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Virtual Employee Training and Skill Development, Workplace Technologies, and Deep Learning Computer Vision Algorithms in the Immersive Metaverse Environment

Virtual Employee Training and Skill Development, Workplace Technologies, and Deep Learning Computer Vision Algorithms in the Immersive Metaverse Environment

ABSTRACT. In this article, I cumulate previous research findings indicating that virtual reality and text analytics tools are instrumental in performance metric analysis as regards virtual work, remote workforce, and collaborative remote work. I contribute to the literature on virtual employee training and skill development, workplace technologies, and deep learning computer vision algorithms in the immersive metaverse environment by showing that virtual reality-based recruiting tools integrate sensory immersion, sentiment data, voice biometrics, and cognitive computing systems across 3D digital worlds. Throughout March 2022, I performed a quantitative literature review of the Web of Science, Scopus, and ProQuest databases, with search terms including “metaverse” + “virtual employee training and skill development,” “workplace technologies,” “deep learning computer vision algorithms,” and “immersive environments.” As I inspected research published in 2022, only 83 articles satisfied the eligibility criteria. By eliminating controversial findings, outcomes unsubstantiated by replication, too imprecise material, or having similar titles, I decided upon 14, 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, ROBIS, and SRDR.
JEL codes: E24; J21; J54; J64

Keywords: virtual; employee; training; skill; metaverse; immersion

How to cite: Hawkins, M. (2022). “Virtual Employee Training and Skill Development, Workplace Technologies, and Deep Learning Computer Vision Algorithms in the Immersive Metaverse Environment,” Psychosociological Issues in Human Resource Management 10(1): 106–120. doi: 10.22381/pihrm10120228.

Received 28 March 2022 • Received in revised form 25 May 2022
Accepted 28 May 2022 • Available online 30 May 2022

*The Center for Datafied Urban Governance at AAER, Melbourne, Australia, mark.hawkins@aa-er.org.