Movement and Behavior Tracking Tools, and Virtual Retail Algorithms in a Real-Time Interoperable Decentralized Metaverse
Movement and Behavior Tracking Tools, and Virtual Retail Algorithms in a Real-Time Interoperable Decentralized Metaverse

Summary/Abstract: I draw on a substantial body of theoretical and empirical research on immersive retail experiences in virtual marketplaces. With increasing evidence of consumer engagement metrics, data visualization tools, and real-time predictive analytics assisting virtual retail experiences, there is an essential demand for comprehending whether frictionless immersive retail and virtual shopping experiences integrate behavioral and demographic analytics across digital marketplaces and the interconnected metaverse. In this research, prior findings were cumulated indicating that consumer location data, real-time predictive analytics, and metaverse technologies are pivotal across virtual shopping malls in immersive 3D worlds, optimizing purchase journeys. I carried out a quantitative literature review of ProQuest, Scopus, and the Web of Science throughout June 2022, with search terms including “metaverse” + “image processing computational algorithms,” “movement and behavior tracking tools,” and “virtual retail algorithms.” As I analyzed research published in 2021 and 2022, only 171 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, I decided on 35, 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.

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