Let's face it: Are customers ready for facial recognition technology at quick-service restaurants?

This study aims to provide an integrated model that examines the determinants of customer intention to use facial recognition systems (FRS) in quick-service restaurants (QSRs). An extended model built based on the unified theory of acceptance and use of technology (UTAUT) was tested via structural equation modeling (SEM) using data collected from a sample of 558 QSR customers. The results showed that perceived performance expectancy, social influence, and trust in the system significantly and positively affect customer intention to use FRS to access loyalty and payment accounts. Furthermore, customer hedonic motivation had a positive effect on the intention to use FRS for authorization to their loyalty accounts, but no effect on the intention to use this technology for payment account authorization. The developed model would be helpful to managers for making a decision of utilizing FRS in QSRs and promoting the technology among customers.

Automated summary

This study found that customer intention to use facial recognition systems in quick-service restaurants is positively influenced by perceived performance expectancy, social influence, and trust in the system. Customer hedonic motivation has a positive effect on the intention to authorize access to loyalty accounts using the system, but no effect on the intention to authorize payment accounts.