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Refurbishment or quality recovery: joint quality and pricing decisions for new product development

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  • Zelin Zhang
  • Jianghua Wu
  • Feiqiong Wei

Abstract

Refurbishment and quality recovery, as two important strategies of reverse logistics, have been widely used for consumer durables, especially consumer electronics. This trend is driven by manufacturers’ profit-seeking behaviours and the increasing environmental concerns of society. This study investigates and compares the optimal emergence of these two strategies when product quality is endogenous. Model analyses provide several notable insights. First, we find that the refurbishment strategy dominates the quality recovery strategy when the fraction of the recoverable quality-inducing components in the defective product is low enough. Moreover, when the refurbishment strategy emerges as the optimum, the quality and price of the new product as well as the total realised sales of both new and refurbished products are consistently higher than those with the quality recovery strategy. In addition, when either the refurbishment or quality recovery strategy emerges as the optimum, the overall consumer surplus is also enhanced. Finally, in the model generalisation, we show that a synthetic strategy with which some of the returned defective products are refurbished and others are remanufactured through quality recovery can certainly increase the manufacturers’ profit compared to either one of them when the fraction of the recoverable quality-inducing components in the defective product is moderate.

Suggested Citation

  • Zelin Zhang & Jianghua Wu & Feiqiong Wei, 2019. "Refurbishment or quality recovery: joint quality and pricing decisions for new product development," International Journal of Production Research, Taylor & Francis Journals, vol. 57(8), pages 2327-2343, April.
  • Handle: RePEc:taf:tprsxx:v:57:y:2019:i:8:p:2327-2343
    DOI: 10.1080/00207543.2018.1516904
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    Cited by:

    1. Hsieh, Chung-Chi & Lathifah, Artya, 2022. "Ordering and waste reuse decisions in a make-to-order system under demand uncertainty," European Journal of Operational Research, Elsevier, vol. 303(3), pages 1290-1303.
    2. K. Jeganathan & S. Selvakumar & S. Saravanan & N. Anbazhagan & S. Amutha & Woong Cho & Gyanendra Prasad Joshi & Joohan Ryoo, 2022. "Performance of Stochastic Inventory System with a Fresh Item, Returned Item, Refurbished Item, and Multi-Class Customers," Mathematics, MDPI, vol. 10(7), pages 1-37, April.
    3. Zhixin Chen & Shijian Hong & Xiang Ji & Ruixia Shi & Jie Wu, 2022. "Refurbished products and supply chain incentives," Annals of Operations Research, Springer, vol. 310(1), pages 27-47, March.

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