Abstract

AbstractAcademics and practitioners have shown a growing interest in automobile reverse supply chain (RSC) management as a result of the rise of circular economy and the development of Industry 4.0. Accurate quantity prediction enhances the efficiency of all decision levels in automobile RSC, not only the recovery of end-of-life vehicles (ELVs). Therefore, a comprehensive state-of-the-art review, evaluating ELVs quantity forecasting methodologies and summarizing the main variables influencing forecasting outcomes, is conducted to throw shed light on future research directions.

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