Supply chain forecasting : theory, practice, their gap and the future

Syntetos, Aris and Babai, Zied and Boylan, John Edward and Kolassa, Stephan and Nikolopoulos, Konstantinos (2016) Supply chain forecasting : theory, practice, their gap and the future. European Journal of Operational Research, 252 (1). pp. 1-26. ISSN 0377-2217

[thumbnail of EJOR review paper_R2 manuscript]
PDF (EJOR review paper_R2 manuscript)
EJOR_review_paper_R2_manuscript.pdf - Accepted Version
Available under License Creative Commons Attribution-NonCommercial-NoDerivs.

Download (1MB)


Supply Chain Forecasting (SCF) goes beyond the operational task of extrapolating demand requirements at one echelon. It involves complex issues such as supply chain coordination and sharing of information between multiple stakeholders. Academic research in SCF has tended to neglect some issues that are important in practice. In areas of practical relevance, sound theoretical developments have rarely been translated into operational solutions or integrated in state-of-the-art decision support systems. Furthermore, many experience-driven heuristics are increasingly used in everyday business practices. These heuristics are not supported by substantive scientific evidence; however, they are sometimes very hard to outperform. This can be attributed to the robustness of these simple and practical solutions such as aggregation approaches for example (across time, customers and products). This paper provides a comprehensive review of the literature and aims at bridging the gap between the theory and practice in the existing knowledge base in SCF. We highlight the most promising approaches and suggest their integration in forecasting support systems. We discuss the current challenges both from a research and practitioner perspective and provide a research and application agenda for further work in this area. Finally, we make a contribution in the methodology underlying the preparation of review articles by means of involving the forecasting community in the process of deciding both the content and structure of this paper.

Item Type:
Journal Article
Journal or Publication Title:
European Journal of Operational Research
Additional Information:
This is the author’s version of a work that was accepted for publication in European Journal of Operational Research. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in European Journal of Operational Research, 252, 1, 2016 DOI: 10.1016/j.ejor.2015.11.010
Uncontrolled Keywords:
?? supply chain forecastingforecasting softwareforecasting empirical researchliterature reviewmodelling and simulationmanagement science and operations researchinformation systems and management ??
ID Code:
Deposited By:
Deposited On:
24 Mar 2016 16:40
Last Modified:
12 May 2024 01:00