Data-driven Consumer Engagement, Virtual Immersive Shopping Experiences, and Blockchain-based Digital Assets in the Retail Metaverse Cover Image
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Data-driven Consumer Engagement, Virtual Immersive Shopping Experiences, and Blockchain-based Digital Assets in the Retail Metaverse
Data-driven Consumer Engagement, Virtual Immersive Shopping Experiences, and Blockchain-based Digital Assets in the Retail Metaverse

Author(s): Andrew Dawson
Subject(s): Business Economy / Management
Published by: Addleton Academic Publishers
Keywords: retail metaverse; virtual immersive shopping environment;digital assets management;

Summary/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.

  • Issue Year: 10/2022
  • Issue No: 2
  • Page Range: 52-66
  • Page Count: 15
  • Language: English
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