The role of smart green tourism technologies in shaping tourist intentions: Balancing authenticity and sustainability in natural tourism

This study addresses a critical gap in understanding how smart green tourism technologies (SGTT) shape tourist intentions in natural tourism settings by integrating Service-Dominant Logic (SDL) and the Theory of Planned Behavior (TPB). Unlike previous research that primarily examines SGTT in urban tourism, this study uniquely investigates its application in diverse natural tourism contexts. Grounded in these two theoretical perspectives, the research explores the extent to which smart technologies influence tourists' revisit intentions, recommendations, and the intention to buy local products, with particular attention to the differential effects of each smart tourism component. The study addresses the theoretical gap regarding the extent to which smart technologies enhance or detract from the authenticity of natural tourism experiences, while also promoting sustainable behaviors. Furthermore, this research contributes to the debate on the paradox of technology in tourism by examining how the introduction of SGTT can either enhance or undermine authenticity. By differentiating between the roles of STH, STE, and STS, the study provides empirical insights into how different types of smart tourism technologies—particularly service-based platforms— may influence sustainable choices while preserving or challenging perceived authenticity. Using a sample of 400 tourists in Thailand, the research employs structural equation modeling (SEM) to analyze the relationships between natural tourism types, smart technologies, and tourist intentions. The findings reveal that while Smart Tourism Services (STS) significantly enhance tourist intentions, Smart Tourism Hubs (STH) and Smart Tourism Experiences (STE) demonstrate more limited or non-significant influence, suggesting their impact may depend heavily on context and user expectations. This nuanced perspective advances theoretical discourse by demonstrating that different smart tourism technologies yield varying levels of influence on tourist behavior.