Аннотация
The research analyzes perceptions of economically sustainable tourism development in three selected comparable countries (Serbia, Kazakhstan, and Hungary), focusing on benefits, costs, social support, cultural identification, and reciprocal benefits. The aim is to evaluate public support for tourism by examining perceived benefits and costs and the moderating effects of travel frequency and interactions with tourists. Forecasting analyses for 2025–2030 indicate potential growth in tourist arrivals, with Hungary showing the highest projections. Combining MGA and SEM analysis revealed that positive perceptions of benefits and cultural identification enhance tourism support while perceived costs reduce it. Key predictors influencing tourism support were identified using the Random Forest algorithm, and the XGBoost model improved prediction accuracy. K-means clustering and PCA highlighted relationships among the constructs. The findings underscore the importance of positive benefit perceptions and cultural identification in promoting tourism support, while negative cost perceptions diminish it. Understanding the roles of travel frequency and tourist interactions can inform sustainable tourism strategies that consider various benefits and costs.