Talent Acquisition and Management, Immersive Work Environments, and Machine Vision Algorithms in the Virtual Economy of the Metaverse
Talent Acquisition and Management, Immersive Work Environments, and Machine Vision Algorithms in the Virtual Economy of the Metaverse

Summary/Abstract: The purpose of this study is to examine talent acquisition and management, immersive work environments, and machine vision algorithms in the virtual economy of the metaverse. In this article, I cumulate previous research findings indicating that virtual work throughout immersive work environments articulates interconnected virtual experiences by integrating workforce analytics, visual data mining, and analytic decision models. I contribute to the literature on talent acquisition and management, immersive work environments, and machine vision algorithms in the virtual economy of the metaverse by showing that remote work apps assist in talent acquisition and management and across the virtual training environment by deploying employee engagement data. Throughout February 2022, I performed a quantitative literature review of the Web of Science, Scopus, and ProQuest databases, with search terms including “metaverse” + “talent acquisition and management,” “immersive work environments,” “machine vision algorithms,” and “virtual economy.” As I inspected research published in 2022, only 79 articles satisfied the eligibility criteria. By removing controversial findings, outcomes unsubstantiated by replication, too imprecise material, or having similar titles, I decided upon 12, generally empirical, sources. Data visualization tools: Dimensions (bibliometric mapping) and VOSviewer (layout algorithms). Reporting quality assessment tool: PRISMA. Methodological quality assessment tools include: AXIS, Dedoose, MMAT, and SRDR.

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