Makale detayı · 2025
Global Sustainability Performance and Regional Disparities: A Machine Learning Approach Based on the 2025 SDG Index
Dergi
SustainabilityISSN 2071-1050
ISSN kaydı başka bir dergiye işaret ediyor; ad YÖKSİS kaydından.
- Yıl
- 2025
- Tür
- article
Veri kaynağı ayrımı
- YÖKSİS YÖKSİS makale kaydı
- YÖKSİS dergi adı Sustainability
- Katalog eşleşmesi (ISSN) Sustainability (Switzerland)
- OpenAlex OpenAlex zenginleştirmesi (özet, atıf, konular)
Özet
OpenAlex · İngilizce
Sustainability performance varies significantly across countries, yet global assessments overlook the underlying structural trends. This study bridges this gap using machine learning to uncover meaningful clustering in global sustainability outcomes based on the 2025 Sustainable Development Goals (SDG) Index. We applied K-Means clustering to group 166 countries into five standardized indicators: SDG score, spillover effects, regional score, population size, and recent progress. The five-cluster solution was confirmed by the Elbow and Silhouette procedures, with ANOVA and MANOVA tests subsequently indicating statistically significant cluster differences. For the validation and interpretation of the results, six supervised learning algorithms were employed. Random Forest, SVM, and ANN performed best in classification accuracy (97.7%) with perfect ROC-AUC scores (AUC = 1.0). Feature importance analysis showed that SDG and regional scores were most predictive of cluster membership, while population size was the least. This supervised–unsupervised hybrid approach offers a reproducible blueprint for cross-country benchmarking of sustainability. It also offers actionable insights for tailoring policy to groups of countries, whether high-income OECD nations, emerging markets, or resource-scarce countries. Our findings demonstrate that machine learning is a useful tool for revealing structural disparities in sustainability and informing cluster-specific policy interventions toward the 2030 Agenda.
Konular
Atıflar
OpenAlex cited_by_count. WoS veya Scopus atıf sayısı değildir; o kaynaklar için ayrı kolon yoktur.
26 atıf
OpenAlex cited_by_count (önbellek / veritabanı)
Yerel katalogda bu makaleye atıf yapan 13 yayın (OpenAlex referans eşleşmesi; tam dünya listesi değildir).
- Citation classification and key phrase extraction in legal texts using machine learning: an examination of the legal text classification dataset 2026
- Global cost of living patterns: machine learning insights and structural economic interpretation 2026
- Global cost of living patterns: machine learning insights and structural economic interpretation 2026
- Unveiling structural patterns of global budget transparency using advanced machine learning and explainable artificial intelligence frameworks 2026
- Beyond the Black Box: Nonlinear Regimes and Explainable AI in Global Innovation Systems 2026
- Multidimensional analysis of global economic freedom performances: structural findings and machine learning approaches 2026
- Beyond the Black Box: Nonlinear Regimes and Explainable AI in Global Innovation Systems 2026
- Global Gender Inequality Through Explainable AI: Machine Learning, Clustering, and SHAP Insights 2026
- Global Gender Inequality Through Explainable AI: Machine Learning, Clustering, and SHAP Insights 2026
- Analyzing Eco-Innovation Performance with Tree-Based Machine Learning and Shap Analysis 2026