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Forecasting the Number of End-of-Life Vehicles: State of the Art Report

Published online by Cambridge University Press:  26 May 2022

H. Xia ,
J. Han  and
J. Milisavljevic-Syed
H. Xia*
Affiliation:
University of Liverpool, United Kingdom
J. Han
Affiliation:
University of Liverpool, United Kingdom
J. Milisavljevic-Syed
Affiliation:
University of Liverpool, United Kingdom
*
[email protected]

Abstract

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Academics 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.

Keywords

sustainabilitydesign reviewcircular economychange prediction
Type
Article
Information
Proceedings of the Design Society , Volume 2: DESIGN2022 , May 2022 , pp. 1169 - 1178
Creative Commons
Creative Common License - CCCreative Common License - BYCreative Common License - NCCreative Common License - ND
This is an Open Access article, distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives licence (http://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is unaltered and is properly cited. The written permission of Cambridge University Press must be obtained for commercial re-use or in order to create a derivative work.
Copyright
The Author(s), 2022.

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