Table 1.

Theories being used in AI-driven hospitality personalization

TheoryDocuments
Restorative environment theory (grounded in attention restoration theory and stress recovery theory)Lin et al. (2025) 
Dynamic McKinsey matrixChen et al. (2025) 
Technology Acceptance Model (TAM)Mahmoud et al. (2024) 
Diffusion of Innovations Theory (DIT)
Complexity theoryPitakaso et al. (2025) 
Open innovation
Expectancy-disconfirmation theory (EDT)Mensah et al. (2025) 
SERVQUAL model
Cognitive-affective model
Task-technology fit (TTF) theoryZhang et al. (2025) 
Price fairness theoryTan et al. (2025) 
AISAS (attention → interest → search → action → share) model
Herzberg’s motivation theoryYi et al. (2024) 
Complexity theory
Zero-shot learningGuidotti et al. (2025) 
Natural language inferences
Transformer and attention mechanismFélix et al. (2025) 
Large language models
Word embedding and neural language modelsKirilenko and Stepchenkova (2025) 
Salience theory of consumer choiceAnguera-Torrell and Nicolau (2025) 
Technology acceptance model (TAM)Chotisarn and Phuthong (2025) 
SERVQUAL
Stimulus-organism-response (S-O-R)
Humanness-value-loyalty (HVL)
e-WOMKourtit et al. (2025) 
Keller’s customer-based brand equity (CBBE) modelPiriyakul et al. (2024) 
Aaker’s brand equity model
Social appraisal theory
Self-efficacy theory
Social appraisal theory
Social communication theory
Appraisal theory
Discrete emotion theoryYu et al. (2024) 
Curiosity theoryLi et al. (2024) 
Communication theoryBlanco-Moreno et al. (2024) 
Mental imagery theory
Fuzzy set theoryCamatti et al. (2025) 
Sustainability frameworkFirza et al. (2024) 
Stakeholder theory and signaling theoryGupta and Jaiswal (2024) 
Source(s): Developed by authors

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