Immersive Virtual Shopping Experiences in the Retail Metaverse: Consumer-driven E-Commerce, Blockchain-based Digital Assets, and Data Visualization Tools
Immersive Virtual Shopping Experiences in the Retail Metaverse: Consumer-driven E-Commerce, Blockchain-based Digital Assets, and Data Visualization Tools

Summary/Abstract: Based on an in-depth survey of the literature, the purpose of the paper is to explore immersive virtual shopping experiences in the retail metaverse as regards consumer-driven e-commerce, blockchain-based digital assets, and data visualization tools. In this research, previous findings were cumulated showing that livestreaming e-commerce can integrate consumer retail data to enhance real-time customization services and optimize immersive virtual shopping experiences, thus increase user engagement, and I contribute to the literature by indicating that deep learning algorithms, digital neural networks, image recognition, and data-driven decision making can drive operational efficiencies as regards customization and responsiveness, enriching customer intelligence. Throughout March 2022, a quantitative literature review of the Web of Science, Scopus, and ProQuest databases was performed, with search terms including “metaverse” + “immersive virtual shopping experiences,” “retail brands,” “consumer-driven e-commerce,” “blockchain-based digital assets,” and “data visualization tools.” As research published in 2022 was inspected, only 89 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.

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