Analyzing behaviour of safety technologies in construction: An empirical study using the UTAUT Model in Guangdong Province, China

This study examines the behavioural determinants that influence the adoption of safety mechanisms among field workers in the construction industry in Guangdong Province, China, using the Unified Theory of Acceptance and Use of Technology (UTAUT) as the theoretical foundation. The primary objective is to evaluate how performance expectancy (PE), effort expectancy (EE), social influence (SI), and facilitating conditions (FC) shape workers’ intention to adopt (INT), and how intention subsequently affects actual adoption behaviour (AB) of safety technologies such as smart helmets and IoT wearables. The study also assesses indirect effects and convergent validity to establish robust psychometric properties of the model. Data was collected from 443 construction field workers using a structured questionnaire and analyzed using SmartPLS 4.0 for Partial Least Squares Structural Equation Modeling (PLS-SEM). The results show that facilitating conditions (β = 0.420) and social influence (β = 0.316) significantly predict intention, while intention strongly predicts adoption behaviour (β = 0.705). Effort expectancy had a weak and non-significant influence, whereas performance expectancy showed a modest positive effect (β = 0.119). Indirect effects further confirmed that facilitating conditions and social influence affect adoption behaviour through intention. These findings align with Sustainable Development Goal, SDG 8 (Decent Work and Economic Growth) and SDG 9 (Industry, Innovation, and Infrastructure) by highlighting pathways to improve occupational safety and technological integration in hazardous work environments. The study provides practical recommendations for policymakers, site managers, and technology developers to enhance the design, deployment, and support of safety innovations tailored to worker needs and workplace conditions.