This research strives to understand the resistance of elderly customers to AI-powered chatbots in banking. It applies the resistance to innovation paradigm to test the effects of barriers and the socioemotional selectivity theory to integrate future time perspective (FTP) (limited or expansive) to understand how elderly non-users perceive barriers and resistance.
This research consisted of twelve studies. In study 1, data were collected online from elderly non-users. The model was tested using SmartPLS. In Study 2, participants were randomly primed with either a limited or an expansive FTP. In Studies 3a-j, participants were randomly assigned to either high or low barrier conditions, with each study focusing exclusively on a specific barrier. All studies employed a snowball sampling method.
The findings of Study 1 indicated that FTP was negatively associated with resistance, as well as with only four barriers: value and complexity barriers (functional barriers) and information and privacy risk barriers (psychological barriers). These four barriers, in turn, were positively related to resistance. The results from Studies 2 and 3a-j validated the causal relationships among these four variables, allowing for an analysis of both the direct and indirect effects (through value, complexity, information and privacy risk barriers) of FTP on resistance.
This research is the first to consider the perception that elderly people have that the time they have left (i.e. FTP) affects the way they form barriers and resistance to AI-powered chatbots. Therefore, this research provides a novel understanding of the phenomenon of resistance based on how people view and adjust their future outlook.
