Explaining Tourism Behavior With Machine Learning: A SHAP-Based Analysis of Certification Awareness and Revisit Intentions

Tourist satisfaction is significantly influenced by both attraction features and supporting facilities. While prior studies underscore the importance of measuring satisfaction to sustain a destination’s competitiveness, limited attention has been paid to the role of environmental certifications in shaping revisit intentions. This study adopts a mixed-methods approach, combining qualitative insights from in-depth interviews with machine learning analysis of field survey data collected from visitors to Blue Flag-certified beaches. The findings reveal that certification enhances the perceived quality of beach destinations. However, its impact on tourists’ intention to revisit is contingent on their awareness and understanding of the certification. The study highlights the importance of not only maintaining high environmental and service standards but also actively communicating the value of certification to beachgoers. These insights offer critical implications for policymakers and destination managers aiming to foster sustainable tourism through behavioral engagement and informed decision-making.