Information from the abstract
Artificial intelligence (AI) is reshaping tourism service operations, smart tourism ecosystems, and digital customer engagement, yet many tourism SMEs still struggle to convert AI readiness into operational capability and firm performance. This study develops a staged capability-conversion model that integrates the Technology-Organization-Environment (TOE) framework, Social Cognitive Theory, the Resource-Based View, and Dynamic Capabilities Theory. Using a quantitative cross-sectional design, data were collected from employees and managers of tourism SMEs, particularly small and medium-sized travel agencies in mainland China. After data screening, 433 valid responses were analyzed using exploratory factor analysis, confirmatory factor analysis, covariance-based structural equation modeling, and 5000-resample bootstrap mediation testing. The results suggest that organizational readiness is the most consistent readiness-related antecedent, digital self-efficacy is positively associated with AI adoption and operational capability, and operational capability shows the strongest direct association with perceived firm performance. These findings are consistent with the view that AI-enabled value in tourism SMEs is associated less with technology adoption alone than with the conversion of readiness into behavioral and operational capabilities.
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Related topics: AI in Service Interactions · Digital Transformation in Industry · Technology Adoption and User Behaviour
Thai researcher and institutional participation
Tao Mei · Mahachai Sattayathamrongthian · Rajamangala University of Technology Rattanakosin
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