Exploring customer adoption of autonomous shopping systems

Autonomous technology is on the rise, allowing customers to delegate shopping tasks and decisions to such artificial intelligence-based systems. However, trust and privacy issues are impeding the adoption of such technology. This study examines the factors affecting the adoption of autonomous shopping systems. A conceptual framework is developed by adding trust and moderating variables of privacy concern to the UTAUT model. Using a quantitative research design, data is collected from 454 respondents and analysed using covariance-based structural equation modelling. Results show that performance expectancy, effort expectancy, social influence, and facilitating conditions positively impact perceived trust in autonomous shopping systems. Privacy concern as a moderator dampens the positive relationship between performance expectancy and perceived trust. Also, privacy concerns dampen the positive relationship between social influence and perceived trust. This study is one of the first to empirically examine customers' autonomous shopping system intention by revising the UTAUT with trust and privacy concerns. These findings generate valuable insights into an under-researched area of customer behaviour and artificial intelligence.