A sorting-based multicriteria decision model for ESG screening of sovereign investment assets

https://doi.org/10.55214/jcrbef.v8i1.11936

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The rapid growth of sustainable finance has increased the need for transparent and robust decision-support tools for screening environmental, social, and governance (ESG) investment assets. Conventional ESG evaluation methods often rely on composite scores that obscure trade-offs among criteria and inadequately address data imprecision and heterogeneity. This paper proposes a hierarchical interval outranking approach for classifying sustainable finance assets into acceptability categories, rather than producing a full ranking. The method structures ESG criteria hierarchically and represents performance evaluations using intervals to explicitly account for uncertainty, variability, and incomplete information commonly observed in ESG datasets. An outranking-based sorting procedure is then applied to assign assets to predefined classes, such as non-acceptable, acceptable, and priority investments. The framework is demonstrated using publicly available ESG indicators for countries, interpreted as sovereign investment assets, illustrating its ability to deliver transparent, non-compensatory classifications while maintaining interpretability at each aggregation level. The results show that the approach supports consistent and explainable ESG screening decisions, offering a viable alternative to opaque scoring-based methods. The proposed model contributes to sustainable finance research by integrating hierarchical multicriteria decision analysis with interval-based uncertainty handling and provides practical value for portfolio managers and policymakers engaged in responsible investment decision-making.

How to Cite

Montelongo, J. A. G., Aguilera, A., Magallanes, F., Gaona, J. A. Álvarez, Flores, J. D. C., & Flores, A. (2026). A sorting-based multicriteria decision model for ESG screening of sovereign investment assets. Journal of Contemporary Research in Business, Economics and Finance, 8(1), 1–18. https://doi.org/10.55214/jcrbef.v8i1.11936

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2026-01-29

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