Generative Artificial Intelligence and Virtual Recruitment Tools, Wearable Self-Tracking and Augmented Reality Devices, and Multimodal Behavioral Analytics in Virtual Workplaces
Juraj Cug1, Pavol Kubala1, and Aurel Pera2ABSTRACT. In this article, previous research findings were cumulated, indicating that immersive 3D experiences can be achieved by generative artificial intelligence and remote sensing tools, employee performance metrics, and real-time predictive analytics. The contribution to the literature on generative artificial intelligence and movement and behavior tracking tools shaping career development, virtual teamworks, and employee expectations and productivity is by showing that immersive interconnected virtual experiences can be achieved by generative artificial intelligence and people analytics tools, realistic movement simulations, and mobile biometric and sentiment data. Throughout July 2023, a quantitative literature review of the Web of Science, Scopus, and ProQuest databases was performed, with search terms including “generative artificial intelligence and virtual recruitment tools” + “wearable self-tracking and augmented reality devices,” “multimodal behavioral analytics,” and “virtual workplaces.”As research published in 2023 was inspected, only 169 articles satisfied the eligibility criteria, and 50 mainly empirical sources were selected. 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.
Keywords: generative artificial intelligence; virtual recruitment tools; wearable self-tracking; augmented reality devices; multimodal behavioral analytics; virtual workplaces
How to cite: Cug, J., Kubala, P., and Pera, A. (2023). “Generative Artificial Intelligence and Virtual Recruitment Tools, Wearable Self-Tracking and Augmented Reality Devices, and Multimodal Behavioral Analytics in Virtual Workplaces,” Analysis and Metaphysics 22: 140–158. doi: 10.22381/am2220238.
Received 16 August 2023 • Received in revised form 15 December 2023
Accepted 26 December 2023 • Available online 30 December 2023