How intelligence level and compliment influence consumer satisfaction with AI service robots

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.

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Publication Details

Journal
Journal of Contemporary Marketing Science
Published
2025-12-26
DOI
https://doi.org/10.1108/jcmars-09-2025-0044
Primary Topic
AI in Service Interactions
Type
article
Field-Weighted Citation Impact
0.00
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article

How intelligence level and compliment influence consumer satisfaction with AI service robots

Jingjing He, Jing Zhao
Journal of Contemporary Marketing Science
AI in Service Interactions
article

How intelligence level and compliment influence consumer satisfaction with AI service robots

Jingjing He, Jing Zhao
article en

Abstract

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.

Journal of Contemporary Marketing ScienceVol. 9(1)
Wuhan University (CN)
Openalex Percentile: Top 18%
AI in Service Interactions
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