abstract: The aim of this paper is to propose a new empirical method for identifying technologically important patents within a patent citation network and to apply it to the telecommunication switching industry. The method proposed is labelled the genetic approach, as it is inspired by population genetics: as geneticists are interested in studying patterns of migration and therefore the common origins of people, in innovation studies we are interested in tracing the origin and the evolution of today knowledge. In the context of patent and citation networks, this is done by calculating the patent’s persistence index, i.e., decomposing patent’s knowledge applying the Mendelian law of gene inheritance. This draws on the idea that the more a patent is related (through citations) to “descendent” patents, the more it affects future technological development and therefore its contribution persists in the technology. Results show that the method proposed is successful in reducing the number of both nodes and links considered. Furthermore, our method is indeed successful in identifying technological discontinuities where previous knowledge is not relevant for current technological development. Copyright Springer-Verlag Berlin Heidelberg 2014

Keywords: Patent data; Patent citation network; Technology dynamics; Telecommunication manufacturing industry; 030; 031 (search for similar items in EconPapers)
Date: 2014
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (24)

Downloads: (external link)
http://hdl.handle.net/10.1007/s00191-014-0349-5 (text/html)
Access to full text is restricted to subscribers.

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:joevec:v:24:y:2014:i:3:p:623-652

Ordering information: This journal article can be ordered from
http://www.springer.com/economics/journal/191/PS2

DOI: 10.1007/s00191-014-0349-5

Access Statistics for this article

Journal of Evolutionary Economics is currently edited by Uwe Cantner, Elias Dinopoulos, Horst Hanusch and Luigi Orsenigo

More articles in Journal of Evolutionary Economics from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().