DOI: 10.12688/f1000research.190262.1 ISSN: 2046-1402

Artificial Intelligence and Innovation in Tourism SMEs: A Bibliometric and Systematic Review with a Constraint-Enabled Perspective

Yohannes Mekonnen Yesuf, Ziska Fields
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Artificial intelligence (AI) as a strategic driver of tourism innovation is widely recognized; however, its effect on small and medium-sized enterprises’ (SMEs) innovation performance (in developing countries) remains unknown. The current study proposes an integrated conceptual model that shows how human-centered organizational processes mediate the relationship between AI capability and innovation performance, and under context-specific conditions. Using a mixed-methods approach based on a bibliometric and systematic literature review (SLR), the study attempts to integrate these different streams of research on AI, digital transformation, and tourism innovation. Based on the Dynamic Capabilities Theory (DCT) and Technology-Organization-Environment framework, this study represents AI capability as a conglomerate factor (e.g., AI knowledge, data quality, AI infrastructures, and digital skills), influencing innovation performance (product, services, process, and marketing innovations) indirectly through digitally grounded self-efficacy, epistemic curiosity, and knowledge integration. Additionally, the study shows that the mediating effects of self-efficacy, curiosity, and knowledge integration in the relationship between AI capabilities and tourism innovation performance are moderated by institutional support and environmental limitations. The study contributes to the literature by introducing a socio-technical, context-specific perspective on AI-driven innovation at the macro level rather than technology-based perspectives. Beyond that, innovation can also be stimulated by the interaction of technology, dynamic organizational capabilities, and the external environment. Therefore, a valid empirical investigation may be based on the theoretical lens provided by the current framework and shed light on practical applications for tourism managers and practitioners in emerging countries, thereby enhancing AI capacity and boosting tourism innovation.

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