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

Syntetos, Argyrios, Babai, Zied, Boylan, John, 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. 10.1016/j.ejor.2015.11.010

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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 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: Article
Date Type: Publication
Status: Published
Schools: Business (Including Economics)
Subjects: H Social Sciences > HF Commerce
H Social Sciences > HG Finance
Additional Information: This journal has an embargo period of 36 months PDF uploaded in accordance with publisher's policies at (accessed 19.11.15).
Publisher: Elsevier
ISSN: 0377-2217
Date of First Compliant Deposit: 30 March 2016
Date of Acceptance: 11 November 2015
Last Modified: 17 Nov 2018 02:30

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