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Author Co-citation Analysis for Digital Twin Studies

디지털 트윈 연구의 저자 동시인용 분석

  • 김수민 (경북대학교 대학원 경영학부) ;
  • 서창교 (경북대학교 경영학부)
  • Received : 2019.06.02
  • Accepted : 2019.08.23
  • Published : 2019.09.30

Abstract

Purpose A digital twin is a digital replication of a physical system. Gartner identified the digital twin as one of the Gartner Top 10 Strategic Technology Trend for three years from 2017. The rapid development of the digital twin market is expected to bring about innovation and change throughout society, and much research has been done recently in academia. In this research, we tried to explore the main research trends for digital twin research. Design/methodology/approach We collected the digital twin research from Web of Science, and analyzed 804 articles that was published during time span of 2010-2018. A total of 41 key authors were selected based on the frequency of citation. We created a co-citation matrix for the core authors, and performed multivariate analysis such as cluster analysis and multidimensional scaling. We also conducted social network analysis to find the influential researchers in digital twin research. Findings We identified four major sub- areas of digital twin research: "Infrastructure", "Prospects and Challenges", "Security", and "Smart Manufacturing". We also identified the most influential researchers in digital twin research: Lee EA, Rajkumar R, Wan J, Karnouskos S, Kim K, and Cardenas AA. Limitation and further research suggestion were also discussed as a concluding remarks.

Keywords

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