A Data-Validated Multi-Criteria Decision Framework for Ranking Sustainable Energy Pathways Toward Net-Zero Emissions

Abstract

Sustainable energy planning requires decision frameworks that capture interdependencies among criteria while ensuring empirical validation. A data-validated multi-criteria decision-making framework is developed by integrating the Decision-Making Trial and Evaluation Laboratory and the Multi-Criteria Optimization and Compromise Solution methods to rank sustainable energy options by their contribution to net-zero targets. Empirical validation is performed using cross-country energy indicators obtained from the Our World in Data Energy Dataset. The results show that energy efficiency has the highest priority, with compromise index values near 0.00–0.02, followed by renewable energy (0.18–0.20) and electrification (0.36–0.38), while carbon capture (0.69–0.71) and circular economy (0.98–1.00) exhibit lower performance. Policy feasibility (+1.53) and technological readiness (+0.84) are identified as dominant driving criteria, whereas economic feasibility (−0.92) and environmental impact (−0.45) are dependent factors. The strong agreement between expert-based and data-driven results confirms the robustness of the framework. Sensitivity analysis indicates stable rankings with only minor variations among intermediate strategies. The framework provides a reliable basis for prioritizing sustainable energy strategies under real-world conditions.