TY - JOUR
TI - Two-step cluster analysis for energy performance indicators comparison
AU - Rađenović Žarko J
AU - Rajić Milena N
JN - Thermal Science
PY - 2025
VL - 29
IS - 5
SP - 3453
EP - 3464
PT - Article
AB - Assessing energy performance indicators is important for understanding EU countries’ progress toward achieving sustainability and climate goals, including reducing greenhouse gas emissions and increasing the share of renewable energy. This paper employs two-step cluster analysis using IBM SPSS 26.0 to classify EU member states based on six key energy indicators. The optimal number of clusters was determined using Schwarz’s Bayesian information criterion, ensuring statistical robustness. Four distinct clusters were identified, revealing varying strengths and weaknesses. These insights provide important guidance for policymakers, enabling the development of targeted strategies for improving energy efficiency and sustainability across the EU.