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Ordering and inventory reallocation decisions in a shared inventory platform with demand information sharing

Author

Listed:
  • Qi Xu

    (Donghua University)

  • Zhong-miao Sun

    (Donghua University)

  • Xiao-qing Gao

    (Donghua University)

Abstract

In this paper, we study the optimal ordering and inventory reallocation of the inventory service platform under the retailer demand information sharing. Due to the uncertainty of market demand, retailers’ demand information is likely to be inaccurate or even false. In this regard, retailers can reduce demand uncertainty by screening market signals. Therefore, based on the sharing of mean demand information and market signals, we explored the platform’s optimal ordering and inventory reallocation strategies, analyzed the retailer’s motivation for sharing false demand information, and proposed a corresponding penalty coordination mechanism. Our results show that the sharing of demand information and screening market signals reduces the uncertainty of market demand, thereby improving the accuracy of orders and increasing profit of the system. On the other hand, we find that the inventory reallocation strategy of the platform is affected by uncertain market information, but has nothing to do with the actual average demand and market signals shared by retailers. In this way, retailers will only share real information when the sharing system meets certain key conditions, otherwise they may share false demand information. The proposed punishment mechanism can encourage retailers to share their actual demand information with the platform.

Suggested Citation

  • Qi Xu & Zhong-miao Sun & Xiao-qing Gao, 2023. "Ordering and inventory reallocation decisions in a shared inventory platform with demand information sharing," Annals of Operations Research, Springer, vol. 329(1), pages 471-499, October.
  • Handle: RePEc:spr:annopr:v:329:y:2023:i:1:d:10.1007_s10479-020-03803-5
    DOI: 10.1007/s10479-020-03803-5
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