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Dynamic pricing of remanufacturable products under demand substitution: a product life cycle model

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  • Mustafa Akan
  • Barış Ata
  • R. Savaşkan-Ebert

Abstract

We consider a manufacturer who sells both the new and remanufactured versions of a product over its life cycle. The manufacturer’s profit depends crucially on her ability to synchronize product returns with the sales of the remanufactured product. This gives rise to a challenging dynamic optimization problem where the size of both the market and the user pool are dynamic and their current values depend on the entire history. We provide an analytical characterization of the manufacturer’s optimal pricing, production, and inventory policies which lead to a practical threshold policy with a small optimality gap. In addition, our analysis offers a number of interesting insights. First, the timing of remanufacturing activity and its co-occurrence with new product manufacturing critically depends on remanufacturing cost benefits, attractiveness of the remanufactured product and product return rate. Second, there is a small upward jump in the price of the new product when remanufacturing is introduced. Third, the manufacturer keeps the new product longer on the market as the cost of remanufacturing decreases. Fourth, partially satisfying demand for the remanufactured item is never optimal, i.e., it is satisfied either fully or not at all. Finally, user pool and inventory of returned products are substitutes in ensuring the supply for future remanufacturing. Copyright Springer Science+Business Media New York 2013

Suggested Citation

  • Mustafa Akan & Barış Ata & R. Savaşkan-Ebert, 2013. "Dynamic pricing of remanufacturable products under demand substitution: a product life cycle model," Annals of Operations Research, Springer, vol. 211(1), pages 1-25, December.
  • Handle: RePEc:spr:annopr:v:211:y:2013:i:1:p:1-25:10.1007/s10479-013-1409-1
    DOI: 10.1007/s10479-013-1409-1
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    References listed on IDEAS

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    2. Cave, Joshua & Chaudhuri, Kausik & Kumbhakar, Subal C., 2023. "Dynamic firm performance and estimator choice: A comparison of dynamic panel data estimators," European Journal of Operational Research, Elsevier, vol. 307(1), pages 447-467.
    3. Bayrak, Busra & Guray, Busra & Uzunlar, Nilsu & Nadar, Emre, 2024. "Diffusion control in closed-loop supply chains: Successive product generations," International Journal of Production Economics, Elsevier, vol. 268(C).
    4. Guowei Liu & Jianxiong Zhang & Wansheng Tang, 2015. "Joint dynamic pricing and investment strategy for perishable foods with price-quality dependent demand," Annals of Operations Research, Springer, vol. 226(1), pages 397-416, March.
    5. Xin Yan & Xiaohua Han, 2022. "Optimal pricing and remanufacturing entry strategies of manufacturers in the presence of online reviews," Annals of Operations Research, Springer, vol. 316(1), pages 59-92, September.
    6. Shin, Hojung & Park, Soohoon & Lee, Euncheol & Benton, W.C., 2015. "A classification of the literature on the planning of substitutable products," European Journal of Operational Research, Elsevier, vol. 246(3), pages 686-699.
    7. Xiaohua Han & Ying Shen & Yiwen Bian, 2020. "Optimal recovery strategy of manufacturers: Remanufacturing products or recycling materials?," Annals of Operations Research, Springer, vol. 290(1), pages 463-489, July.
    8. Liangchuan Zhou & Surendra M. Gupta, 2019. "A Pricing and Acquisition Strategy for New and Remanufactured High-Technology Products," Logistics, MDPI, vol. 3(1), pages 1-26, February.

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