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Optimal procurement strategies from suppliers with random yield and all-or-nothing risks

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  • Xiang Li

    (Nankai University)

Abstract

Supply uncertainty has been elevated to a strategic level concern in driving supply chain success. This paper considers that a firm faces a deterministic demand and procures from two unreliable suppliers: one is subject to a random disruption and might deliver all or nothing of the firm’s order, while the other one exposes to a random yield risk for the firm’s order. We explore the models of no recourse and ordering with recourse, and derive optimal solutions for each model. We provide the conditions under which single or dual sourcing strategy should be used. We also compare the decisions and profits among different models through computational experiments and find that it is more beneficial to order from the relatively expensive supplier as a backup source.

Suggested Citation

  • Xiang Li, 2017. "Optimal procurement strategies from suppliers with random yield and all-or-nothing risks," Annals of Operations Research, Springer, vol. 257(1), pages 167-181, October.
    • Handle: RePEc:spr:annopr:v:257:y:2017:i:1:d:10.1007_s10479-015-1923-4
    DOI: 10.1007/s10479-015-1923-4
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    References listed on IDEAS

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    Cited by:

    1. Bo He & Yange Yang, 2018. "Mitigating supply risk: an approach with quantity flexibility procurement," Annals of Operations Research, Springer, vol. 271(2), pages 599-617, December.
    2. Svoboda, Josef & Minner, Stefan & Yao, Man, 2021. "Typology and literature review on multiple supplier inventory control models," European Journal of Operational Research, Elsevier, vol. 293(1), pages 1-23.
    3. Tsan-Ming Choi & Ya-Jun Cai, 2020. "Impacts of lead time reduction on fabric sourcing in apparel production with yield and environmental considerations," Annals of Operations Research, Springer, vol. 290(1), pages 521-542, July.
    4. Shalpegin, Timofey, 2020. "Collaborative product development: Managing supplier incentives for key component testing," European Journal of Operational Research, Elsevier, vol. 285(2), pages 553-565.
    5. Noura Yassine, 2020. "A sustainable economic production model: effects of quality and emissions tax from transportation," Annals of Operations Research, Springer, vol. 290(1), pages 73-94, July.
    6. Choi, Tsan-Ming & Wen, Xin & Sun, Xuting & Chung, Sai-Ho, 2019. "The mean-variance approach for global supply chain risk analysis with air logistics in the blockchain technology era," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 127(C), pages 178-191.
    7. Yixin Zhang & Xifu Wang, 2021. "Optimal pricing and sourcing strategies in the presence of supply uncertainty and competition," Journal of Intelligent Manufacturing, Springer, vol. 32(1), pages 61-76, January.
    8. Rongfang Yan & Dejun Kou & Bin Lu, 2019. "Optimal Order Policies for Dual-Sourcing Supply Chains under Random Supply Disruption," Sustainability, MDPI, vol. 11(3), pages 1-14, January.
    9. Kelei Xue & Yongjian Li & Xueping Zhen & Wen Wang, 2020. "Managing the supply disruption risk: option contract or order commitment contract?," Annals of Operations Research, Springer, vol. 291(1), pages 985-1026, August.
    10. Deligiannis, Michalis & Liberopoulos, George & Pandelis, Dimitrios G., 2023. "Managing supply chain risks with dual sourcing: Bayesian learning of censored supply capacity," International Journal of Production Economics, Elsevier, vol. 265(C).
    11. Jun Wang & Qian Zhang & Pengwen Hou, 2022. "Implications of credit default and yield uncertainty on supply chain’s equilibrium financial strategy," Annals of Operations Research, Springer, vol. 315(1), pages 507-533, August.
    12. Liu, Zhongyi & Li, Mengyu & Zhai, Xin, 2022. "Managing supply chain disruption threat via a strategy combining pricing and self-protection," International Journal of Production Economics, Elsevier, vol. 247(C).
    13. Jiarong Luo & Xu Chen & Chong Wang & Gaoxun Zhang, 2021. "Bidirectional options in random yield supply chains with demand and spot price uncertainty," Annals of Operations Research, Springer, vol. 302(1), pages 211-230, July.
    14. Gel, Esma S. & Salman, F. Sibel, 2022. "Dynamic ordering decisions with approximate learning of supply yield uncertainty," International Journal of Production Economics, Elsevier, vol. 243(C).

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