Artificial intelligence consumer behavior: A hybrid review and research agenda

Abstract

The advancement of artificial intelligence (AI) technology and its applications has drastically transformed consumer behavior (CB). As consumers interact with these applications on multiple platforms and touchpoints, it becomes crucial to understand how these interactions affect consumer behavior and its components, including personality, attitude, engagement, decision-making, and trust. The research on the relationship between artificial intelligence and consumer behavior (hereafter referred to as AI CB) revolves around these topics and has grown exponentially in recent years. A rigorous review is required to provide directions for future studies by comprehending the extensive literature, understanding research gaps, and identifying the future directions for scholarly work. This article aims to address this research gap by analyzing 107 AI CB articles using the bibliometric and framework-based methodology to provide insights into publication trends, dominant theories, methods, antecedents, decisions, and outcomes in the AI CB literature. Most importantly, the review identifies clusters of research fronts and provides a thematic framework for current research. These clusters or themes relate to AI interaction with consumer behavior dimensions, including consumer acceptance and trust, consumer interaction and engagement, attitude and personality, decision-making, and adoption. This thematic framework and TCM-ADO analysis offer future research directions to advance theory development and have implications for industry and society.