Navigating the metaverse: unravelling employees’ sentiments and satisfaction from metaverse-based training reviews

Purpose The metaverse is described as the next disruptive technology that bears the promise of fundamentally revolutionizing the way businesses perform their functions. The potential of the metaverse is being rapidly propelled by its growing integration into business operations and multi-million-dollar corporate investments in developing metaverse-related technologies. Despite its rapid evaluation, the metaverse’s scope and its implications for human resource development function is less known. Using the machine learning approaches, this study aims to explore and demonstrate the implications of the metaverse in employee training and development function. Design/methodology/approach This paper used structural topic modeling, factor analysis and a linear regression model to perform the sentiment analysis. Findings Specifically, this study utilizes deep learning fine-grained sentiment analysis on a large quantity of employees’ online reviews about metaverse-based leading training platforms: STRIVR, Spatial Computing, Mursion, Program ACE, Rewo, Gather and ARKit, to explore employees’ sentiments and examine their connection with satisfaction ratings. The findings show that real-time collaboration is the area that most positive sentiments are linked to, followed by customized platform, real-time analytics and technology-training fit. Cybersecurity concern is the main aspect that triggers negative sentiments among trainees. The relationship between employee sentiments and satisfaction appears strong, indicating that these two aspects of employee experiences are inherently connected. Research limitations/implications This study contributes to the burgeoning literature that tries to build meaningful insight into the possible opportunities for organizations in the metaverse by highlighting its potential in human resource development. This study is among the earliest to examine the new phenomenon of using the metaverse in employee training. Practical implications The implications of the study offer useful insights for businesses transitioning from conventional to metaverse-based HR processes in the future. To implement metaverse-based training programs into training and development functions, HR managers must understand the sentiments and satisfaction levels of employees that attended such training. Originality/value This study contributes to the burgeoning literature that tries to build meaningful insight into the possible opportunities for organizations in metaverse by highlighting its potential in human resource development. This study is among the earliest to examine the new phenomenon of using metaverse in employee training.

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Publication Details

Journal
European journal of training and development
Published
2025-11-06
DOI
https://doi.org/10.1108/ejtd-06-2025-0108
Citations
1
Primary Topic
Virtual Reality Applications and Impacts
Type
article
Field-Weighted Citation Impact
1.94
Controls
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article

Navigating the metaverse: unravelling employees’ sentiments and satisfaction from metaverse-based training reviews

Ashiq Ali, Abubakr Saeed
1 citations
European journal of training and development
Virtual Reality Applications and Impacts
1.94
article

Navigating the metaverse: unravelling employees’ sentiments and satisfaction from metaverse-based training reviews

Ashiq Ali, Abubakr Saeed
article en
1 citations

Abstract

Purpose The metaverse is described as the next disruptive technology that bears the promise of fundamentally revolutionizing the way businesses perform their functions. The potential of the metaverse is being rapidly propelled by its growing integration into business operations and multi-million-dollar corporate investments in developing metaverse-related technologies. Despite its rapid evaluation, the metaverse’s scope and its implications for human resource development function is less known. Using the machine learning approaches, this study aims to explore and demonstrate the implications of the metaverse in employee training and development function. Design/methodology/approach This paper used structural topic modeling, factor analysis and a linear regression model to perform the sentiment analysis. Findings Specifically, this study utilizes deep learning fine-grained sentiment analysis on a large quantity of employees’ online reviews about metaverse-based leading training platforms: STRIVR, Spatial Computing, Mursion, Program ACE, Rewo, Gather and ARKit, to explore employees’ sentiments and examine their connection with satisfaction ratings. The findings show that real-time collaboration is the area that most positive sentiments are linked to, followed by customized platform, real-time analytics and technology-training fit. Cybersecurity concern is the main aspect that triggers negative sentiments among trainees. The relationship between employee sentiments and satisfaction appears strong, indicating that these two aspects of employee experiences are inherently connected. Research limitations/implications This study contributes to the burgeoning literature that tries to build meaningful insight into the possible opportunities for organizations in the metaverse by highlighting its potential in human resource development. This study is among the earliest to examine the new phenomenon of using the metaverse in employee training. Practical implications The implications of the study offer useful insights for businesses transitioning from conventional to metaverse-based HR processes in the future. To implement metaverse-based training programs into training and development functions, HR managers must understand the sentiments and satisfaction levels of employees that attended such training. Originality/value This study contributes to the burgeoning literature that tries to build meaningful insight into the possible opportunities for organizations in metaverse by highlighting its potential in human resource development. This study is among the earliest to examine the new phenomenon of using metaverse in employee training.

European journal of training and development
COMSATS University Islamabad (PK), Riphah International University (PK)
Openalex Percentile: Top 11%
Virtual Reality Applications and Impacts
1.94
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