Drivers and inhibitors of consumers’ adoption of AI-driven drone food delivery services

This study sheds light on the determinants of consumers’ adoption of artificial intelligence-driven drone food delivery service (AI-driven DFDS) using a mixed-methods approach. Interviews with hospitality industry professionals revealed several drivers and inhibitors of AI-driven DFDS adoption. Using these findings, we developed a theoretical model AI-driven DFDS adoption based on the premise of the behavioral reasoning theory and innovation resistance theory. The model was tested using data collected from 1240 consumers. The results suggest that drones’ relative advantage, perceived ubiquity, social influence, and green image positively influence attitudes and adoption. Risk, usage, and experience barriers have an adverse influence on attitudes and adoption. Consumers’ openness to new technology has a positive influence on ‘reasons for’ using AI-driven DFDS. The research makes an important theoretical contribution to research on the adoption of AI-driven DFDS. The study also provides important practical implications for marketers and industry professionals. • Mixed-method research design to analyze the enablers and barrier of AI-driven DFDS. • Robust Framework to comprehend intention to use AI-driven DFDS using BRT. • Strategic guidance to service providers for sustainable technology adoption. • Aids policy makers to apprehend risks and challenges experienced by consumers.