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Pregled bibliografske jedinice broj: 1075961

Exploring knowledge flow within a technology domain by conducting a dynamic analysis of a patent co-citation network


Smojver, Vladimir; Štorga, Mario; Zovak, Goran
Exploring knowledge flow within a technology domain by conducting a dynamic analysis of a patent co-citation network // Journal of Knowledge Management, 25 (2020), 10.1108/JKM-01-2020-0079, 21 doi:10.1108/JKM-01-2020-0079 (međunarodna recenzija, članak, znanstveni)


CROSBI ID: 1075961 Za ispravke kontaktirajte CROSBI podršku putem web obrasca

Naslov
Exploring knowledge flow within a technology domain by conducting a dynamic analysis of a patent co-citation network

Autori
Smojver, Vladimir ; Štorga, Mario ; Zovak, Goran

Izvornik
Journal of Knowledge Management (1367-3270) 25 (2020); 10.1108/JKM-01-2020-0079, 21

Vrsta, podvrsta i kategorija rada
Radovi u časopisima, članak, znanstveni

Ključne riječi
Network analysis ; Knowledge flow ; Link prediction ; Future-oriented analysis ; Patent citation analysis

Sažetak
Purpose – This paper aims to present a methodology by which future knowledge flow can be predicted by predicting co-citations of patents within a technology domain using a link prediction algorithm applied to a co-citation network. Design/methodology/approach – Several methods and approaches are used: a dynamic analysis of a patent citation network to identify technology life cycle phases, patent co-citation network mapping from the patent citation network and the application of link prediction algorithms to the patent co- citation network. Findings – The results of the presented study indicate that future knowledge flow within a technology domain can be predicted by predicting patent co-citations using the preferential attachment link prediction algorithm. Furthermore, they indicate that the patent – co- citations occurring between the end of the growth life cycle phase and the start of the maturation life cycle phase contribute the most to the precision of the knowledge flow prediction. Finally, it is demonstrated that most of the predicted knowledge flow occurs in a time period closely following the application of the link – prediction algorithm. Practical implications – By having insight into future potential co- citations of patents, a firm can leverage its existing patent portfolio or asses the acquisition value of patents or the companies owning them. Originality/value – It is demonstrated that the flow of knowledge in patent co-citation networks follows a rich get richer intuition. Moreover, it is show that the knowledge contained in younger patents has a greater chance of being cited again. Finally, it is demonstrated that these co-citations can be predicted in the short termwhen the preferential attachment algorithm is applied to a patent co-citation network.

Izvorni jezik
Engleski



POVEZANOST RADA


Projekti:
IP-2018-01-7269 - Timska adaptabilnost u razvoju inovativnih proizvoda (TAIDE) (Štorga, Mario, HRZZ - 2018-01) ( POIROT)

Ustanove:
Fakultet strojarstva i brodogradnje, Zagreb,
Fakultet prometnih znanosti, Zagreb

Profili:

Avatar Url Mario Štorga (autor)

Avatar Url Goran Zovak (autor)

Citiraj ovu publikaciju

Smojver, Vladimir; Štorga, Mario; Zovak, Goran
Exploring knowledge flow within a technology domain by conducting a dynamic analysis of a patent co-citation network // Journal of Knowledge Management, 25 (2020), 10.1108/JKM-01-2020-0079, 21 doi:10.1108/JKM-01-2020-0079 (međunarodna recenzija, članak, znanstveni)
Smojver, V., Štorga, M. & Zovak, G. (2020) Exploring knowledge flow within a technology domain by conducting a dynamic analysis of a patent co-citation network. Journal of Knowledge Management, 25, 10.1108/JKM-01-2020-0079, 21 doi:10.1108/JKM-01-2020-0079.
@article{article, year = {2020}, pages = {21}, DOI = {10.1108/JKM-01-2020-0079}, chapter = {10.1108/JKM-01-2020-0079}, keywords = {Network analysis, Knowledge flow, Link prediction, Future-oriented analysis, Patent citation analysis}, journal = {Journal of Knowledge Management}, doi = {10.1108/JKM-01-2020-0079}, volume = {25}, issn = {1367-3270}, title = {Exploring knowledge flow within a technology domain by conducting a dynamic analysis of a patent co-citation network}, keyword = {Network analysis, Knowledge flow, Link prediction, Future-oriented analysis, Patent citation analysis}, chapternumber = {10.1108/JKM-01-2020-0079} }
@article{article, year = {2020}, pages = {21}, DOI = {10.1108/JKM-01-2020-0079}, chapter = {10.1108/JKM-01-2020-0079}, keywords = {Network analysis, Knowledge flow, Link prediction, Future-oriented analysis, Patent citation analysis}, journal = {Journal of Knowledge Management}, doi = {10.1108/JKM-01-2020-0079}, volume = {25}, issn = {1367-3270}, title = {Exploring knowledge flow within a technology domain by conducting a dynamic analysis of a patent co-citation network}, keyword = {Network analysis, Knowledge flow, Link prediction, Future-oriented analysis, Patent citation analysis}, chapternumber = {10.1108/JKM-01-2020-0079} }

Časopis indeksira:


  • Current Contents Connect (CCC)
  • Web of Science Core Collection (WoSCC)
    • Social Science Citation Index (SSCI)
    • SCI-EXP, SSCI i/ili A&HCI
  • Scopus


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