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The adoption of circular economy (CE) practices and artificial intelligence (AI) in the supply chain (SC) has become extremely significant in manufacturing organizations. The CE seeks to facilitate sustainable growth by managing the flow of materials and energy within closed-loop systems. The CE has resulted in the development of sustainable business models. AI capabilities transform work activities, data flows, and organizational processes. Therefore, the present study aims to develop a framework to improve circular supply chain (CSC) adoption in the automobile manufacturing sector by identifying and analyzing CE practices and AI-enabled digital strategies. The proposed framework was analyzed by employing a hybrid approach of Prioritized Weighted Average–Criteria Importance Through Intercriteria Correlation–Preference Ranking Organization Method for Enrichment Evaluations-II (PWA-CRITIC-PROMETHEE-II) under an Interval-Valued Fermatean Fuzzy (IVFF) environment. IVFF-CRITIC was employed to determine the CE practices’ weights, while IVFF-PROMETHEE-II was utilized to establish the relative index of AI-enabled digital strategies to enhance the CSC adoption. The key findings of the current study indicate that “AI-enabled infrastructure configuration for circular economy adoption in the supply chain”, “AI-integrated equipment to facilitate adaptability and mass personalization”, and “Robotics and AI-driven manufacturing and material reclamation” are the most significant AI-based digital strategies that support CE practices to enhance the adoption of a CSC and encourage case example manufacturing organizations to align their operations with AI and CE. Moreover, the outcomes of the study will deliver a comprehensive evaluation of CE practices and AI-enabled digital strategies for SC managers, based on the relative indexing obtained through the implementation of the hybrid approach. Full article

The Fermatean fuzzy set, in contrast to other generalizations of fuzzy sets like PFS and IFS, has a wide range of acceptance for both MF and NMF. In light of this, the Fermatean fuzzy set performs as an efficient, flexible, and comprehensive representation in situations that lack certainty. Here, the weaker forms of Fermatean fuzzy sets are introduced, and their traits are analyzed. Decomposition and continuity of the Fermatean fuzzy $\alpha$-open set are also accustomed. With the goal of safeguarding our green environment, hiring the best supplier is of the utmost significance in the construction industry. Using outranking techniques, Visual PROMETHEE Academic Edition 1.4 is a live multi-criteria decision aid software program. It runs virtual analysis through GAIA and applies selected criteria to contrast parameters. It also saves them for possible export and editing. In this article, the PROMETHEE II method is applied for Fermatean fuzzy numbers with $FF(\alpha ,\beta )$-level for selecting the optimal green supplier for a construction company. Because of its ability to handle vagueness, the FF PROMETHEE II method emerges as a valuable tool in Multi-criteria decision making. Furthermore, this study assesses the efficacy of the proposed technique by comparing its results with those obtained through other established methods. Full article