User Perceptions and Adoption of AI Chatbots in Online Retail: A Study using S-O-R Framework

Abstract: This study explores the factors influencing users’ adoption intentions of AI-based chatbots on online retail platforms through an extended Stimulus-Organism-Response (S-O-R) model. A structured survey of 150 users was analyzed using structural equation modelling via AMOS 23. Findings reveal that chatbot intelligence, usefulness, and trust significantly shape user perceptions and adoption willingness, regardless of demographic factors. The results offer practical insights for e-commerce stakeholders—designers, marketers, and developers—highlighting the importance of perceived usefulness in driving chatbot adoption. This research pioneers the integration of the S-O-R framework with AI-specific variables, offering a novel perspective on consumer decision-making in online retail. Keywords: AI-based Chatbots, Structural Equation Modelling, S-O-R Model, Perceived Usefulness