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Virtual Team Performance, Collaborative Remote Work, and Employee Engagement and Multimodal Behavioral Analytics in the Metaverse Economy
Virtual Team Performance, Collaborative Remote Work, and Employee Engagement and Multimodal Behavioral Analytics in the Metaverse Economy

Author(s): Kimberly Hancock
Subject(s): Management and complex organizations, Human Resources in Economy, ICT Information and Communications Technologies
Published by: Addleton Academic Publishers
Keywords: virtual team performance; collaborative remote work; employee engagement and multimodal behavioral analytics; metaverse;

Summary/Abstract: Based on an in-depth survey of the literature, the purpose of the paper is to explore remote workforce management in the metaverse economy. In this research, previous findings were cumulated showing that immersive 3D experiences necessitate remote working tools, spatial computing technology, and employee avatars, and I contribute to the literature by indicating that people analytics tools, wearable augmented reality devices, and artificial intelligence computing capabilities configure virtual human resource management. Throughout May 2022, a quantitative literature review of the Web of Science, Scopus, and ProQuest databases was performed, with search terms including “metaverse economy” + “virtual team performance,” “collaborative remote work,” and “employee engagement and multimodal behavioral analytics.” As research published in 2022 was inspected, only 156 articles satisfied the eligibility criteria. By taking out controversial or ambiguous findings (insufficient/irrelevant data), outcomes unsubstantiated by replication, too general material, or studies with nearly identical titles, I selected 31 mainly empirical sources. Data visualization tools: Dimensions (bibliometric mapping) and VOSviewer (layout algorithms). Reporting quality assessment tool: PRISMA. Methodological quality assessment tools include: AMSTAR, Dedoose, Distiller SR, and SRDR.

  • Issue Year: 10/2022
  • Issue No: 2
  • Page Range: 55-70
  • Page Count: 16
  • Language: English