Enhancing human capital in the industrial metaverse: the role of mental workload in assembly training across different levels of immersion

Purpose We aim to enhance the understanding of how the industrial metaverse can serve as a training environment for human capital development in organizations. Therefore, we examine the impact of different training environments – that is, the real world, computer-based simulations and augmented metaverse settings – on mental workload and task performance. Our study provides insights into the metaverse as a viable alternative for training, contributing to the optimization of work processes and human capital development. Design/methodology/approach We conducted a within-subject lab experiment with 30 participants to examine the impact of different levels of immersion on mental workload and performance. Each participant completed an assembly training task in three different environments in random order. Each round concluded with the NASA-TLX questionnaire and qualitative feedback. Findings Our findings indicate that different levels of immersion in training environments do not lead to significant differences in mental workload. Moreover, prior experience with immersive technologies improves performance and reduces frustration levels, while the attitude toward immersive technologies has no measurable impact. These insights highlight the potential of the metaverse as a scalable solution for training, especially in complex and high-risk scenarios. Originality/value Our study contributes to metaverse research by linking the fields of immersive training, mental workload and human capital development. We enrich theoretical discussions about the metaverse with empirical findings from a lab experiment, offering new insights into the feasibility of immersive technologies. We hope to inspire further research into the metaverse’s role in optimizing training processes and advancing human capital.