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The study examines an energy-intensive industry as it moves from traditional linear supply chains toward circular models. Its authors state that such a transition involves environmental, social and governance uncertainties that conventional operational research can overlook. The purpose was not to measure changes in emissions, recycling rates or industrial performance. Instead, it sought to identify and prioritize ESG risks relevant to implementing an aluminium circular supply chain, including considerations associated with international regulatory requirements such as the Carbon Border Adjustment Mechanism.

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To assemble the risk set, the team used a literature review and then finalized the identified issues with a PF-Delphi method. It subsequently assessed causal relationships among the risks through Pythagorean fuzzy DEMATEL and determined their relative importance using the Analytic Network Process. The authors describe the combined framework as a way to handle uncertainty in expert judgment while integrating information about relationships and relative significance. Its results are model-derived risk priorities rather than direct observations of outcomes in aluminium production facilities or supply chains.

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The highest-ranked issue, limited access to cleaner technology, received a weight of 0.1335. High demand for affordable renewable electricity followed closely at 0.1289. Both belong to the environmental category, which collectively took precedence over social risks, followed in turn by governance risks. The numerical weights indicate the relative importance assigned within the study’s framework; they are not universal thresholds, and the supplied findings do not establish how the ranking would change under different expert panels, risk sets or decision-making settings.

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By placing a literature-derived risk inventory, expert consensus, causal assessment and hierarchical weighting within one integrated approach, the study offers a structured way to examine ESG uncertainty in aluminium circularity. Its principal reported result is the ordering of the assessed risks: cleaner-technology access and affordable renewable-electricity demand emerge as the leading concerns, while environmental risks as a group outrank social and governance risks. The authors present the method as a quantitative tool for risk assessment under uncertainty and a possible analytical basis for policymakers seeking to identify the ESG constraints most relevant to the aluminium industry.

Subject of Research: Expert-based prioritization of ESG risks in aluminium circular supply chains using Pythagorean fuzzy DEMATEL and the Analytic Network Process.

Article Title: Environmental, social, and governance (ESG) risks assessment in implementing aluminium circular supply chain

Article References: Keshavarzi, Y., Shojaei, P., & Abbasi, A. (2026). Environmental, social, and governance (ESG) risks assessment in implementing aluminium circular supply chain. Discover Sustainability. https://doi.org/10.1007/s43621-026-04735-z

Image Credits: AI Generated

DOI: 10.1007/s43621-026-04735-z

Keywords: aluminium, circular supply chains, ESG risk, clean technology, renewable electricity, fuzzy decision analysis, Pythagorean fuzzy sets, DEMATEL, Analytic Network Process, industrial sustainability, Environmental, social