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Tailored Supply Chain Decision Making Under Price-Sensitive Stochastic Demand and Delivery Uncertainty

Author

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  • Saibal Ray

    (Desautels Faculty of Management, McGill University, 1001 W. Sherbrooke Street, Montréal, Quebec, Canada H3A IG5)

  • Shanling Li

    (Desautels Faculty of Management, McGill University, 1001 W. Sherbrooke Street, Montréal, Quebec, Canada H3A IG5)

  • Yuyue Song

    (Desautels Faculty of Management, McGill University, 1001 W. Sherbrooke Street, Montréal, Quebec, Canada H3A IG5)

Abstract

In this paper, we study a serial two-echelon supply chain selling a procure-to-stock product in a price-sensitive market. Our analytical modelling framework incorporates optimal pricing and stocking decisions for both echelons in the presence of stochastic demand and random delivery times. We focus on understanding how these decisions for the chain are affected by its management paradigm (centralized or decentralized), and its business characteristics---price sensitivity, demand uncertainty, and delivery time variability. A novel combination of transformations enables us to analyze the framework and determine the unique optimal choices for centralized and wholesale price-based decentralized supply chains. More detailed investigation reveals that, in general, the business characteristics influence both the behavior and the optimal values of the decision variables, while the management paradigm primarily governs the optimal values. We illustrate the significance of these results in terms of how managers should tailor their decisions to align with their business requirements. Subsequently, comparison of the optimal profits between the channel partners and the management paradigms provides implications for decentralization strategy. A decentralized chain is most inefficient for moderately price-sensitive customers and uncertain environments, but is relatively more effective when dealing with mature products. We propose a contracting scheme that can improve the decentralized chain profit in reliable delivery time settings. The salient modelling insight of this paper is that ignoring the randomness of delivery time trivializes the interaction between pricing and stocking decisions. On the other hand, from a managerial viewpoint, we establish that optimal pricing policies provide the means to increase revenue and also act as strategic tools for tackling uncertainty.

Suggested Citation

  • Saibal Ray & Shanling Li & Yuyue Song, 2005. "Tailored Supply Chain Decision Making Under Price-Sensitive Stochastic Demand and Delivery Uncertainty," Management Science, INFORMS, vol. 51(12), pages 1873-1891, December.
    • Handle: RePEc:inm:ormnsc:v:51:y:2005:i:12:p:1873-1891
    DOI: 10.1287/mnsc.1050.0452
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    References listed on IDEAS

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    Cited by:

    1. Xiang Fang & Jun Ru & Yunzeng Wang, 2021. "The Effect of List Price on Channel Performance with Consignment," Production and Operations Management, Production and Operations Management Society, vol. 30(1), pages 235-252, January.
    2. Blome, Constantin & Schoenherr, Tobias & Eckstein, Dominik, 2014. "The impact of knowledge transfer and complexity on supply chain flexibility: A knowledge-based view," International Journal of Production Economics, Elsevier, vol. 147(PB), pages 307-316.
    3. Xing, Wei & Wang, Shouyang & Liu, Liming, 2012. "Optimal ordering and pricing strategies in the presence of a B2B spot market," European Journal of Operational Research, Elsevier, vol. 221(1), pages 87-98.
    4. Ru, Jun & Wang, Yunzeng, 2010. "Consignment contracting: Who should control inventory in the supply chain?," European Journal of Operational Research, Elsevier, vol. 201(3), pages 760-769, March.
    5. Ma, Jun & Nault, Barrie R. & Tu, Yiliu (Paul), 2023. "Customer segmentation, pricing, and lead time decisions: A stochastic-user-equilibrium perspective," International Journal of Production Economics, Elsevier, vol. 264(C).
    6. Xing, Wei & Liu, Liming & Wang, Shouyang, 2014. "More than a second channel? Supply chain strategies in B2B spot markets," European Journal of Operational Research, Elsevier, vol. 239(3), pages 699-710.
    7. Zhu, Stuart X., 2015. "Integration of capacity, pricing, and lead-time decisions in a decentralized supply chain," International Journal of Production Economics, Elsevier, vol. 164(C), pages 14-23.
    8. Peter Seele & Claus Dierksmeier & Reto Hofstetter & Mario D. Schultz, 2021. "Mapping the Ethicality of Algorithmic Pricing: A Review of Dynamic and Personalized Pricing," Journal of Business Ethics, Springer, vol. 170(4), pages 697-719, May.
    9. Chung, Wenming & Talluri, Srinivas & Narasimhan, Ram, 2015. "Optimal pricing and inventory strategies with multiple price markdowns over time," European Journal of Operational Research, Elsevier, vol. 243(1), pages 130-141.
    10. Yang, Yang & Liu, Jie, 2023. "Price timing and financing strategies for a capital-constrained supply chain with price-dependent stochastic demand," International Journal of Production Economics, Elsevier, vol. 261(C).
    11. Sinha, Priyank & Kumar, Sameer & Prakash, Surya, 2020. "Measuring and mitigating the effects of cost disturbance propagation in multi-echelon apparel supply chains," European Journal of Operational Research, Elsevier, vol. 282(1), pages 148-160.
    12. Fuqiang Zhang, 2010. "Procurement Mechanism Design in a Two-Echelon Inventory System with Price-Sensitive Demand," Manufacturing & Service Operations Management, INFORMS, vol. 12(4), pages 608-626, August.
    13. Adeinat, Hamza & Pazhani, Subramanian & Mendoza, Abraham & Ventura, Jose A., 2022. "Coordination of pricing and inventory replenishment decisions in a supply chain with multiple geographically dispersed retailers," International Journal of Production Economics, Elsevier, vol. 248(C).
    14. Ray, Saibal & Song, Yuyue & Verma, Manish, 2010. "Comparison of two periodic review models for stochastic and price-sensitive demand environment," International Journal of Production Economics, Elsevier, vol. 128(1), pages 209-222, November.
    15. Jiang, Li, 2012. "The implications of postponement on contract design and channel performance," European Journal of Operational Research, Elsevier, vol. 216(2), pages 356-366.
    16. Langenberg, Kerstin U. & Seifert, Ralf W. & Tancrez, Jean-Sébastien, 2012. "Aligning supply chain portfolios with product portfolios," International Journal of Production Economics, Elsevier, vol. 135(1), pages 500-513.
    17. Noori-Daryan, Mahsa & Taleizadeh, Ata Allah & Jolai, Fariborz, 2019. "Analyzing pricing, promised delivery lead time, supplier-selection, and ordering decisions of a multi-national supply chain under uncertain environment," International Journal of Production Economics, Elsevier, vol. 209(C), pages 236-248.
    18. Chung, Wenming & Talluri, Srinivas & Narasimhan, Ram, 2011. "Price markdown scheme in a multi-echelon supply chain in a high-tech industry," European Journal of Operational Research, Elsevier, vol. 215(3), pages 581-589, December.
    19. Zhang, Guoquan & Shang, Jennifer & Li, Wenli, 2011. "Collaborative production planning of supply chain under price and demand uncertainty," European Journal of Operational Research, Elsevier, vol. 215(3), pages 590-603, December.

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