Litcius/Paper detail

A decision-support framework for evaluating AI-enabled ESG strategies in the context of sustainable manufacturing systems

Abeer Aljohani

2025Scientific Reports10 citationsDOIOpen Access PDF

Abstract

With the increasing global environmental and social challenges, it is more urgent than ever to implement effective strategies for sustainable development. Environmental, Social and Governance (ESG) criteria are also necessary requirements guiding organizations toward responsible and sustainable practices. However, the multi-dimensionality of the criteria and the uncertainty associated with judgment by an expert makes evaluation and choice of the best ESG-driven strategy a very complex task. The current paper introduces an innovative approach to the assessment of ESG strategies via Fuzzy based multi-criteria decision-making tools. Those selected shall be addressed particularly through the Fuzzy TOPSIS method, considering and ranking seven key strategies driven by ESG focus areas- AI-Powered Predictive Analytics, Renewable Energy Integration, Smart Waste Management Systems, Blockchain for Transparent Governance, AI-Enhanced Workforce and Community Development, Sustainable Supply Chain Optimization and Generative AI for Eco-Friendly Innovation. The results of this assessment indicate that the most popular ESG approach is renewable energy integration, which is in line with the industry's pivotal role in advancing energy transition and climate action. AI-Powered Predictive Analytics and Sustainable Supply Chain Optimization are closely related, emphasizing the strategic value of data intelligence as well as operational efficiency in improving sustainability practices. These results offer important novel insights about how AI-powered methods might guide environmentally friendly choices in intricate industrial settings. Our method provides a strong and transparent framework for assessing ESG strategies under sustainability by incorporating fuzzy logic into decision-making. The study adds to the rapidly expanding body of research on AI-driven sustainability evaluations, from which companies, policymakers and other stakeholders could gain insight how to enhance their ESG performance as well as advance sustainable development.

Topics & Concepts

Context (archaeology)Computer scienceDecision support systemProcess managementData scienceArtificial intelligenceBusinessBiologyPaleontologyDigital Transformation in IndustrySustainable Supply Chain ManagementFlexible and Reconfigurable Manufacturing Systems