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Modeling the Benefits of Sharing Future Demand Information

Author

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  • Kaijie Zhu

    (Department of Industrial Engineering and Engineering Management, Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong)

  • Ulrich W. Thonemann

    (Institute of Supply Chain Management, University of Münster, D-48143 Münster, Germany)

Abstract

We analyze how sharing of future demand information (FDI) can help companies to lower cost. FDI is imperfect information on the customer demands of the upcoming period. We consider a supply chain with a single retailer and multiple customers, where customer demands are normally distributed and correlated. The retailer faces two decisions: With which customers should information be shared and how much should be ordered? We model the problem as a two-stage dynamic program, develop an optimal solution approach, and provide structural insights into the optimal extent of FDI sharing. We show that information cost and demand correlation are important factors for determining the optimal extent of FDI sharing. For a simplified version of the problem where only a single customer is contacted, we analyze how the optimal solution is affected by nonidentically distributed or nonuniformly correlated demands.

Suggested Citation

  • Kaijie Zhu & Ulrich W. Thonemann, 2004. "Modeling the Benefits of Sharing Future Demand Information," Operations Research, INFORMS, vol. 52(1), pages 136-147, February.
    • Handle: RePEc:inm:oropre:v:52:y:2004:i:1:p:136-147
    DOI: 10.1287/opre.1030.0061
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    Cited by:

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    3. Jean-Philippe Gayon & Saif Benjaafar & Francis de Véricourt, 2009. "Using Imperfect Advance Demand Information in Production-Inventory Systems with Multiple Customer Classes," Manufacturing & Service Operations Management, INFORMS, vol. 11(1), pages 128-143, July.
    4. Borga Deniz, 2012. "Inventory Control with Advance Demand Information When Demand is Intermittent," Business and Management Research, Business and Management Research, Sciedu Press, vol. 1(4), pages 35-45, December.
    5. Xiao Fu & Guanghua Han, 2017. "Trust-Embedded Information Sharing among One Agent and Two Retailers in an Order Recommendation System," Sustainability, MDPI, vol. 9(5), pages 1-18, April.
    6. Rippe, Christoph & Kiesmüller, Gudrun P., 2023. "The repair kit problem with imperfect advance demand information," European Journal of Operational Research, Elsevier, vol. 304(2), pages 558-576.
    7. Kefeng Xu & Yang Dong & Yu Xia, 2014. "‘Too Little’ or ‘Too Late’: The Timing of Supply Chain Demand Collaboration," Working Papers 0203mss, College of Business, University of Texas at San Antonio.
    8. Choi, Tsan-Ming & Sethi, Suresh, 2010. "Innovative quick response programs: A review," International Journal of Production Economics, Elsevier, vol. 127(1), pages 1-12, September.
    9. Saif Benjaafar & William L. Cooper & Setareh Mardan, 2011. "Production‐inventory systems with imperfect advance demand information and updating," Naval Research Logistics (NRL), John Wiley & Sons, vol. 58(2), pages 88-106, March.
    10. Tong Wang & Beril L. Toktay, 2008. "Inventory Management with Advance Demand Information and Flexible Delivery," Management Science, INFORMS, vol. 54(4), pages 716-732, April.
    11. Fu, Qi & Zhu, Kaijie, 2010. "Endogenous information acquisition in supply chain management," European Journal of Operational Research, Elsevier, vol. 201(2), pages 454-462, March.
    12. Felix Papier, 2016. "Supply Allocation Under Sequential Advance Demand Information," Operations Research, INFORMS, vol. 64(2), pages 341-361, April.
    13. Taher Ahmadi & Zümbül Atan & Ton de Kok & Ivo Adan, 2019. "Optimal control policies for an inventory system with commitment lead time," Naval Research Logistics (NRL), John Wiley & Sons, vol. 66(3), pages 193-212, April.
    14. Uçkun, Canan & Karaesmen, Fikri & Savas, Selçuk, 2008. "Investment in improved inventory accuracy in a decentralized supply chain," International Journal of Production Economics, Elsevier, vol. 113(2), pages 546-566, June.
    15. Yu, Yugang & Zhou, Sijie & Shi, Ye, 2020. "Information sharing or not across the supply chain: The role of carbon emission reduction," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 137(C).
    16. Tan, Tarkan & Güllü, Refik & Erkip, Nesim, 2009. "Using imperfect advance demand information in ordering and rationing decisions," International Journal of Production Economics, Elsevier, vol. 121(2), pages 665-677, October.
    17. Mohammed Hichame Benbitour & Evren Sahin, 2015. "Evaluation of the Impact of Uncertain Advance Demand Information on Production/Inventory Systems," Post-Print hal-01199290, HAL.
    18. Seyed M.R. Iravani & Tieming Liu & K.L. Luangkesorn & David Simchi‐Levi, 2007. "A produce‐to‐stock system with advance demand information and secondary customers," Naval Research Logistics (NRL), John Wiley & Sons, vol. 54(3), pages 331-345, April.
    19. Fernando Bernstein & Gregory A. DeCroix, 2015. "Advance Demand Information in a Multiproduct System," Manufacturing & Service Operations Management, INFORMS, vol. 17(1), pages 52-65, February.
    20. Amit Verma & Ann Melissa Campbell, 2019. "Strategic placement of telemetry units considering customer usage correlation," EURO Journal on Transportation and Logistics, Springer;EURO - The Association of European Operational Research Societies, vol. 8(1), pages 35-64, March.

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