Article
Consumer Engagement with AI-Enabled Retail Services: From Chatbot Interactions to Purchase Intention
The recent fusion of artificial intelligence (AI) with retail has brought changes to consumer engagement from common digital client interactions to more advanced interactive dialogue-based service interactions. This study intends to understand how the perceived AI Chatbot interactivity is responded to and subsequently how the level of engagement and trust consumers have in the AI Chatbot influence the purchase intention. Based on the Stimulus-Organism-Response (S-O-R) framework, a sequential model is created and analysed to understand the perceived AI Chatbot interactivity, consumer engagement and trust in AI Chatbots, and purchase intention. Data from 480 consumers in the six major cities of Punjab, India, who have engaged with AI retail chatbots, were collected. Exploratory factor analysis, reliability analysis, and Pearson correlation were performed followed by multiple regression analysis and sequential mediation analysis via Hayes' PROCESS Model 6 with bootstrapping. The results showed that the perceived interactivity of AI Chatbots enhanced consumer engagement, and engagement in turn raised trust in the AI Chatbots. Trust in the AI Chatbots emerged as the strongest purchase intention predictor. The sequential indirect effect of interactivity of AI Chatbots on purchase intention through consumer engagement and trust was statistically significant, whilst the other direct effects indicated partial mediation. The study has applied the S-O-R framework to the AI retail domain for the first time and revealed that the influence of chatbot interactivity on purchase intention occurs partially through an experiential to relational pathway of consumer engagement and trust. The results of the study bring to the foreground the importance of interactive AI retail systems that engage and build trust with customers.