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VOL. 7, ISSUE 2 (2025)
ESG driven decision making with predictive analytics – A scientometric study
Authors
Mariya Fatima, Farhat Naaz, Mohammed Junaid Ahmed, Nomaan Abdul Majeed, Mohd Arif Hussain
Abstract
We examine the integration of predictive
analytics into Environmental, Social, and Governance (ESG)-driven
decision-making through this systematic literature review, with a particular
focus on the manufacturing sector amid escalating regulatory demands such as
the EU Deforestation Regulation (EUDR) and Corporate Sustainability Reporting
Directive (CSRD). We draw on a PRISMA-guided synthesis of 10 core studies from
2021–2025, complemented by bibliometric analysis of 258 records from
Dimensions.ai, to trace ESG's evolution from socially responsible investing
origins to a strategic imperative. We highlight predictive tools' role in
forecasting risks, enhancing transparency, and optimizing supply chains. Our
key findings reveal exponential publication growth (166 in 2025 alone),
dominance of management disciplines (79% of outputs), and influential themes
such as AI-enhanced ESG scoring (92% accuracy) and Industry 4.0 moderation. We
underscore regional disparities in adoption (93% in Europe vs. 79% in North America)
and analytics' potential for equitable implementation, although gaps in SME
accessibility and metric standardization persist. For manufacturing, we
identify implications including 15–30% improvements in compliance and cost
reductions, positioning predictive analytics as a bridge between ethical
sustainability and competitive advantage. This study offers practitioners and
scholars a roadmap, as we advocate hybrid AI-human models to advance global ESG
resilience.
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Pages:90-98
How to cite this article:
Mariya Fatima, Farhat Naaz, Mohammed Junaid Ahmed, Nomaan Abdul Majeed, Mohd Arif Hussain "ESG driven decision making with predictive analytics – A scientometric study". International Journal of Environmental and Ecology Research, Vol 7, Issue 2, 2025, Pages 90-98
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