Meta-inventory management decisions: A theoretical model

Jianhua Xiao, Siyuan Ma, Shuyi Wang and George Q. Huang

International Journal of Production Economics, 2024, vol. 275, issue C

Abstract: The manufacturing industry leverages the traceability and visibility of Industrial 4.0 to integrate digital and physical twins for solving the intricacy of a production system. Physical entities can be converted into digital twins with smart IoT (Internet of Things) devices and computational techniques. Research efforts have generally focused on the development of digital twin models for basic practical applications. Advanced applications of digital twins have not been widely reported. An innovative use of digital twins for inventory management has only been analysed theoretically and reported as meta-inventory management for the first time by Wang and Huang (2023). This paper extends the novel concept of meta-inventory by using a theoretical Newsvendor model for original equipment manufacturing (OEM) and own brand manufacturing (OBM) factories. The impacts of meta-inventory on both supply chain members, including the factory and its downstream retailer, are investigated through two kinds of response models (e.g., hybrid and separate response models). Analytical and numerical results show that a factory achieves better performance by using a separate model since it clarifies the responsibility of digital twins. The hybrid response model holds a higher proportion of digital inventory, but its final profits are less than that in the separate model due to fewer orders and higher prices and costs of uncertainty. OBM can better leverage the advantage of digital twins than OEM. Also, both supply chain members benefit from the implementation of meta-inventory out of profit increase, price reduction, and risk hedging. This research provides guidance for manufacturing sites to implement digital twins and reduce their concerns on investing in meta-inventory.

Keywords: Meta-inventory; Digital twins; Separate/hybrid response models; Inventory management decisions; Industrial 4.0 (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:eee:proeco:v:275:y:2024:i:c:s0925527324001968

DOI: 10.1016/j.ijpe.2024.109339

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