An Integrative Model for Remanufacturing Operations through Two-Stage Data Envelopment Analysis: Insights using Game Theory Perspective

Manufacturing operations that emphasize environmental responsibility, product quality and end-of-life (EOL) management are increasingly adopted by firms. These steps are necessary due to increasing environmental legislation and a growing consumer demand for sustainable products. An advantageous approach to effectively addressing returned items within this framework is remanufacturing. The findings of this research explore the dynamic processes involved in the remanufacturing stages, namely the collection, sorting, and testing phase, as well as the development phase, which remanufactures the product, and how they affect the entire supply chain (SC) performance. The current research offers a unified strategy to thoroughly evaluate model responses across a wide range of variables by analysing the impact of key variables within these phases and employing various distribution functions to model their behaviour. A two-stage Data Envelopment Analysis (DEA), an efficient analytical method in Multi-Criteria Decision Making (MCDM), is employed to evaluate the efficiency of the developed models. Research findings indicate that the initial phases of collection, sorting and testing are more efficient than the development phase. Furthermore, the findings show that the cooperative method yields more efficient outcomes than the leader-follower approach in the non-cooperative setting.