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Optimal inventory replenishment strategy for deteriorating items in a demand-declining market with the retailer’s price manipulation

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  • Kung-Jeng Wang
  • Yu-Siang Lin

Abstract

Due to rapid technological innovation and global competitiveness, the demand of many fashion-typed products usually decline significantly over time. A retailer facing such a market can employ replenishment strategies to increase its profit. This study, from the perspective of the retailer in a two-echelon supply chain, develops the optimal replenishment strategy for products experiencing deterioration, continuous decrease in market demand and price changes. This model help determine the optimal product life for products. Numerical examples are systematically conducted to verify the performances of the proposed model. Copyright Springer Science+Business Media, LLC 2012

Suggested Citation

  • Kung-Jeng Wang & Yu-Siang Lin, 2012. "Optimal inventory replenishment strategy for deteriorating items in a demand-declining market with the retailer’s price manipulation," Annals of Operations Research, Springer, vol. 201(1), pages 475-494, December.
    • Handle: RePEc:spr:annopr:v:201:y:2012:i:1:p:475-494:10.1007/s10479-012-1213-3
    DOI: 10.1007/s10479-012-1213-3
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    2. Maihami, Reza & Govindan, Kannan & Fattahi, Mohammad, 2019. "The inventory and pricing decisions in a three-echelon supply chain of deteriorating items under probabilistic environment," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 131(C), pages 118-138.
    3. Maryam Ghoreishi & Gerhard-Wilhelm Weber & Abolfazl Mirzazadeh, 2015. "An inventory model for non-instantaneous deteriorating items with partial backlogging, permissible delay in payments, inflation- and selling price-dependent demand and customer returns," Annals of Operations Research, Springer, vol. 226(1), pages 221-238, March.
    4. Krishna Prasad & Bani Mukherjee, 2016. "Optimal inventory model under stock and time dependent demand for time varying deterioration rate with shortages," Annals of Operations Research, Springer, vol. 243(1), pages 323-334, August.
    5. Sadia Samar Ali & Haripriya Barman & Rajbir Kaur & Hana Tomaskova & Sankar Kumar Roy, 2021. "Multi-Product Multi Echelon Measurements of Perishable Supply Chain: Fuzzy Non-Linear Programming Approach," Mathematics, MDPI, vol. 9(17), pages 1-27, August.
    6. 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.
    7. Rini & Priyamvada & Chandra K. Jaggi, 2021. "Sustainable and flexible production system for a deteriorating item with quality consideration," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 12(5), pages 951-960, October.
    8. Yunlong Yu & Tiaojun Xiao & Zhangwei Feng, 2020. "Price and cold-chain service decisions versus integration in a fresh agri-product supply chain with competing retailers," Annals of Operations Research, Springer, vol. 287(1), pages 465-493, April.
    9. Konstantinos N. Konstantakis & Panagiotis T. Cheilas & Ioannis G. Melissaropoulos & Panos Xidonas & Panayotis G. Michaelides, 2023. "Supply chains and fake news: a novel input–output neural network approach for the US food sector," Annals of Operations Research, Springer, vol. 327(2), pages 779-794, August.

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