Dashed expectations in service experiences. Effects of robots human-likeness on customers’ responses

Purpose There is growing interest in the use of human-like social robots, able to undertake complex tasks whilst building consumer engagement. However, further exploration is needed on the optimal level of humanoid appearance for service robots. In particular, the literature is limited with respect to mitigating disconfirmed expectations for robots high in human-likeness. This paper aims to address this gap by testing the effect of robot appearance, disconfirmed expectations and warmth (vs competence) on customers’ responses. Design/methodology/approach The study adopts a mixed-method design by presenting a focus group (Study 1) that guides two laboratory experiments (Studies 2 and 3). Studies 2 and 3 test for the moderating effect of warmth (vs competence) and the mediating roles of perceived eeriness and disconfirmed expectations. Findings The findings show that a robot high (vs low) in human-likeness leads to higher negative customers’ responses, which is explained by disconfirmed expectations rather than perceived eeriness. However, when customers interact with a warm (vs competent) robot high in human-likeness, this negative effect vanishes. Research limitations/implications The paper investigates boundary conditions and underlying mechanisms that affect customers’ experiences. Although the study adopts high realistic experiments, a limitation lies in not measuring customers’ actual behaviours in the field. Practical implications This study provides new insights on how the appearance and characteristics of social robots influence the consumers’ experience. By doing so, this study offers managers actionable insights (i.e. enhancing warmth) to lessen the risk of disconfirmed expectations. Originality/value The paper offers new explanations as to why human-like robots can generate negative responses from customers. Moving beyond the “uncanny valley” hypothesis, this study shows the key role of disconfirmed expectations in explaining consumers’ negative responses towards humanoid robots. Moreover, it sheds light on the moderating role of warmth (vs competence), which can mitigate such negative effects.