Bitte verwenden Sie diesen Link, um diese Publikation zu zitieren, oder auf sie als Internetquelle zu verweisen: https://hdl.handle.net/10419/241689 
Erscheinungsjahr: 
2021
Quellenangabe: 
[Journal:] Journal of Open Innovation: Technology, Market, and Complexity [ISSN:] 2199-8531 [Volume:] 7 [Issue:] 1 [Publisher:] MDPI [Place:] Basel [Year:] 2021 [Pages:] 1-22
Verlag: 
MDPI, Basel
Zusammenfassung: 
This study collected literature on augmented reality (AR) from academic and patent databases to plot the historic development trajectory of AR and forecast its future research and development trends. A total of 3193 and 13,629 papers were collected from academic and patent databases, respectively. First, a network was established using references from the academic literature; main path analysis was conducted on this reference network to plot the overall development trajectory. Subsequent cluster and word cloud analyses revealed the following five major groups of AR research topics: AR surgical navigation applications, AR education applications, AR applications in manufacturing, AR applications in architecture, and AR applications in visual tracking. Subsequently, the relationships between the overall development trajectory and the five AR research topics were compared. Next, the title and abstract of AR-related academic and patent papers were subjected to text mining to identify keywords with a high frequency of occurrence. The results can provide a reference for industry, government, and academia when planning future development strategies for the AR field. This research adopted an integrated analysis procedure to plot the trajectory of AR technology development and applications successfully and effectively, predict future patent research and development directions and produce technological forecasts.
Schlagwörter: 
augmented reality
citation network analysis
development trajectory
literature review
main path analysis
open innovation
Persistent Identifier der Erstveröffentlichung: 
Creative-Commons-Lizenz: 
cc-by Logo
Dokumentart: 
Article

Datei(en):
Datei
Größe
10.7 MB





Publikationen in EconStor sind urheberrechtlich geschützt.