Work

Evaluation of the Three Largest Brazilian Steel Companies’ Sustainable Performance Using VIKOR and Gaussian AHP

Year: 2025

Type: article

Abstract: In 2023, Brazil’s steel production accounted for 1.7% of global steel output, ranking the country as the 9th largest producer worldwide. The country accounted for 54.84% of the regional production in Latin America. This economic situation presently coexists with environmental and social challenges inherent to the steel industry, stemming from the repercussions of its activities on the environment and human health and well-being. Thus, while the Brazilian steel sector is crucial for economic progress, an examination of the sustainable performance of these entities uncovers challenges and underscores the necessity of reconciling economic, environmental, and social factors to secure a sustainable future. Consequently, a classification system for the sustainable performance of Brazil’s three largest steel companies, centered on the Triple Bottom Line and grounded in criteria associated with corporate reports compliant with the Global Reporting Initiative (GRI) framework, is essential to elucidate the conduct of these companies. Consequently, utilizing 11 criteria (four economic, four social, and three environmental) derived from documentary research conducted between 2019 and 2021, this study formulates a framework for classifying the principal steel companies through the ViseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR) method, integrated with the Gaussian Analytical Hierarchy Process (Gaussian AHP) for weight assignment, thereby eliminating the need for specialists and mitigating inherent subjectivity. The method’s application revealed a change in the classification of steel mills according to the criteria established by the research. The current study enables interested parties to assess organizational behavior and identifies areas for improvement to enhance sustainable performance rankings.

Source: International Journal of Mathematical Engineering and Management Sciences

DOI: 10.33889/ijmems.2025.10.6.080

Authors: Carlos Alberto Soares Cunha, Luís Alberto Duncan Rangel, Julio Vieira Neto

Institution: Universidade Federal Fluminense

Language: English

Topic: Multi-Criteria Decision Making

Subfield: Management Science and Operations Research

Field: Decision Sciences

Domain: Social Sciences

SDGs: Responsible consumption and production, Industry, innovation and infrastructure

Open Access status: gold

Estimated APC paid: $500