Flattery from robots, praise from humans: building consumer trust and comfort

Purpose This study aims to investigate how the interaction between service agent type (robot vs human) and language style (flattery vs praise) influences customers’ psychological comfort, alongside the dual mediating roles of affective and cognitive trust and the moderating role of emotional sensitivity. Design/methodology/approach Drawing on schema congruity theory and the affect infusion model, the study conducted three scenario-based experiments (n = 1,229) using a 2 × 2 between-subjects design that manipulated agent type and language style. The data were analyzed using ANOVA and Hayes’ PROCESS macro to test the proposed effects and underlying mechanisms. Findings The study shows that flattery (vs praise) decreases psychological comfort when delivered by human service agents but increases it when delivered by service robots. This interaction effect is mediated by affective and cognitive trust, which are weakened in human-agent encounters yet strengthened in robot-agent encounters. Furthermore, the effect is more pronounced among customers with higher levels of emotional sensitivity. Research limitations/implications The findings extend theory by demonstrating that trust formation in service interactions depends on the congruity between agent type and language style. From a managerial perspective, human employees should emphasize authentic praise to foster customer comfort, whereas service robots may strategically use moderate flattery to enhance customer experiences in routine service encounters. Originality/value This research shifts focus from macro-level technology acceptance to microlevel linguistic dynamics, offering a novel framework for understanding how strategically positive language shapes trust in AI-enabled services.