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A two-stage supply chain with demand sensitive to price, delivery time, and reliability of delivery

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  • Tiaojun Xiao

    (Nanjing University)

  • Xiangtong Qi

    (The Hong Kong University of Science and Technology)

Abstract

We consider a two-stage supply chain with one supplier and one manufacturer. The manufacturer faces a Poisson demand process where the arrival rate depends on the selling price, the announced delivery time, and the delivery reliability defined as the probability of satisfying the announced delivery time. Such a demand model generalizes the works in the literature by simultaneously considering the above three demand sensitivity factors. The main purpose of this paper is to study the equilibrium decisions in the supply chain with an all-unit quantity discount contract. We consider four scenarios regarding whether the leadtime standard, the delivery reliability standard, and the manufacturer’s capacity are endogenous, and whether the manufacturer’s production cost is its private information. We find that an all-unit quantity discount scheme can coordinate the supply chain for most cases. Managerial insights are observed regarding the impact of the three demand sensitivity factors. For example, the breakpoint in an optimal quantity discount contract always increases with the delivery reliability sensitivity under an exogenous delivery reliability, but may decrease under an endogenous delivery reliability; with asymmetric information, a higher variance of the manufacturer’s unit production costs leads to a lower unit wholesale price for the low-cost manufacturer.

Suggested Citation

  • Tiaojun Xiao & Xiangtong Qi, 2016. "A two-stage supply chain with demand sensitive to price, delivery time, and reliability of delivery," Annals of Operations Research, Springer, vol. 241(1), pages 475-496, June.
  • Handle: RePEc:spr:annopr:v:241:y:2016:i:1:d:10.1007_s10479-012-1085-6
    DOI: 10.1007/s10479-012-1085-6
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    3. Zhai, Yue & Hua, Guowei & Cheng, Meng & Cheng, T.C.E., 2023. "Production lead-time hedging and order allocation in an MTO supply chain," European Journal of Operational Research, Elsevier, vol. 311(3), pages 887-905.
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    7. Sayid Albana, Abduh & Frein, Yannick & Hammami, Ramzi, 2018. "Effect of a lead time-dependent cost on lead time quotation, pricing, and capacity decisions in a stochastic make-to-order system with endogenous demand," International Journal of Production Economics, Elsevier, vol. 203(C), pages 83-95.
    8. Xu, Xiaoping & Zhang, Mian & He, Ping, 2020. "Coordination of a supply chain with online platform considering delivery time decision," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 141(C).
    9. Amirmohsen Golmohammadi & Alireza Tajbakhsh & Mohamed Dia & Pawoumodom M. Takouda, 2022. "Effect of timing on reliability improvement and ordering decisions in a decentralized assembly system," Annals of Operations Research, Springer, vol. 312(1), pages 159-192, May.
    10. Jalili Marand, Ata & Tang, Ou & Li, Hongyan, 2019. "Quandary of service logistics: Fast or reliable?," European Journal of Operational Research, Elsevier, vol. 275(3), pages 983-996.
    11. Demir, Sercan & Aktas, Ersin & Paksoy, Turan, 2021. "Cold chain logistics: The case of Turkish Airlines vaccine distribution," Chapters from the Proceedings of the Hamburg International Conference of Logistics (HICL), in: Kersten, Wolfgang & Ringle, Christian M. & Blecker, Thorsten (ed.), Adapting to the Future: How Digitalization Shapes Sustainable Logistics and Resilient Supply Chain Management. Proceedings of the Hamburg Internationa, volume 31, pages 771-798, Hamburg University of Technology (TUHH), Institute of Business Logistics and General Management.
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    14. Hongbo Li & Zhenzhen Wang & Zhijie Yuan & Xin Yan, 2023. "Multidimensional Evaluation of Consumers’ Shopping Risks under Live-Streaming Commerce," Sustainability, MDPI, vol. 15(19), pages 1-14, September.
    15. Hammami, Ramzi & Frein, Yannick & Albana, Abduh S., 2020. "Delivery time quotation and pricing in two-stage supply chains: Centralized decision-making with global and local managerial approaches," European Journal of Operational Research, Elsevier, vol. 286(1), pages 164-177.
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