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Financial Innovation· 2026Q1

Scenario-based ESG scoring for sustainable financial investments using an advanced multi-facet fuzzy system

Wei Liu, Yedan Shen, Hasan Dınçer, Serhat Yüksel et al.

Short summary

A new hybrid model using information-gain dependency weighting, PCRO, and dynamic multi-facet fuzzy sets identifies social responsibility and ethical practices as the most impactful ESG criteria for sustainable financial investments.

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Key points

  • Developed a hybrid decision-making model combining information-gain dependency weighting, PCRO, and dynamic multi-facet fuzzy sets (DMFFSs).
  • Identified social responsibility and ethical practices as the most influential criteria in ESG scoring for sustainable investments.
  • Ranked sustainability-based loans and ESG-related fintech platforms as the most critical investment alternatives.
  • The model provides a flexible, AI-supported framework for decision-making under uncertainty in sustainable finance.

AI-generated from the title and abstract; the full text is not read.

Abstract

Sustainable financial investments are emerging as a multidimensional decision-making area that requires a holistic assessment of environmental, social, and governance (ESG) criteria. However, the literature demonstrates that the relative importance of each of these criteria on investment performance has not been systematically analyzed, creating a significant uncertainty problem in decision-making processes. While existing studies generally emphasize the importance of factors such as carbon impact, resource efficiency, social responsibility, and ethical practices separately, a holistic prioritization approach to determining which factors play the most decisive role in sustainable financial investment decisions remains limited. This deficiency makes it difficult for investors to determine the correct criteria weights and hinders the efficient use of financial resources. The primary objective of this study is to address this methodological gap and develop a new decision-making model that can identify the most critical factors affecting the performance of sustainable financial investments. The model developed for this purpose calculates criteria importance weights using an information-gain-based dependency-weighting procedure, ranks alternatives using the principal component ranking optimization (PCRO) technique, and manages uncertainty in a multidimensional manner using the dynamic multi-facet fuzzy sets (DMFFSs) approach. This hybrid structure not only produces more flexible and realistic results compared to classical fuzzy logic models but also allows for the amplification of expert opinions with AI support. The analysis results show that social responsibility and ethical practices are the most effective criteria in ESG scoring, while sustainability-based loans and ESG-related fintech platforms represent the most critical alternatives for sustainable financial investments. These findings demonstrate that social and ethical governance directly shape investment performance and that digital financial instruments have the potential to transform sustainable investments. By providing a unique analytical framework for evaluating sustainable financial investments, the study fills a gap in the literature regarding priority analysis and provides a methodological contribution to decision-making under uncertainty.

The authors' abstract, as published at the source. Financial Innovation, 2026 · DOI ↗

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Field: Building and Construction

Building and ConstructionEngineering