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Inventory Management in a Consumer Electronics Closed-Loop Supply Chain

Author

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  • Andre P. Calmon

    (Technology and Operations Management, INSEAD, 77305 Fontainebleau Cedex, France)

  • Stephen C. Graves

    (A. P. Sloan School of Management, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139)

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.

Suggested Citation

  • Andre P. Calmon & Stephen C. Graves, 2017. "Inventory Management in a Consumer Electronics Closed-Loop Supply Chain," Manufacturing & Service Operations Management, INFORMS, vol. 19(4), pages 568-585, October.
    • Handle: RePEc:inm:ormsom:v:19:y:2017:i:4:p:568-585
    DOI: 10.1287/msom.2017.0622
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    References listed on IDEAS

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    3. Fu, Lingxian & Meng, Fanyong, 2020. "A human disease transmission inspired dynamic model for closed-loop supply chain management," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 134(C).
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    5. Omar Besbes & Adam N. Elmachtoub & Yunjie Sun, 2020. "Pricing Analytics for Rotable Spare Parts," Interfaces, INFORMS, vol. 50(5), pages 313-324, September.
    6. Cui, Hailong & Rajagopalan, Sampath & Ward, Amy R., 2020. "Predicting product return volume using machine learning methods," European Journal of Operational Research, Elsevier, vol. 281(3), pages 612-627.
    7. Cai, Ya-Jun & Choi, Tsan-Ming & Zhang, Ting, 2022. "Commercial used apparel collection operations in retail supply chains," European Journal of Operational Research, Elsevier, vol. 298(1), pages 169-181.
    8. Liu, Baolong & Papier, Felix, 2022. "Remanufacturing of multi-component systems with product substitution," European Journal of Operational Research, Elsevier, vol. 301(3), pages 896-911.
    9. Xiaodong Lv & Angfei Li & Shuhong Wang & Tao Zhang, 2023. "Building a demand-oriented optimal model for the recycling of used electronic products," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 25(7), pages 5949-5971, July.
    10. Lin, Yizhong & Leung, Janny M.Y. & Zhang, Lianmin & Gu, Jia-Wen, 2020. "Single-item repairable inventory system with stochastic new and warranty demands," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 142(C).
    11. Gökbayrak, Esra & Kayış, Enis, 2023. "Single item periodic review inventory control with sales dependent stochastic return flows," International Journal of Production Economics, Elsevier, vol. 255(C).
    12. Luttiely Santos Oliveira & Ricardo Luiz Machado, 2021. "Application of optimization methods in the closed-loop supply chain: a literature review," Journal of Combinatorial Optimization, Springer, vol. 41(2), pages 357-400, February.

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