Understanding digital assistant attributes, customer perceived values and purchase intention in AI-driven retail interaction: a qualitative enquiry

Purpose The growing debate on the role of artificial intelligence (AI) in shaping customer value drags to know how it conduits between digital assistants’ (DAs’) attributes and purchase intentions. Given that, this study aims to underscore the multifaceted attribute, value and outcome in AI-driven retail interaction by underpinning the Stimulus–Organism–Response (SOR) model and the Theory of Consumption Values (TCV). Design/methodology/approach A grounded theory approach was used to conduct a thematic analysis of 52 customer responses collected through in-depth interviews. Findings Conceptualizing DA attributes and customer values into functional, social and emotional dimensions, the findings reveal that customers’ perceived values, followed by purchase intentions, are predominantly related to DA attributes. In doing so, the study identifies ten first-order constructs of attributes and nine for customer perceived values. Adding to this, the study depicts six valuable propositions, highlighting to test the relationships and offer empirical evidence. Originality/value The originality of this study lies in expanding the SOR model and the TCV in marketing value aspects, unleashing a novel attribute–value–outcome (AVO) framework and enriching the human–DA literature. It provides crucial managerial insights into understanding the role of DA attributes in shaping customer-perceived values and purchase intentions in a technology-mediated service context.