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Inventory Management in a Consumer Electronics Closed-Loop Supply Chain

Author(s)
Calmon, Andre P.; Graves, Stephen C
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Creative Commons Attribution-Noncommercial-Share Alike http://creativecommons.org/licenses/by-nc-sa/4.0/
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Abstract
The goal of this paper is to describe, model, and optimize inventory in a reverse logistics system that supports the warranty returns and replacements for a consumer electronic device. The context and motivation for this work stem from a collaboration with an industrial partner, a Fortune 100 company that sells consumer electronics. The reverse logistics system is a closed-loop supply chain: failed devices are returned for repair and refurbishing; this inventory is then used to serve warranty claims or sold through a side sales channel. Managing inventory in this system is challenging because of the short life cycle of these devices and the rapidly declining value for the inventory. We examine an inventory model that captures these dynamics. We characterize the structure of the optimal policy for this problem for stochastic demand and introduce an algorithm to calculate optimal sell-down levels. We also provide a closed-form policy for the deterministic version of the problem, and we use this policy as a certainty-equivalent approximation to the stochastic optimal policy. Finally, using numerical experiments, we analyze the sensitivity of this system to changes in various parameters, and we also evaluate the performance of the certainty-equivalent approximation using data from our industrial partner. Keywords: inventory management; closed-loop supply chains; reverse logistics; sustainability
Date issued
2017-04
URI
https://hdl.handle.net/1721.1/122357
Department
Sloan School of Management
Journal
Manufacturing & Service Operations Management
Publisher
Institute for Operations Research and the Management Sciences (INFORMS)
Citation
Calmon, Andre P. and Stephen C. Graves. "Institute for Operations Research and the Management Sciences (INFORMS)." Manufacturing & Service Operations Management (October 2017): 509-712 © 2017 INFORMS
Version: Author's final manuscript
ISSN
1523-4614
1526-5498

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