Two-step cluster analysis for energy performance indicators comparison

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.