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Inventory - forecasting: mind the gap

Goltsos, Thanos E. ORCID:, Syntetos, Aris A. ORCID:, Glock, Christoph H. and Ioannou, George 2022. Inventory - forecasting: mind the gap. European Journal of Operational Research 299 (2) , pp. 397-419. 10.1016/j.ejor.2021.07.040

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We are concerned with the interaction and integration between demand forecasting and inventory control, in the context of supply chain operations. The majority of the literature is fragmented. Forecasting research more often than not assumes forecasting to be an end in itself, disregarding any subsequent stages of computation that are needed to transform forecasts into replenishment decisions. Conversely, most contributions in inventory theory assume that demand (and its parameters) are known, in effect disregarding any preceding stages of computation. Explicit recognition of these shortcomings is an important step towards more realistic theoretical developments, but still not particularly helpful unless they are somehow addressed. Even then, forecasts often constitute exogenous variables that serially feed into a stock control model. Finally, there is a small but growing stream of research that is explicitly built around jointly tackling the inventory forecasting question. We introduce a framework to define four levels of integration: from disregarding, to acknowledging, to partly addressing, to fully understanding the interactions. Focusing on the last two, we conduct a structured review of relevant (integrated) academic contributions in the area of forecasting and inventory control and argue for their classification with regard to integration. We show that the development from one level to another is in many cases chronological in order, but also associated with specific schools of thought. We also argue that although movement from one level to another adds realism, it also adds complexity in terms of actual implementations, and thus a trade-off exists. The article makes a contribution into an area that has always been fragmented despite the importance of bringing the forecasting and inventory communities together to solve problems of common interest. We close with an indicative agenda for further research and a call for more theoretical contributions, but also more work that would help to expand the empirical knowledge base in this area.

Item Type: Article
Date Type: Publication
Status: Published
Schools: Business (Including Economics)
Additional Information: This is an open access article under the CC BY license (
Publisher: Elsevier
ISSN: 0377-2217
Funders: EPSRC
Date of First Compliant Deposit: 23 August 2021
Date of Acceptance: 21 July 2021
Last Modified: 03 May 2023 04:07

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