Abstract
This study proposes a framework for tracing carbon footprints and allocating emission reduction responsibilities in green supply chains by integrating Product Lifecycle Management (PLM) with a Discrete Hopfield Neural Network-based Analytic Hierarchy Process (DHNN-AHP). By constructing an integrated “trace-evaluate-allocate” model, it achieves systematic tracking of carbon footprints across the entire chain of raw material acquisition, production, distribution, usage, and recycling, while introducing DHNN-AHP for dynamic low-carbon performance evaluation of suppliers. Based on this, a responsibility allocation mechanism is proposed, grounded in carbon contributions and performance results, to promote overall carbon efficiency coordination in the supply chain. A case study using cathode material suppliers as an example demonstrates that this method enhances the accuracy of supply chain carbon management while balancing environmental and economic benefits, providing methodological support for the governance and policy coordination of green supply chains under carbon neutrality goals.