Recent literature emphasises the necessity for further exploration in the domain of smart helmet technologies. This study aims to investigate the factors that instil trust in these devices and the determinants driving users' recommendation behaviour. Task technology fit and parasocial relationship theory serve as the foundational frameworks for this investigation.
Employing a deductive approach, this study used purposive sampling to collect responses from 312 respondents. Data analysis was performed using partial least squares structural equation modelling (PLS-SEM) to test the hypothesised research model.
The results indicate that navigation quality and safety quality directly influence users’ recommendation behaviour. In contrast, anthropomorphism does not exert a direct effect on recommendation behaviour; instead, it operates through a full mediation effect of trust. Furthermore, navigation quality, anthropomorphism and safety quality significantly impact users’ trust. Trust demonstrates a significant positive influence on users’ recommendation intention and partially mediates the relationships between navigation quality and safety quality and users’ recommendation behaviour.
This study offers valuable insights for product developers, marketers and policymakers regarding smart helmet design and marketing. The identification of trust-enhancing factors like navigation quality, anthropomorphism and perceived safety quality offers insights for stakeholders to prioritise these attributes in product development to meet consumer expectations. For policymakers, these insights can guide regulations that promote safety, enhance user experiences in smart wearable devices and drive recommendations for smart helmets.
This study fills a critical gap in the existing literature on smart helmets. Where prior research has largely been confined to technical, conceptual, or experimental dimensions, the empirical validation of the hypothesised relationships within the smart helmet context offers critical insights and contributes a unique empirical perspective to the field. The study’s novel approach provides a deeper understanding of the behavioural dynamics and offers actionable knowledge that can inform both academic discourse and industry practices.
