ABSTRACT. The present study systematically reviews the existing research on data-driven consumer engagement, virtual immersive shopping experiences, and blockchain-based digital assets in the retail metaverse. My findings indicate that data-driven artificial intelligence, virtual navigation tools, computer vision algorithms, and cognitive enhancement technologies. I contribute to the literature by clarifying that consumer product brands can harness predictive analytics during live shopping events across immersive virtual environments to configure customized experiences. Throughout March 2022, a quantitative literature review of the Web of Science, Scopus, and ProQuest databases was performed, with search terms including “retail metaverse” + “data-driven consumer engagement,” “virtual immersive shopping experiences,” and “blockchain-based digital assets.” As research published in 2022 was inspected, only 68 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, I selected 19 mainly empirical sources. Data visualization tools: Dimensions (bibliometric mapping) and VOSviewer (layout algorithms). Reporting quality assessment tool: PRISMA. Methodological quality assessment tools include: AMSTAR, Dedoose, Distiller SR, and SRDR.
JEL codes: D53; E22; E32; E44; G01; G41

Keywords: retail metaverse; virtual immersive shopping environment; digital asset

How to cite: Dawson, A. (2022). “Data-driven Consumer Engagement, Virtual Immersive Shopping Experiences, and Blockchain-based Digital Assets in the Retail Metaverse,” Journal of Self-Governance and Management Economics 10(2): 52–66. doi: 10.22381/jsme10220224.

Received 26 March 2022 • Received in revised form 20 June 2022
Accepted 24 June 2022 • Available online 30 June 2022

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