Exploring the Role of Nature-based Leisure in Promoting Sustainable Tourism
DOI:
https://doi.org/10.33422/ictmh.v3i1.1977Keywords:
Clustering, Machine Learning, Nature-Based Leisure, Sustainability, Tourism IntensityAbstract
This study examines the relationship between environmental sustainability and tourism development across 173 countries from 2000 to 2018, focusing on nature-based leisure. Using data from the World Bank, the UN SDG framework, and the World Tourism Organization, a panel dataset is constructed. A composite Nature Sustainability Index (NSI) is developed using renewable energy, rural population, CO₂ damage, and forest depletion. The analysis combines exploratory data analysis, regression, clustering, and machine learning methods. Results show a negative global relationship between sustainability and tourism intensity, reflecting differences between high-income, high-tourism countries and lower-income, nature-rich economies. However, the relationship becomes positive in upper-middle-income countries, indicating a development threshold. Machine learning models outperform linear approaches, emphasizing nonlinear dynamics and identifying GDP per capita and resource dependence as key predictors. Overall, the findings highlight that sustainability can become a competitive advantage when supported by adequate infrastructure and development.
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Copyright (c) 2026 Georgios Vasileiadis

This work is licensed under a Creative Commons Attribution 4.0 International License.



