Modeling Sustainable Urban Tourism with Digital Self-Guided Tours: A Smart City Perspective

The rise of independent travel is reshaping tourism, moving away from mass tourism and rigid itineraries toward flexible, technology-driven, and sustainable experiences. This study examines how self-guided digital tours can reduce congestion at points of interest while maintaining visitor engagement. Using a stylized agent-based simulation implemented with the Mesa framework, we modeled guided and self-guided tourist groups to compare congestion patterns, travel flows, and completion rates. The results indicate that self-guided tours flatten congestion peaks and support decentralized, walking-based exploration while maintaining comparable engagement levels. The findings suggest that digital self-guided formats can complement urban visitor management and smart-city strategies by distributing tourist flows more evenly. Future research should calibrate the model with real-world data and case studies to validate and extend these results. This study contributes to the discourse on sustainable urban tourism by positioning self-guided tours as a tool for integrating visitor management into smart infrastructure and enhancing long-term cultural and environmental resilience.