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Metaverse Engagement Metrics, Algorithmic Tracking and Spatial Computing Technologies, and Cognitive and Behavioral Algorithms in Virtual Workplaces

Metaverse Engagement Metrics, Algorithmic Tracking and Spatial Computing Technologies, and Cognitive and Behavioral Algorithms in Virtual Workplaces

ABSTRACT. The purpose of this study is to examine employee behavioral data, networked digital tools, and metaverse engagement metrics. In this article, I cumulate previous research findings indicating that employee avatars, remote collaboration tools, and spatial intelligence technology shape virtual workplaces. I contribute to the literature on interactive collaborative work on blockchain-based metaverse platforms by showing that spatial intelligence tools, quality tracking systems, and employee engagement analytics are pivotal in immersive work environments. Throughout April 2022, I performed a quantitative literature review of the Web of Science, Scopus, and ProQuest databases, with search terms including “virtual workplaces” + “metaverse engagement metrics,” “algorithmic tracking and spatial computing technologies,” and “cognitive and behavioral algorithms.” As I inspected research published in 2022, only 158 articles satisfied the eligibility criteria. By removing controversial findings, outcomes unsubstantiated by replication, too imprecise material, or having similar titles, I decided upon 29, 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.
JEL codes: E24; J21; J54; J64

Keywords: metaverse engagement metrics; algorithmic tracking and spatial computing technologies; cognitive and behavioral algorithms; virtual workplaces

How to cite: Perkins, J. (2022). “Metaverse Engagement Metrics, Algorithmic Tracking and Spatial Computing Technologies, and Cognitive and Behavioral Algorithms in Virtual Workplaces,” Psychosociological Issues in Human Resource Management 10(2): 39–54. doi: 10.22381/pihrm10220223.

Received 22 May 2022 • Received in revised form 21 October 2022
Accepted 24 October 2022 • Available online 30 October 2022

*The Center for Networked and Integrated Urban Technologies at AAER, Adelaide, Australia, james.perkins@aa-er.org.