Factors affecting chatbots in banking services: the UTAUT2 and innovation resistance theory perspective

This paper aims to investigate the factors affecting the users’ intention to use chatbots for banking service requirements. Based on the survey of 194 individuals, a partial least square and structural equation modelling (PLS–SEM) is employed to examine the factors affecting behavioural intention. Furthermore, a sub-sample analysis based on age (Gen Z and older age individuals) is performed to uncover the unique effects of various factors depending on the age groups. We find the positive effect of hedonic motivation, performance expectancy and social influence on behavioural intention, whereas the risk barrier has a negative effect on behavioural intention. Further sub-sample analysis reveals interesting results. Hedonic motivation’s effect is observed only for Gen Z individuals, whereas the effect of social influence is observed only for the older age groups. The effects of performance expectancy and risk barrier are observed for both the sub-samples. The current study contributes to the extant literature in two ways. First, the findings contribute to the ongoing research on the application of Artificial Intelligence (AI) in general and chatbots in particular. Though there is growing research on chatbots in the last few years, there is a lack of empirical studies on chatbots for banking services specifically. Second, this study empirically validates the UTAUT2 and IRT theories, particularly the fusion of the two in explaining the innovation adoption.