Digitalization-Oriented Circular Supplier Selection for Recycled Materials: A Probabilistic Uncertain Linguistic T-Spherical Fuzzy CASPAS Approach

Le résumé fourni par la source

Against the backdrop of global carbon-neutrality targets, the circular utilization of end-of-life power batteries has become a critical pathway for securing resources and reducing environmental risks. Digital technologies are increasingly reshaping circular supply-chain management. High-performing circular suppliers are essential to the efficient operation of digital circular supply chains. However, existing research on circular supplier selection (CSS) still faces three gaps: a theoretical gap in which digitalization is neglected in circular supply chains, an information-representation gap causing evaluation distortion, and an aggregation-mechanism gap arising from the inadequate treatment of interdependencies among decision variables. To address these issues, this study constructs a decision model based on probabilistic uncertain linguistic T-spherical fuzzy sets (PULTSFSs) and Choquet-integral-based aggregated sum product assessment (CASPAS). First, this study develops a multilevel evaluation system that closely integrates digital management and control capabilities. By combining PULTSFSs with the Choquet integral (CI), a CASPAS group decision-making model that captures interaction effects among decision elements is proposed. The strategic procurement of nickel-cobalt-manganese 811 (NCM811) cathode-material precursors by CATL is used as a case study. The results show that this indicator system is better suited to digital circular supply-chain management scenarios than traditional frameworks. In the CATL case, the recycled-material supplier h3 achieves a comprehensive score of 0.660, 5.60% higher than that of the second-ranked alternative. By capturing interdependencies among evaluation elements, the proposed model exhibits stronger ranking discriminability and robustness than traditional independent-attribute methods, thereby providing a practical foundation and an efficient tool for digital supply-chain management in the power-battery recycling industry.

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