ABSTRACT. I draw on a substantial body of theoretical and empirical research on metaverse live shopping analytics. With increasing evidence of retail data measurement tools, computer vision and deep learning algorithms, and decision intelligence and modeling, there is an essential demand for comprehending whether spatial analytics and computer vision algorithms can enhance immersive retail experiences in blockchain-based virtual worlds by leveraging business intelligence tools to determine consumer behavior and preferences. In this research, prior findings were cumulated indicating that data visualization tools can be decisive in retail analytics by optimizing experiential shopping as regards digital assets across shared virtual environments. I carried out a quantitative literature review of ProQuest, Scopus, and the Web of Science throughout March 2022, with search terms including “metaverse” + “live shopping analytics,” “retail data measurement tools,” “computer vision and deep learning algorithms,” and “decision intelligence and modeling.” As I analyzed research published in 2021 and 2022, only 72 papers met the eligibility criteria. By removing controversial or unclear findings (scanty/unimportant data), results unsupported by replication, undetailed content, or papers having quite similar titles, we decided on 19, chiefly empirical, sources. Data visualization tools: Dimensions (bibliometric mapping) and VOSviewer (layout algorithms). Reporting quality assessment tool: PRISMA. Methodological quality assessment tools include: AMSTAR, Distiller SR, ROBIS, and SRDR.
JEL codes: D53; E22; E32; E44; G01; G41

Keywords: metaverse; shopping analytics; retail data; computer vision; deep learning

How to cite: Hawkins, M. (2022). “Metaverse Live Shopping Analytics: Retail Data Measurement Tools, Computer Vision and Deep Learning Algorithms, and Decision Intelligence and Modeling,” Journal of Self-Governance and Management Economics 10(2): 22–36. doi: 10.22381/jsme10220222.

Received 24 March 2022 • Received in revised form 21 June 2022
Accepted 25 June 2022 • Available online 30 June 2022

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