Factors influencing the use of VR technology for safety training among electric industry workers in China: an extended TAM

Despite the potential of virtual reality (VR)-based safety training to reduce fatalities in the electric industry, its success depends on worker acceptance. This study validated an extended technology acceptance model incorporating self-efficacy (SE), facilitating conditions (FC), and technology anxiety (TA) using data from 341 electric industry workers. Results confirmed that while SE and FC are significant positive predictors of perceived usefulness (PU) and perceived ease of use (PEOU) (p < 0.05), TA exerts a significant negative influence on PEOU and PU (path coefficients of − 0.194 and − 0.217, respectively). Structural equation modeling indicated that the research model explained a substantial proportion of variance: 38.1% for PEOU, 61.5% for PU, 65.6% for attitude, and 44.7% for intention to use. These findings provided an evidence-based framework for stakeholders to bolster user confidence and mitigate technological anxiety, thereby accelerating the strategic adoption of VR safety training in high-risk electrical environments.

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Publication Details

Journal
Scientific Reports
Published
2026-04-28
DOI
https://doi.org/10.1038/s41598-026-49473-4
Primary Topic
Virtual Reality Applications and Impacts
Type
article
Field-Weighted Citation Impact
0.00
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article

Factors influencing the use of VR technology for safety training among electric industry workers in China: an extended TAM

Changjian Zeng, Fucai Huang, Li Li, Siu Shing Man et al.
Scientific Reports
Virtual Reality Applications and Impacts
article

Factors influencing the use of VR technology for safety training among electric industry workers in China: an extended TAM

Changjian Zeng, Fucai Huang, Li Li, Siu Shing Man, Caiyu Lin, Jianwei He, Chuanbing Li
article en

Abstract

Despite the potential of virtual reality (VR)-based safety training to reduce fatalities in the electric industry, its success depends on worker acceptance. This study validated an extended technology acceptance model incorporating self-efficacy (SE), facilitating conditions (FC), and technology anxiety (TA) using data from 341 electric industry workers. Results confirmed that while SE and FC are significant positive predictors of perceived usefulness (PU) and perceived ease of use (PEOU) (p < 0.05), TA exerts a significant negative influence on PEOU and PU (path coefficients of − 0.194 and − 0.217, respectively). Structural equation modeling indicated that the research model explained a substantial proportion of variance: 38.1% for PEOU, 61.5% for PU, 65.6% for attitude, and 44.7% for intention to use. These findings provided an evidence-based framework for stakeholders to bolster user confidence and mitigate technological anxiety, thereby accelerating the strategic adoption of VR safety training in high-risk electrical environments.

Scientific Reports
Longyan University (CN), Fujian Electric Power Survey & Design Institute (CN), Ningde Normal University (CN), South China University of Technology (CN)
Industry, innovation and infrastructure
Openalex Percentile: Top 5%
Virtual Reality Applications and Impacts
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