A Comparative Study of Cross-Border E-Commerce Green Supply Chains Based on Enhanced G-SCOR: JD.com vs. Amazon

Based on existing literature on green supply chains in cross-border e-commerce and relevant data results, this study constructs an improved G-SCOR model that integrates cross-border indicators (such as carbon tariff sensitivity). To scientifically quantify greenness, the research first combines the Analytic Hierarchy Process (AHP) and entropy weight method to determine the weight of indicators, and then establishes a fuzzy comprehensive evaluation model. It applies and validates the model through practical examples from JD.com and Amazon. The results show that Amazon achieves a 90% carbon reduction primarily through sea transportation (accounting for 65%), with AI optimization reducing mileage by 19%, but the packaging recycling rate is only 52%; JD.com's policy-driven recycling rate reaches 74%, and blockchain reduces dispute-related returns by 30%. The model scoring reveals a dual-path differentiation: policy-driven (JD.com) excels in recycling and planning, while market-driven (Amazon) excels in logistics efficiency. The conclusion calls for the establishment of standardized carbon accounting protocols and international EPR mutual recognition to promote cross-border green collaboration.