Sustainable development goals as drivers of tourism competitiveness: a machine learning perspective

This study investigates how progress on Sustainable Development Goals (SDGs) influences tourism competitiveness, reversing the conventional view of tourism as a driver of SDGs. Using data from the SDG Index and machine learning techniques, Random Forest, Bagging, Boosting, SHAP, and PDPs, the study evaluates how 17 SDGs predict international arrivals, tourism expenditures, and employment. Results highlight SDG 5 (Gender Equality), SDG 9 (Industry, Innovation, and Infrastructure), and SDG 16 (Peace, Justice, and Strong Institutions) as the most influential across outcomes. The findings contribute to theory by introducing a novel SDGs→tourism perspective and offer methodological innovation through interpretable machine learning. Practical implications suggest that targeted investments in gender equity, infrastructure, and institutional stability can enhance tourism performance and sustainability. This research provides actionable insights for aligning tourism policy with sustainable development priorities.