Self-efficacy and personal innovation in the intention to use of facial recognition systems by tourists: a mediation model moderated by trust and anticipated emotions.

Abstract

Facial recognition systems are crucial for personalising and enhancing user experiences in tourism. These technologies reliably verify identities and improve security and efficiency in areas such as airports and hotels. However, there is a lack of research on the psychological and emotional factors shaping the use of these technologies. This study proposes a novel conceptual model that examines how self-efficacy and personal innovation influence the intention to use facial recognition systems, through a model mediated by trust and moderated by anticipated emotions, to better understand the psychological and emotional dynamics underlying the use of emerging biometric technologies in the context of tourism. We issued a survey to 1027 frequent tourists and analysed their data using PLS-SEM. The results highlight the importance of users’ self-efficacy, trust and emotions in their predisposition to use facial recognition systems. Furthermore, this study considers the potential practical implications for developers and administrators of tourist destinations.