Hotel Brand Loyalty in Western Thailand: A Dual-Analytical Approach Using Structural Equation Modeling and Necessary Condition Analysis

Abstract

This study investigates the relationships among overall service quality, customer satisfaction, customer engagement behaviors, and hotel brand loyalty within the sustainable tourism context of Western Thailand's accommodation sector. It further explores the roles of online reviews, hotel management responses, and artificial intelligence technology in shaping customer perceptions. Data were collected from 459 Thai consumers with prior hotel booking experience through online platforms using a structured questionnaire. Structural equation modeling (SEM) was employed to examine sufficiency relationships among the latent constructs, while necessary condition analysis (NCA) was used to identify minimum threshold conditions for achieving high brand loyalty. The results reveal that the consumer decision-making process and guest online feedback significantly influence perceived service quality, which in turn drives customer satisfaction and engagement behaviors, ultimately leading to brand loyalty. NCA results further demonstrate that service quality and customer satisfaction function as necessary conditions for high loyalty levels, while artificial intelligence showed no statistically significant effect within this context. These findings contribute to the hospitality literature by integrating SEM and NCA to distinguish between sufficiency and necessity conditions, offering actionable insights for improving service quality and fostering long-term brand loyalty in Thai hotels.