Multi-Criteria Ordinal Hierarchical Classification to Improve Energy Investment Decisions

Transitioning towards sustainable energy needs decision models able to integrate economic, environmental, and technological factors in conditions of uncertainty. This paper introduces an innovative multicriteria ordinal classification approach based on the so-called HI-INTERCLASS-nB method to support strategic investment decisions in the energy sector. The approach can consider evaluation criteria organized in a hierarchical structure, and capture interactions among financial, environmental, and operational indicators. Unlike traditional approaches, the proposal allows the use of both precise and interval-based data, which improves robustness when the information is incomplete or imprecise. A computational experiment was conducted using data from energy-producing and energy-intensive companies, which are listed in major global markets. The results demonstrate that the proposed approach can effectively determine high-performance investment alternatives, providing stable and interpretable classifications across multiple scenarios. The results also confirm that HI-INTERCLASS-nB can be a valuable decision-support tool for policymakers and investors to promote efficient and sustainable energy strategies.