ABSTRACT. This article reviews and advances existing literature concerning immersive metaverse and geospatial mapping technologies, remote sensing and cognitive decision-making algorithms, and predictive modeling and machine learning-based image recognition tools. Throughout January 2023, a quantitative literature review of the Web of Science, Scopus, and ProQuest databases was performed, with search terms including “simulated 3D extended reality environments” + “digital twin-enabled Industrial Internet of Things,” “metaverse and machine intelligence technologies,” and “event modeling and forecasting tools.” As research published between 2022 and 2023 was inspected, only 147 articles satisfied the eligibility criteria. By taking out controversial or ambiguous findings (insufficient/irrelevant data), outcomes unsubstantiated by replication, too general material, or studies with nearly identical titles, we selected 25 mainly empirical sources. Data visualization tools: Dimensions (bibliometric mapping) and VOSviewer (layout algorithms). Reporting quality assessment tool: PRISMA. Methodological quality assessment tools include: AXIS, MMAT, ROBIS, and SRDR.
JEL codes: D53; E22; E32; E44; G01; G41

Keywords: digital twin-enabled Industrial Internet of Things; immersive metaverse and machine intelligence technologies; event modeling and forecasting tools; simulated 3D extended reality environments

How to cite: Cug, J., Machcinik, S., and Lăzăroiu, G. (2023). “Digital Twin-enabled Industrial Internet of Things, Immersive Metaverse and Machine Intelligence Technologies, and Event Modeling and Forecasting Tools in Simulated 3D Extended Reality Environments,” Journal of Self-Governance and Management Economics 11(1): 57–72. doi: 10.22381/jsme11120234.

Received 20 January 2023 • Received in revised form 26 March 2023
Accepted 28 March 2023 • Available online 30 March 2023