ABSTRACT. In this article, I cumulate previous research findings indicating that shopper engagement technologies and data visualization tools enable immersive 3D experiences across user-generated digital virtual environments. I contribute to the literature on metaverse purchase experiences achieved through augmented reality shopping tools and predictive and retail analytics by showing that customer experience analytics leverages deep learning artificial intelligence tools and metaverse technologies across virtual economy. Throughout April 2022, I performed a quantitative literature review of the Web of Science, Scopus, and ProQuest databases, with search terms including “metaverse” + “cognitive artificial intelligence and predictive modeling algorithms,” “virtual navigation and geospatial mapping tools,” and “remote sensing data fusion techniques.” As I inspected research published between 2021 and 2022, only 194 articles satisfied the eligibility criteria. By eliminating controversial findings, outcomes unsubstantiated by replication, too imprecise material, or having similar titles, I decided upon 38, generally empirical, sources. Data visualization tools: Dimensions (bibliometric mapping) and VOSviewer (layout algorithms). Reporting quality assessment tool: PRISMA. Methodological quality assessment tools include: AXIS, Dedoose, ROBIS, and SRDR.
JEL codes: D53; E22; E32; E44; G01; G41

Keywords: cognitive artificial intelligence; predictive modeling; virtual navigation; geospatial mapping; remote sensing data fusion; metaverse

How to cite: Hancock, K. (2022). “Cognitive Artificial Intelligence and Predictive Modeling Algorithms, Virtual Navigation and Geospatial Mapping Tools, and Remote Sensing Data Fusion Techniques in the Immersive Metaverse Environment,” Journal of Self-Governance and Management Economics 10(3): 40–55. doi: 10.22381/jsme10320223.

Received 23 May 2022 • Received in revised form 25 September 2022
Accepted 28 September 2022 • Available online 30 September 2022

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