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

Qi Xu, Zhong-miao Sun () and Xiao-qing Gao
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Qi Xu: Donghua University
Zhong-miao Sun: Donghua University
Xiao-qing Gao: Donghua University

Annals of Operations Research, 2023, vol. 329, issue 1, No 17, 499 pages

Abstract: 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.

Keywords: Stochastic demand; Market signal; Fake information sharing; Penalty mechanism (search for similar items in EconPapers)
Date: 2023
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DOI: 10.1007/s10479-020-03803-5

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