Cardiff University | Prifysgol Caerdydd ORCA
Online Research @ Cardiff 
WelshClear Cookie - decide language by browser settings

A unified theory of the dynamics of closed-loop supply chains

Hosoda, Takamichi and Disney, Stephen M. ORCID: https://orcid.org/0000-0003-2505-9271 2018. A unified theory of the dynamics of closed-loop supply chains. European Journal of Operational Research 269 (1) , pp. 313-326. 10.1016/j.ejor.2017.07.020

[thumbnail of A unified theory of the dynamics of closed-loop supply chains pre-print.pdf]
Preview
PDF - Accepted Post-Print Version
Available under License Creative Commons Attribution Non-commercial No Derivatives.

Download (385kB) | Preview

Abstract

We investigate the dynamics of a closed-loop supply chain with first-order auto-regressive (AR(1)) demand and return processes. We assume these two processes are cross-correlated. The remanufacturing process is subject to a random triage yield. Remanufactured products are considered as-goodas- new and used to partially satisfy market demand; newly manufactured products make up the remainder. We derive the optimal linear policy in our closed-loop supply chain setting to minimise the manufacturer’s inventory costs. We show that the lead-time paradox can emerge in many cases. In particular, the auto- and cross-correlation parameters and variances of the error terms in the demand and the returns, as well as the remanufacturing lead time, all influence the existence of the lead-time paradox. Finally, we propose managerial recommendations for manufacturers.

Item Type: Article
Date Type: Publication
Status: Published
Schools: Business (Including Economics)
Uncontrolled Keywords: Supply Chain Management, Closed-loop Supply Chain, Vector Auto-Regressive Process, Order-Up-To Policy, Random Yield
Additional Information: Released with a Creative Commons Attribution Non-Commercial No Derivatives License (CC BY-NC-ND)
Publisher: Elsevier
ISSN: 0377-2217
Funders: JSPS KAKENHI Grant Number 25380475
Date of First Compliant Deposit: 2 July 2017
Date of Acceptance: 2 July 2017
Last Modified: 16 Nov 2023 18:05
URI: https://orca.cardiff.ac.uk/id/eprint/101971

Citation Data

Cited 31 times in Scopus. View in Scopus. Powered By Scopus® Data

Actions (repository staff only)

Edit Item Edit Item

Downloads

Downloads per month over past year

View more statistics