This study investigates the impact of AI-powered marketing activities (engagement, information, usability, and configuration) on destination brand equity (DBE) in the global tourism industry, emphasizing the mediating roles of destination brand love (DBL) and destination brand image (DBI). Grounded in the Stimulus-Organism-Response (S-O-R) framework, it explores how AI-driven strategies foster cognitive and affective responses to enhance destination competitiveness.
A quantitative research design was employed, using a structured online questionnaire to collect data from 390 tourists in Iran who interacted with AI-powered travel platforms within the past 12 months. Partial least squares structural equation modeling (PLS-SEM) was utilized to test the hypothesized relationships, assessing direct effects of AI-powered marketing activities on DBE, DBI, and DBL, and the mediating roles of DBI and DBL.
AI-powered marketing activities significantly enhance destination brand equity, destination brand image, and destination brand love. Both destination brand image and destination brand love serve as mediators in the relationship between AI-powered marketing activities and destination brand equity, amplifying the impact through cognitive and affective pathways. The model demonstrates strong explanatory power for destination brand equity.
The results provide actionable guidance for destination marketers, tourism boards, and AI platform developers. Prioritizing engagement (e.g. interactive chatbots) and information provision (e.g. trustworthy personalized recommendations) can strongly boost brand image and emotional attachment. Usability should focus on intuitive, mobile-friendly interfaces, while configuration requires transparent, opt-in personalization to address privacy concerns. Balancing cognitive (credibility-focused) and affective (passion-focused) strategies, alongside ethical AI practices (e.g. data transparency and bias mitigation), will help build tourist trust, loyalty, and advocacy, ultimately strengthening destination competitiveness in an AI-driven global market.
This study provides an early integrated application of the S-O-R framework to multidimensional AI-driven tourism marketing activities, offering additional insights into the cognitive (DBI) and affective (DBL) pathways through which AI strategies enhance DBE. By identifying the differential impacts of engagement, information, usability, and configuration, it offers novel theoretical insights and practical strategies for leveraging AI to foster destination loyalty and competitiveness in global markets.
