Is Social Presence in Banking Chatbots Relevant? A Multidimensional Multi-analytic Approach

Abstract

This study draws on social presence theory, the extended technology acceptance model and the stimulus-organism-response model to examine the interplay among significant factors affecting the consumers’ behavioural intentions to adopt artificial intelligence (AI)-assisted banking chatbots. Furthermore, it investigates the moderating role of fear of missing out between the dimensions of social presence theory and consumers’ behavioural intention. A structured questionnaire was floated among the consumers of selected Indian banks using convenience-cum-referral sampling approach. The 365 valid responses were analysed using covariance-based structural equation modelling and artificial neural network analysis. The extended technology acceptance model components partially mediate the relationship between social presence theory variables and behavioural intentions. Among the three social presence theory dimensions, social presence of interaction exerts more impact on extended technology acceptance model components. The results of the artificial neural network reveal that perceived enjoyment is the most critical predictor of consumers’ intention to adopt AI-assisted banking chatbots.