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Scenarios as channels of forecast advice

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  • Önkal, Dilek
  • Sayım, Kadire Zeynep
  • Gönül, Mustafa Sinan

Abstract

Today's business environment provides tougher competition than ever before, stressing the important role played by information and forecasts in decision-making. The scenario method has been popular for focused organizational learning, decision making and strategic thinking in business contexts, and yet, its use in communicating forecast information and advice has received little research attention. This is surprising since scenarios may provide valuable tools for communication between forecast providers and users in organizations, offering efficient platforms for information exchange via structured storylines of plausible futures. In this paper, we aim to explore the effectiveness of using scenarios as channels of forecast advice. An experimental study is designed to investigate the effects of providing scenarios as forecast advice on individual and group-based judgmental predictions. Participants are given time series information and model forecasts, along with (i) best-case, (ii) worst-case, (iii) both, or (iv) no scenarios. Different forecasting formats are used (i.e., point forecast, best-case forecast, worst-case forecast, and surprise probability), and both individual predictions and consensus forecasts are requested. Forecasts made with and without scenarios are compared for each of these formats to explore the potential effects of providing scenarios as forecast advice. In addition, group effects are investigated via comparisons of composite versus consensus predictions. The paper concludes with a discussion of results and implications for future research on scenario use in forecasting.

Suggested Citation

  • Önkal, Dilek & Sayım, Kadire Zeynep & Gönül, Mustafa Sinan, 2013. "Scenarios as channels of forecast advice," Technological Forecasting and Social Change, Elsevier, vol. 80(4), pages 772-788.
    • Handle: RePEc:eee:tefoso:v:80:y:2013:i:4:p:772-788
    DOI: 10.1016/j.techfore.2012.08.015
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    Citations

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    Cited by:

    1. Shari De Baets & Dilek Önkal & Wasim Ahmed, 2022. "Do Risky Scenarios Affect Forecasts of Savings and Expenses?," Forecasting, MDPI, vol. 4(1), pages 1-28, February.
    2. Fildes, Robert & Goodwin, Paul & Onkal, Dilek, 2015. "Information use in supply chain forecasting," MPRA Paper 66034, University Library of Munich, Germany.
    3. Bradford Ashton, 2020. "Intelligent Technology Scanning: Aims, Content, and Practice," Foresight and STI Governance (Foresight-Russia till No. 3/2015), National Research University Higher School of Economics, vol. 14(3), pages 15-29.
    4. 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.
    5. Eksoz, Can & Mansouri, S. Afshin & Bourlakis, Michael & Önkal, Dilek, 2019. "Judgmental adjustments through supply integration for strategic partnerships in food chains," Omega, Elsevier, vol. 87(C), pages 20-33.
    6. Chang, Suk-Gwon, 2015. "A structured scenario approach to multi-screen ecosystem forecasting in Korean communications market," Technological Forecasting and Social Change, Elsevier, vol. 94(C), pages 1-20.
    7. Crawford, Megan M. & Wright, George, 2022. "The value of mass-produced COVID-19 scenarios: A quality evaluation of development processes and scenario content," Technological Forecasting and Social Change, Elsevier, vol. 183(C).
    8. Önkal, Dilek & Sinan Gönül, M. & Goodwin, Paul & Thomson, Mary & Öz, Esra, 2017. "Evaluating expert advice in forecasting: Users’ reactions to presumed vs. experienced credibility," International Journal of Forecasting, Elsevier, vol. 33(1), pages 280-297.
    9. Caliskan Demirag, Ozgun & Xue, Weili & Wang, Jie, 2021. "Retailers’ Order Timing Strategies under Competition and Demand Uncertainty," Omega, Elsevier, vol. 101(C).
    10. Liu, Anyu & Vici, Laura & Ramos, Vicente & Giannoni, Sauveur & Blake, Adam, 2021. "Visitor arrivals forecasts amid COVID-19: A perspective from the Europe team," Annals of Tourism Research, Elsevier, vol. 88(C).
    11. Pizarro-Alonso, Amalia & Ravn, Hans & Münster, Marie, 2019. "Uncertainties towards a fossil-free system with high integration of wind energy in long-term planning," Applied Energy, Elsevier, vol. 253(C), pages 1-1.
    12. Goodwin, Paul & Gönül, M. Sinan & Önkal, Dilek, 2019. "When providing optimistic and pessimistic scenarios can be detrimental to judgmental demand forecasts and production decisions," European Journal of Operational Research, Elsevier, vol. 273(3), pages 992-1004.
    13. Karaca, Ferhat & Raven, Paul Graham & Machell, John & Camci, Fatih, 2015. "A comparative analysis framework for assessing the sustainability of a combined water and energy infrastructure," Technological Forecasting and Social Change, Elsevier, vol. 90(PB), pages 456-468.
    14. Fildes, Robert & Goodwin, Paul & Önkal, Dilek, 2019. "Use and misuse of information in supply chain forecasting of promotion effects," International Journal of Forecasting, Elsevier, vol. 35(1), pages 144-156.
    15. Massimo FLORIO & Andrea BASTIANIN & Paolo CASTELNOVO, 2017. "The Socio–Economic Impact of a Breakthrough in the Particle Accelerators’ Technology: A Research Agenda," Departmental Working Papers 2017-18, Department of Economics, Management and Quantitative Methods at Università degli Studi di Milano.
    16. Paul J. H. Schoemaker, 2020. "Thematic reflections on 18 expert commentaries," Futures & Foresight Science, John Wiley & Sons, vol. 2(3-4), September.
    17. Robert Fildes, 2022. "Scenarios, strategic conversations, and forecasting: A commentary on Rowland and Spaniol (2021)," Futures & Foresight Science, John Wiley & Sons, vol. 4(1), March.
    18. Wicke, Lars & Dhami, Mandeep K. & Önkal, Dilek & Belton, Ian K., 2022. "Using scenarios to forecast outcomes of a refugee crisis," International Journal of Forecasting, Elsevier, vol. 38(3), pages 1175-1184.

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