ScholarWorks@성균관대학교

초록

Grounded in the stimulus-organism-response model and diffusion of innovations theory, this study investigates how artificial intelligence (AI) enhanced social media strategies influence revisit behaviour using chain and independent hotels as a case. Drawing on data from 854 hotel customers in Tehran, this study tests the effects of AI on both customer brand engagement and conversion rate optimization, examining how these constructs shape customer satisfaction and revisit behaviour. This study also incorporates the moderating influences of privacy concerns, age, and hotel type to capture the dynamics of AI-driven advertising across different hotel contexts. Using structural equation modelling, the findings reveal that AI on social media significantly enhances customer brand engagement and satisfaction, which, in turn, strengthen revisit intentions. Privacy concerns suppress revisit intentions in independent hotels but not in chain hotels. Moreover, younger customers respond more positively to AI on social media in independent hotels, whereas older guests prefer the consistency of chain hotels. This study, therefore, contributes to the advertising and hospitality literature by integrating underexplored moderators and providing empirical support for AI's role in shaping customer behaviour through digitally mediated brand experiences via social media.

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