Artikel

Analysis of technological trends and technological portfolio of unmanned aerial vehicle

Unmanned aerial vehicles (UAVs) are predicted to be the most dynamic growth sector of the world aerospace market this decade. This technology is swiftly strengthening its presence in multiple fields of human life. In the global aerospace industry, UAVs have become an essential means of securing growth and competitiveness. The investment in UAVs is estimated at billions of dollars in developed countries. However, despite the rapid growth of UAVs, few studies have classified UAV technologies into detailed technologies, or analyzed the technology development trends of UAVs. We used the latent Dirichlet allocation (LDA) method of topic modeling and network analysis to analyze the technological trends and technological portfolio of UAVs. The UAV patents were collected from the Korea Intellectual Property Rights Information Service. Analyzing the results shows that the most popular topics are communication technology (34.1%), power supply (19.5%) and navigation system (17.6%). The technological portfolio of a UAV is constituted of three groups: control system, operation system and device. This study is expected to be guidelines for developers and policy-makers on UAVs.

Sprache
Englisch

Erschienen in
Journal: Journal of Open Innovation: Technology, Market, and Complexity ; ISSN: 2199-8531 ; Volume: 6 ; Year: 2020 ; Issue: 3 ; Pages: 1-14 ; Basel: MDPI

Klassifikation
Management
Thema
network analysis
technological portfolio
technological trend
topic modeling
unmanned aerial vehicle (UAV)

Ereignis
Geistige Schöpfung
(wer)
Battsengel, Ganchimeg
Geetha, Selvaraj
Jeon, Jeonghwan
Ereignis
Veröffentlichung
(wer)
MDPI
(wo)
Basel
(wann)
2020

DOI
doi:10.3390/joitmc6030048
Handle
Letzte Aktualisierung
10.03.2025, 11:44 MEZ

Datenpartner

Dieses Objekt wird bereitgestellt von:
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.

Objekttyp

  • Artikel

Beteiligte

  • Battsengel, Ganchimeg
  • Geetha, Selvaraj
  • Jeon, Jeonghwan
  • MDPI

Entstanden

  • 2020

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