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Conceptual synthesis reveals interactions between customer satisfaction and AI systems in hospitality, highlighting tensions between personalization and fairness.
Purpose This perspective revisits customer satisfaction in hospitality and tourism by connecting three lenses that are often treated separately: ethical non-projection in host–guest treatment, expectancy–disconfirmation as the core evaluative logic of satisfaction and AI-enabled systems that increasingly shape, infer and respond to guest experiences. Design/methodology/approach The paper uses a conceptual synthesis supported by a narrative review of hospitality scholarship. It interprets the Platinum Rule as a normative orientation of expectation-attentiveness and uses it alongside satisfaction and technology literature to organize a past–present–future discussion. Findings The synthesis suggests that the three lenses are complementary but tension-filled: ethical non-projection helps explain how expectations should be approached, expectancy–disconfirmation explains how experiences are judged and AI infrastructures alter both expectation formation and satisfaction management. Three recurring paradoxes emerge: personalization and efficiency versus authenticity and warmth, measurement precision versus privacy and guest agency and real-time intervention versus transparency and fairness. Practical implications Managers should match human–AI configurations to emotional complexity, treat personalization and sensing as governance choices rather than purely technical features and design recovery systems that preserve explanation, choice and fairness across settings. Originality/value Rather than presenting a fully elaborated theory, the paper offers a more integrated conceptual lens for discussing how ethical attentiveness, evaluative judgment and AI-enabled service infrastructures jointly shape satisfaction in hospitality.
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Medeiros et al. (2026) studied this question.
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