Current Volume 9
Abstract
The global shift toward clean energy and digital technology has made rare earth minerals critical to modern supply chains. Despite their importance, existing ESG assessment tools remain inadequate: corporate sustainability reports systematically underreport negative incidents, and major ESG rating agencies exhibit an average inter-agency correlation of only 0.54. This paper develops and validates a data-driven analytical framework using machine learning (ML) and natural language processing (NLP) to automatically detect, classify, and score ESG risks in rare earth mineral supply chains. Applied to a corpus of approximately 840 documents from five major rare earth producers across Australia, the USA, and China (2015–2025), the fine-tuned BERT classifier achieves an F1-score of 0.84. The framework detects ESG controversies an average of 127 days earlier than rating agency updates, reveals a 23.5-point composite ESG risk score gap between Chinese and Western producers, and confirms financial materiality with −3.2% average abnormal returns following controversy disclosure. All four research hypotheses are statistically supported. The study contributes a validated, sector-specific framework for investors, procurement managers, and regulators seeking improved ESG transparency in critical mineral supply chains.
Keywords
Rare Earth Minerals; ESG Risk; Machine Learning; Natural Language Processing; Supply Chain Transparency; BERT; Critical Minerals; Sustainable Supply Chain.
Citations
IRE Journals:
Akash Kumar "A Data-Driven Approach to Mitigating ESG Risks in Rare Earth Mineral Supply Chains" Iconic Research And Engineering Journals Volume 9 Issue 10 2026 Page 4133-4137 https://doi.org/10.64388/IREV9I10-1716255
IEEE:
Akash Kumar
"A Data-Driven Approach to Mitigating ESG Risks in Rare Earth Mineral Supply Chains" Iconic Research And Engineering Journals, 9(10) https://doi.org/10.64388/IREV9I10-1716255
About IRE Journals
IRE Journals is an open access online journals established with an aim to publish high quality of research work in various diciplines. We have more than 6 years in publications. Over 2500+ papers already published.
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