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Inventory control with product returns: The impact of imperfect information

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  • de Brito, Marisa P.
  • van der Laan, Erwin A.

Abstract

Product returns are characterized by considerable uncertainty on time and quantity. In the literature on inventory management for product return environments best forecasts of future returns are associated with methods that use the most information regarding product return history. In practice, however, data is often scarce and unreliable, while forecasts based on historical data, reliable or not, are never perfect. In this paper we therefore investigate the impact of imperfect information with respect to the return process on inventory management performance. We show that in the case of imperfect information the most informed method does not necessarily lead to best performance. The results have relevant implications regarding investments in product return information systems.

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  • de Brito, Marisa P. & van der Laan, Erwin A., 2009. "Inventory control with product returns: The impact of imperfect information," European Journal of Operational Research, Elsevier, vol. 194(1), pages 85-101, April.
    • Handle: RePEc:eee:ejores:v:194:y:2009:i:1:p:85-101
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    Cited by:

    1. Nowak, Thomas & Hofer, Vera, 2014. "On stabilizing volatile product returns," European Journal of Operational Research, Elsevier, vol. 234(3), pages 701-708.
    2. Wee, Hui-Ming & Lee, Ming-Chang & Yu, Jonas C.P. & Edward Wang, C., 2011. "Optimal replenishment policy for a deteriorating green product: Life cycle costing analysis," International Journal of Production Economics, Elsevier, vol. 133(2), pages 603-611, October.
    3. Yoo, Seung Ho, 2014. "Product quality and return policy in a supply chain under risk aversion of a supplier," International Journal of Production Economics, Elsevier, vol. 154(C), pages 146-155.
    4. Zhou, Li & Xie, Jiaping & Gu, Xiaoyu & Lin, Yong & Ieromonachou, Petros & Zhang, Xiaole, 2016. "Forecasting return of used products for remanufacturing using Graphical Evaluation and Review Technique (GERT)," International Journal of Production Economics, Elsevier, vol. 181(PB), pages 315-324.
    5. Carrasco-Gallego, R. & Ponce-Cueto, E. & Dekker, R., 2009. "A framework for closed-loop supply chains of reusable articles," Econometric Institute Research Papers EI 2009-21, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    6. Petropoulos, Fotios & Apiletti, Daniele & Assimakopoulos, Vassilios & Babai, Mohamed Zied & Barrow, Devon K. & Ben Taieb, Souhaib & Bergmeir, Christoph & Bessa, Ricardo J. & Bijak, Jakub & Boylan, Joh, 2022. "Forecasting: theory and practice," International Journal of Forecasting, Elsevier, vol. 38(3), pages 705-871.
      • Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.
    7. Govindan, Kannan & Soleimani, Hamed & Kannan, Devika, 2015. "Reverse logistics and closed-loop supply chain: A comprehensive review to explore the future," European Journal of Operational Research, Elsevier, vol. 240(3), pages 603-626.
    8. Tsiliyannis, Christos Aristeides, 2018. "Markov chain modeling and forecasting of product returns in remanufacturing based on stock mean-age," European Journal of Operational Research, Elsevier, vol. 271(2), pages 474-489.
    9. Flapper, S.D.P. & Gayon, J.P. & Vercraene, S., 2012. "Control of a production–inventory system with returns under imperfect advance return information," European Journal of Operational Research, Elsevier, vol. 218(2), pages 392-400.
    10. Tianji Yang & Chao Fu & Xinbao Liu & Jun Pei & Lin Liu & Panos M. Pardalos, 2018. "Closed-loop supply chain inventory management with recovery information of reusable containers," Journal of Combinatorial Optimization, Springer, vol. 35(1), pages 266-292, January.
    11. Christos I. Papanagnou, 2022. "Measuring and eliminating the bullwhip in closed loop supply chains using control theory and Internet of Things," Annals of Operations Research, Springer, vol. 310(1), pages 153-170, March.
    12. Mabel C. Chou & Chee-Khian Sim & Xue-Ming Yuan, 2020. "Policies for inventory models with product returns forecast from past demands and past sales," Annals of Operations Research, Springer, vol. 288(1), pages 137-180, May.
    13. Hosoda, Takamichi & Disney, Stephen M. & Gavirneni, Srinagesh, 2015. "The impact of information sharing, random yield, correlation, and lead times in closed loop supply chains," European Journal of Operational Research, Elsevier, vol. 246(3), pages 827-836.
    14. Kim, Taebok & Glock, Christoph H. & Kwon, Yongjang, 2014. "A closed-loop supply chain for deteriorating products under stochastic container return times," Omega, Elsevier, vol. 43(C), pages 30-40.
    15. Ilkka Ritola & Harold Krikke & Marjolein C.J. Caniëls, 2020. "Learning from Returned Products in a Closed Loop Supply Chain: A Systematic Literature Review," Logistics, MDPI, vol. 4(2), pages 1-13, April.
    16. Tripathy, Satchidananda & Kumar, Akhilesh & Mahanty, Biswajit, 2023. "Short-lived product returns forecasting when customers are unwilling to return the product: A grey-graphical evaluation and review technique," Technological Forecasting and Social Change, Elsevier, vol. 195(C).
    17. 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.
    18. Wen, Xin & Choi, Tsan-Ming & Chung, Sai-Ho, 2019. "Fashion retail supply chain management: A review of operational models," International Journal of Production Economics, Elsevier, vol. 207(C), pages 34-55.
    19. Xing Hu & Zhixi Wan & Nagesh N. Murthy, 2019. "Dynamic Pricing of Limited Inventories with Product Returns," Manufacturing & Service Operations Management, INFORMS, vol. 21(3), pages 501-518, July.
    20. Juan Pedro Sepúlveda-Rojas & Rodrigo Ternero, 2020. "Analysis of the Value of Information and Coordination in a Dyadic Closed Loop Supply Chain," Sustainability, MDPI, vol. 12(20), pages 1-18, October.
    21. Pauline Keh & Florence Rodhain & Régis Meissonier & Virginie Llorca, 2012. "Financial performance, environmental compliance, and social outcomes: The three challenges of reverse logistics," Post-Print hal-01965596, HAL.
    22. Josip Marić & Marco Opazo-Basáez, 2019. "Green Servitization for Flexible and Sustainable Supply Chain Operations: A Review of Reverse Logistics Services in Manufacturing," Global Journal of Flexible Systems Management, Springer;Global Institute of Flexible Systems Management, vol. 20(1), pages 65-80, December.
    23. Duong, Quang Huy & Zhou, Li & Meng, Meng & Nguyen, Truong Van & Ieromonachou, Petros & Nguyen, Duy Tiep, 2022. "Understanding product returns: A systematic literature review using machine learning and bibliometric analysis," International Journal of Production Economics, Elsevier, vol. 243(C).

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