This study aims to rethink smartness in smart hotels by moving beyond functionalist perspectives emphasizing automation and connectivity. Perceived smartness is reconceptualized as a higher-order cognitive evaluation reflected in guests’ perceptions of smart service experiences. The study examines how perceived smartness influences guest experiences, satisfaction, engagement and revisit intention.
This study is grounded in the Stimulus-Organism-Response (S-O-R) framework and used a multi-method design. Within this framework, smart hotel technologies represent environmental stimuli, perceived smart service cues serve as interpretive signals, and perceived smartness represents an organism-level cognitive evaluation reflected in these perceptions. A qualitative phase with 34 participants who had recent smart hotel experience informed survey development. In the quantitative phase, 304 valid responses were collected, primarily from well-educated, professionally active individuals in their 30s. Data were analyzed using structural equation modeling, fuzzy-set qualitative comparative analysis (fsQCA) and artificial neural networks (ANN) to examine linear, configurational and non-linear relationships.
Results reveal that emotional pathways (memorable experience, satisfaction, online engagement) are stronger predictors of revisit intention than purely functional pathways. Moreover, fsQCA highlights multiple equifinal configurations leading to loyalty, while ANN confirms the superior predictive accuracy of models incorporating emotional variables.
This study contributes to the smart hospitality literature by reconceptualizing perceived smartness as a higher-order cognitive evaluation reflected in guests’ perceptions of smart service experiences, rather than a simple aggregation of functional features. By integrating multiple analytical methods, the study provides theoretical insights into human−artificial intelligence interaction in hospitality and offers actionable strategies for developing guest-centric smart hotel experiences.
