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Forecasting and Operational Research:A Review

Fildes, R A and Nikolopoulos, K and Crone, S and Syntetos, A (2008) Forecasting and Operational Research:A Review. Journal of the Operational Research Society, 59 (9). pp. 1150-1172.

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    Abstract

    From its foundation, operational research (OR) has made many substantial contributions to practical forecasting in organizations. Equally, researchers in other disciplines have influenced forecasting practice. Since the last survey articles in JORS, forecasting has developed as a discipline with its own journals. While the effect of this increased specialization has been a narrowing of the scope of OR's interest in forecasting, research from an OR perspective remains vigorous. OR has been more receptive than other disciplines to the specialist research published in the forecasting journals, capitalizing on some of their key findings. In this paper, we identify the particular topics of OR interest over the past 25 years. After a brief summary of the current research in forecasting methods, we examine those topic areas that have grabbed the attention of OR researchers: computationally intensive methods and applications in operations and marketing. Applications in operations have proved particularly important, including the management of inventories and the effects of sharing forecast information across the supply chain. The second area of application is marketing, including customer relationship management using data mining and computer-intensive methods. The paper concludes by arguing that the unique contribution that OR can continue to make to forecasting is through developing models that link the effectiveness of new forecasting methods to the organizational context in which the models will be applied. The benefits of examining the system rather than its separate components are likely to be substantial.

    Item Type: Article
    Journal or Publication Title: Journal of the Operational Research Society
    Uncontrolled Keywords: forecasting ; supply chain ; market models ; data mining ; operations
    Subjects: UNSPECIFIED
    Departments: Lancaster University Management School > Management Science
    ID Code: 45545
    Deposited By: ep_importer_pure
    Deposited On: 11 Jul 2011 19:33
    Refereed?: Yes
    Published?: Published
    Last Modified: 19 Dec 2013 13:30
    Identification Number:
    URI: http://eprints.lancs.ac.uk/id/eprint/45545

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