An optimization framework for sustainable closed-loop supply chains with green investment and recovery policy

Sustainability in closed-loop supply chains (CLSCs) is becoming a significant focus due to increasing environmental pressures and carbon regulations. While numerous studies have examined aspects such as carbon emissions, green technology, and the quality of used products, gaps remain in integrating these elements, particularly concerning the influence of collection quality on emissions, various recovery policies, and contract-based coordination mechanisms for sharing green technology investments. This study aims to develop a comprehensive supply chain model by integrating these factors through three main mechanisms: centralized coordination, decentralized, and green technology revenue investment sharing (GRIS) contracts. The model employs a mathematical formulation that considers green technology investment, collection rate, the quality of used products, and carbon emissions. Simulations were conducted with sensitivity analysis to evaluate the impact of parameters such as carbon tax, selling price sensitivity coefficient, green technology investment, and collection effort on system performance. Results indicate that the centralized coordination model excels in maximizing total profit and operational stability when compared to the decentralized model. However, it is more sensitive to changes in parameters. GRIS contracts offer flexibility in profit redistribution between producers and retailers without compromising the system efficiency. The findings also indicate that investments in green technology and collection efforts significantly contribute to enhanced collection quality and reduced carbon emissions, with more pronounced effects in the centralized model. This research offers a comprehensive approach to tackling sustainability challenges in CLSC, providing practical insights for industry stakeholders and policymakers in developing strategies that promote both economic and environmental sustainability.