Measuring knowledge persistence : a genetic approach to patent citation networks

A. Martinelli, Z.O. Nomaler

Research output: Contribution to journalArticleAcademicpeer-review

35 Citations (Scopus)
3 Downloads (Pure)


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.
Original languageEnglish
Pages (from-to)623-652
Number of pages30
JournalJournal of Evolutionary Economics
Issue number3
Publication statusPublished - 2014


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