Purpose This study aims to examine how stochastic multi-criteria acceptability analysis (SMAA) can improve the measurement of tourism sustainability across regions. It addresses the limits of deterministic indices by incorporating uncertainty in weighting schemes, providing insights into the robustness and stability of sustainability performance. Design/methodology/approach A quantitative approach integrates 47 economic, environmental and social indicators within the SMAA framework. Data from national and European statistical sources were analysed through one million simulations of alternative weighting structures, generating rank acceptability indices, probability distributions and correlation-based importance analysis. Findings Results show strong heterogeneity. Abruzzo and Veneto emerge as robust leaders, while Calabria, Sicily and Trentino-South Tyrol display fragility. Environmental management and resource efficiency drive resilient performance, whereas reliance on short-term economic factors yields unstable outcomes. Sustainability is thus not mechanically tied to economic development but depends on balancing multidimensional trade-offs. Originality/value This study offers the first application of SMAA to tourism sustainability, showing how probabilistic methods capture ranking stability beyond deterministic hierarchies. It advances methodological debates on synthetic indicators and provides actionable insights for policymakers and managers, encouraging adaptive, inclusive and ecologically grounded strategies for competitiveness and resilience.
Aria et al. (Sat,) studied this question.