Hey Alexa : Identity Driven Recommendation Acceptance Patterns in Voice Enabled Commerce

This research explores the role of consumer identities in the acceptance of voice assistant (VA) recommendations in e-commerce. Employing identity theory, the study examines how self-image congruence and social identity factors—such as cognitive age and tech-savviness—affect consumer attitudes and acceptance behaviors. Data from 510 voice shoppers analyzed via PLS-SEM reveal that identity alignment significantly influences the acceptance of VA suggestions. While factors like tech-savviness enhance acceptance, perceived social class has minimal impact. This investigation not only advances theoretical understanding by applying identity theory to voice commerce but also provides practical insights for designing more effective, user-centric VA systems. Moreover, it outlines the ethical, social, and cultural implications, guiding responsible AI practices in enhancing consumer experience without compromising ethical standards.