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Forecasting support systems technologies-in-practice: A model of adoption and use for product forecasting

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  • Asimakopoulos, Stavros
  • Dix, Alan

Abstract

This paper examines the critical factors for the effective adoption and use of forecasting support systems (FSS) in product forecasting. The adoption of FSS has proved slow and difficult, and their use ineffective. In this paper, using the technologies-in-practice model developed by Orlikowski, and based on evidence from professional designers, users and organizational documents, we found that FSS adoption and use depend on certain situational factors, such as organizational protocols, communication among stakeholders, and product knowledge availability. At the adoption level, analysis shows that FSS are mostly seen as a means of communicating the forecasts effectively, and their outputs can be used as springboard for organizational actions. The findings provide foundations for an enhanced model of adoption and use for the practical development of FSS designs and services.

Suggested Citation

  • Asimakopoulos, Stavros & Dix, Alan, 2013. "Forecasting support systems technologies-in-practice: A model of adoption and use for product forecasting," International Journal of Forecasting, Elsevier, vol. 29(2), pages 322-336.
    • Handle: RePEc:eee:intfor:v:29:y:2013:i:2:p:322-336
    DOI: 10.1016/j.ijforecast.2012.11.004
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    Cited by:

    1. Petropoulos, Fotios & Apiletti, Daniele & Assimakopoulos, Vassilios & Babai, Mohamed Zied & Barrow, Devon K. & Ben Taieb, Souhaib & Bergmeir, Christoph & Bessa, Ricardo J. & Bijak, Jakub & Boylan, Joh, 2022. "Forecasting: theory and practice," International Journal of Forecasting, Elsevier, vol. 38(3), pages 705-871.
      • Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.
    2. Perera, H. Niles & Hurley, Jason & Fahimnia, Behnam & Reisi, Mohsen, 2019. "The human factor in supply chain forecasting: A systematic review," European Journal of Operational Research, Elsevier, vol. 274(2), pages 574-600.
    3. Fildes, Robert & Petropoulos, Fotios, 2015. "Is there a Golden Rule?," Journal of Business Research, Elsevier, vol. 68(8), pages 1742-1745.
    4. Arvan, Meysam & Fahimnia, Behnam & Reisi, Mohsen & Siemsen, Enno, 2019. "Integrating human judgement into quantitative forecasting methods: A review," Omega, Elsevier, vol. 86(C), pages 237-252.
    5. Fildes, Robert & Goodwin, Paul, 2021. "Stability in the inefficient use of forecasting systems: A case study in a supply chain company," International Journal of Forecasting, Elsevier, vol. 37(2), pages 1031-1046.

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