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The Supply Chain Design for Perishable Food with Stochastic Demand

Author

Listed:
  • Shuai Yang

    (School of Economics and Management, Changshu Institute of Technology, Changshu 215500, China)

  • Yujie Xiao

    (Jiangsu Key Laboratory of Modern Logistics, School of Marketing and Logistics Management, Nanjing University of Finance and Economics, Nanjing 210023, China
    Business School, Nanjing University, Nanjing 210093, China)

  • Yong-Hong Kuo

    (Stanley Ho Big Data Decision Analytics Research Centre, the Chinese University of Hong Kong, Shatin, New Territories, Hong Kong 999077, China)

Abstract

It has been a challenging task to manage perishable food supply chains because of the perishable product’s short lifetime, the possible spoilage of the product due to its deterioration nature, and the retail demand uncertainty. All of these factors can lead to a significant amount of shortage of food items and a substantial retail loss. The recent development of tracing and tracking technologies, which facilitate effective monitoring of the inventory level and product quality continuously, can greatly improve the performance of food supply chain and reduce spoilage waste. Motivated by this recent technological advancement, our research aims to investigate the joint decision of pricing strategy, shelf space allocation, and replenishment policy in a single-item food supply chain setting, where our goal is to maximize the retailer’s total expected profit subject to stochastic retail demand. We prove the existence of optimality for the design of the perishable food supply chain. We then extend the single-item supply chain problem to a multi-item setting and propose an easy-to-implement searching algorithm to produce the optimal allocation of shelf space among these items for practical implementation. Finally, we provide numerical examples to demonstrate the effectiveness of our solution.

Suggested Citation

  • Shuai Yang & Yujie Xiao & Yong-Hong Kuo, 2017. "The Supply Chain Design for Perishable Food with Stochastic Demand," Sustainability, MDPI, vol. 9(7), pages 1-12, July.
  • Handle: RePEc:gam:jsusta:v:9:y:2017:i:7:p:1195-:d:104255
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    References listed on IDEAS

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    Cited by:

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    2. Tianwen Chen & Changqing Liu & Xiang Xu, 2022. "Coordination of Perishable Product Supply Chains with a Joint Contract under Yield and Demand Uncertainty," Sustainability, MDPI, vol. 14(19), pages 1-20, October.
    3. Quan Zhu & Harold Krikke, 2020. "Managing a Sustainable and Resilient Perishable Food Supply Chain (PFSC) after an Outbreak," Sustainability, MDPI, vol. 12(12), pages 1-11, June.
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    6. Mingyuan Wei & Hao Guan & Yunhan Liu & Benhe Gao & Canrong Zhang, 2020. "Production, Replenishment and Inventory Policies for Perishable Products in a Two-Echelon Distribution Network," Sustainability, MDPI, vol. 12(11), pages 1-26, June.
    7. Paramaditya Arismawati & Wahyu Andy Prastyabudi, 2021. "An Inventory Policy On Agroindustry Supply Chain: A Case Study Of Fruit Seasonal In East Java," Food & Agribusiness Management (FABM), Zibeline International Publishing, vol. 2(2), pages 46-50, March.
    8. Shuai Yang & Yujie Xiao & Yan Zheng & Yan Liu, 2017. "The Green Supply Chain Design and Marketing Strategy for Perishable Food Based on Temperature Control," Sustainability, MDPI, vol. 9(9), pages 1-8, August.
    9. Yaqing Xu & Jiang Zhang & Zihao Chen & Yihua Wei, 2021. "Single-Manufacturer Multi-Retailer Supply Chain Models with Discrete Stochastic Demand," Sustainability, MDPI, vol. 13(15), pages 1-13, July.
    10. Mohd Fahmi Bin Mad Ali & Mohd Khairol Anuar Bin Mohd Ariffin & Faizal Bin Mustapha & Eris Elianddy Bin Supeni, 2021. "An Unsupervised Machine Learning-Based Framework for Transferring Local Factories into Supply Chain Networks," Mathematics, MDPI, vol. 9(23), pages 1-31, December.
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