Abstract
Climate change is increasingly reshaping the viability, stability, and competitiveness of alpine tourism, creating an urgent need for predictive frameworks capable of anticipating disruptions and supporting adaptive transformation. This study introduces the AI-Integrated Resilience System (AIRS), a hybrid deep learning framework that operationalizes destination resilience as a computationally measurable and dynamically evolving construct. AIRS integrates environmental, economic, socio-behavioral, and institutional indicators to generate the Destination Resilience Index (DRI), enabling scenario-based analysis, temporal tracking, and evidence-driven governance. Using a comprehensive multi-source dataset (2010–2024)—including MeteoSwiss climate observations, national tourism statistics, operational hotel metrics, and a behavioral survey of 620 tourists—the study trains three complementary models: LSTM-Attention, Gradient Boosted Trees (GBT), and ANFIS behavioral inference, which are fused using a meta-learning integration layer. The hybrid AIRS model achieves a MAPE of 5.4%, a 63% improvement over conventional forecasting approaches. Findings show high baseline resilience in the Swiss Alps (DRI = 0.82) but substantial vulnerability under snow-dependent conditions (0.69) and compound climate–economic stressors (0.61). AI-optimized hotel operations further deliver measurable sustainability gains, reducing energy use by 12%, water consumption by 9%, and waste generation by 15%, with a 4.4-year financial payback. Behavioral modeling reveals that memorable tourism experiences mediate 32% of the relationship between environmental perception and pro-environmental behavior, highlighting the experiential basis of sustainability transitions. Theoretically, the study quantifies systemic resilience and links micro-behavioral dynamics with macro-destination performance. Practically, AIRS provides a powerful tool for crisis anticipation, operational optimization, behavioral targeting, and adaptive governance, supporting more equitable and ecologically grounded tourism futures.
Details
Presentation Type
Theme
2026 Special Focus—Pathways to Resilience; Sustainable Practices in Tourism and Leisure
KEYWORDS
AI-Enabled Resilience, Deep Learning, Destination Resilience Index, Climate Change Adaptation
