How intelligence level and compliment influence consumer satisfaction with AI service robots
Jing Zhao, Jingjing He · Journal of Contemporary Marketing Science · 2025
Purpose This paper aims to investigate AI service robots' communication strategy from the perspective of compliment strategy. In particular, based on attribution theory and the Persuasion Knowledge Model, this paper examined the interactive influence of intelligence level and compliment on consumer satisfaction toward AI service robots. Design/methodology/approach This paper tested proposed hypotheses through three online experiments with different service scenarios. Findings The results show that when an AI service robot demonstrates a high intelligence level, consumers' attribution for its compliments remains at the surface level, subconsciously perceiving the compliments as expressions of warm intentions. Thereby, consumers are satisfied with the AI service robot. Conversely, when an AI service robot exhibits a low intelligence level, consumers are more likely to apply persuasion knowledge to infer the motive behind the compliments, interpreting them as ulterior motives, which consequently reduces their satisfaction with the service robot. Originality/value The findings of this research not only enrich the literature on AI service robot communication strategies but also offer practical insights to firms on how to design communication strategies for AI service robots.