The value of point of sales information in upstream supply chain forecasting: an empirical investigation

Abolghasemi, Mahdi, Rostami-Tabar, Bahman ORCID: https://orcid.org/0000-0002-3730-0045 and Syntetos, Argyrios ORCID: https://orcid.org/0000-0003-4639-0756 2023. The value of point of sales information in upstream supply chain forecasting: an empirical investigation. International Journal of Production Research 61 (7) , pp. 2162-2177. 10.1080/00207543.2022.2063086

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Abstract

Traditionally, manufacturers use past orders (received from some downstream supply chain level) to forecast future ones, before turning such forecasts into appropriate inven- tory and production optimization decisions. With recent advances in information sharing technologies, upstream supply chain (SC) companies may have access to downstream point of sales (POS) data. Such data can be used as an alternative source of information for forecasting. There are a few studies that investigate the benefits of using orders versus POS data in upstream SC forecasting; the results are mixed and empirical evidence is lacking, particularly in the context of multi-echelon SCs and in the presence of promo- tions. We investigate an actual three-echelon SC with 684 series where the manufacturer aims to forecast orders received from distribution centers (DCs) using either aggregated POS data at DC level or historical orders received from the DCs. Our results show that the order-based methods outperform the POS-based ones by 6%-15%. We find that low values of mean, variance, non-linearity and entropy of POS data, and promotion presence negatively impact the performance of the POS-based forecasts. Such findings are useful for determining the appropriate source of data and the impact of series characteristics for order forecasting in SCs.

Item Type:	Article
Date Type:	Publication
Status:	Published
Schools:	Business (Including Economics)
Subjects:	H Social Sciences > H Social Sciences (General)
Publisher:	Taylor and Francis
ISSN:	0020-7543
Date of First Compliant Deposit:	9 May 2022
Date of Acceptance:	27 March 2022
Last Modified:	28 Nov 2024 22:15
URI:	https://orca.cardiff.ac.uk/id/eprint/149339

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