On the performance of hierarchical forecasting approaches: case of a vaccine supply chain

Omri, Oussema, Nadine, Kafa, Babai, Mohamed Zied, Jemai, Zied and Rostami-Tabar, Bahman ORCID: https://orcid.org/0000-0002-3730-0045 2025. On the performance of hierarchical forecasting approaches: case of a vaccine supply chain. Journal of the Operational Research Society Item availability restricted.

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Abstract

Accurate demand forecasts are crucial for effective planning and decision-making in vaccine supply chains (VSCs). VSCs exhibit a hierarchical structure, a feature often overlooked in both research and practice. Moreover, while some studies assess the accuracy of hierarchical forecasting methods, they do not investigate their impact on inventory performance. This paper empirically analyzes both the forecast accuracy and inventory performance of multiple hierarchical forecasting approaches, including Bottom-Up, Top-Down, and Minimum Trace Reconciliation, using two forecasting models: Error-Trend-Seasonality (ETS) and Auto-Regressive Integrated Moving Average (ARIMA). A periodic reorder-point order-up-to-level policy is applied for inventory control at different hierarchy levels, with performance measured by combined inventory holding volumes and achieved service-level efficiency. The empirical investigation uses data from the childhood VSC in an African developing country, which follows a four-level geographical hierarchy: national, regional, district, and subdistrict. The results show that while the Bottom-Up approach consistently delivers high forecast accuracy and strong inventory performance, the Top-Down approach occasionally yields better inventory efficiency despite its lower forecast accuracy.

Item Type:	Article
Status:	In Press
Schools:	Schools > Business (Including Economics)
Publisher:	Taylor and Francis Group
ISSN:	1476-9360
Date of First Compliant Deposit:	26 September 2025
Date of Acceptance:	13 September 2025
Last Modified:	26 Sep 2025 10:00
URI:	https://orca.cardiff.ac.uk/id/eprint/181334

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