<p>In today's highly competitive business environment, businesses and industries are increasingly focused on mitigating carbon emissions and waste, alongside economic goals. This heightened emphasis underscores the importance of green development, aiming to achieve social, economic, and environmental sustainability. Within this context, a novel multi-echelon green supply chain inventory model for deteriorating items is developed by incorporating green technology investment under a carbon tax policy. The proposed framework consists of multiple suppliers, a single producer, and multiple buyers, and operates under selling price- and green-sensitive demand. Preservation technologies are adopted to control the deterioration rate, and the effects of inflation are explicitly considered. To address uncertainty inherent in real-world supply chains, selected parameters are represented using triangular fuzzy numbers. The objective of the model is to maximize total profit while simultaneously reducing carbon emissions. Numerical experiments are conducted in both crisp and fuzzy environments, and the concavity of the total profit function is analytically established. The numerical results indicate that, in the crisp environment, the optimal green investment level is $0.7563 per unit per month, yielding a total profit of $48,414.6. In contrast, under the fuzzy environment, the optimal green investment increases to $0.8941 per unit per month, resulting in a higher total profit of $76,919.7, which corresponds to an improvement of approximately 58.9% over the crisp case. Notably, this improvement is achieved without any modification to the production cycle time or infrastructure. Furthermore, comparative analysis and sensitivity analysis confirm the robustness of the proposed model. The findings highlight that the integration of fuzzy decision-making, preservation techniques, and green investments significantly enhances economic performance while supporting environmental and sustainable development goals.</p>