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Heuristics, biases and improvement strategies in judgmental time series forecasting

Author

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  • Goodwin, P
  • Wright, G

Abstract

There is evidence that forecasts produced in business and other organizations often involve substantial elements of human judgment. In forming their judgments forecasters may have access to either time series or time series and contextual information. This paper reviews the literature to ascertain, for each information level, what we currently know about the heuristics people use when producing judgmental point forecasts and the biases which emanate from the use of these heuristics. The paper then uses evidence from the literature to review the effectiveness of a number of strategies which are designed to improve the accuracy of judgmental point forecasts.

Suggested Citation

  • Goodwin, P & Wright, G, 1994. "Heuristics, biases and improvement strategies in judgmental time series forecasting," Omega, Elsevier, vol. 22(6), pages 553-568, November.
    • Handle: RePEc:eee:jomega:v:22:y:1994:i:6:p:553-568
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    Citations

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    Cited by:

    1. Anqiang Huang & Kin Keung Lai & Han Qiao & Shouyang Wang & Zhenji Zhang, 2018. "Does Interval Knowledge Sharpen Forecasting Models? Evidence from China’s Typical Ports," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 17(02), pages 467-483, March.
    2. Goodwin, P., 1996. "Statistical correction of judgmental point forecasts and decisions," Omega, Elsevier, vol. 24(5), pages 551-559, October.
    3. Anqiang Huang & Han Qiao & Shouyang Wang & John Liu, 2016. "Improving Forecasting Performance by Exploiting Expert Knowledge: Evidence from Guangzhou Port," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 15(02), pages 387-401, March.
    4. Reimers, Stian & Harvey, Nigel, 2024. "Bars, lines and points: The effect of graph format on judgmental forecasting," International Journal of Forecasting, Elsevier, vol. 40(1), pages 44-61.
    5. Zoe Theocharis & Leonard A. Smith & Nigel Harvey, 2019. "The influence of graphical format on judgmental forecasting accuracy: Lines versus points," Futures & Foresight Science, John Wiley & Sons, vol. 1(1), March.
    6. Harvey, Nigel & Harries, Clare, 2004. "Effects of judges' forecasting on their later combination of forecasts for the same outcomes," International Journal of Forecasting, Elsevier, vol. 20(3), pages 391-409.
    7. Syntetos, Aris A. & Kholidasari, Inna & Naim, Mohamed M., 2016. "The effects of integrating management judgement into OUT levels: In or out of context?," European Journal of Operational Research, Elsevier, vol. 249(3), pages 853-863.
    8. Wright, George & Lawrence, Michael J. & Collopy, Fred, 1996. "The role and validity of judgment in forecasting," International Journal of Forecasting, Elsevier, vol. 12(1), pages 1-8, March.
    9. JS Armstrong & Fred Collopy, 2004. "Integration of Statistical Methods and Judgment for Time Series," General Economics and Teaching 0412024, University Library of Munich, Germany.
    10. Petropoulos, Fotios & Goodwin, Paul & Fildes, Robert, 2017. "Using a rolling training approach to improve judgmental extrapolations elicited from forecasters with technical knowledge," International Journal of Forecasting, Elsevier, vol. 33(1), pages 314-324.
    11. Thomson, Mary E. & Onkal-Atay, Dilek & Pollock, Andrew C. & Macaulay, Alex, 2003. "The influence of trend strength on directional probabilistic currency predictions," International Journal of Forecasting, Elsevier, vol. 19(2), pages 241-256.
    12. Belton, Valerie & Goodwin, Paul, 1996. "Remarks on the application of the analytic hierarchy process to judgmental forecasting," International Journal of Forecasting, Elsevier, vol. 12(1), pages 155-161, March.
    13. 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.
    14. 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.
    15. Reimers, Stian & Harvey, Nigel, 2011. "Sensitivity to autocorrelation in judgmental time series forecasting," International Journal of Forecasting, Elsevier, vol. 27(4), pages 1196-1214, October.
    16. Theocharis, Zoe & Harvey, Nigel, 2019. "When does more mean worse? Accuracy of judgmental forecasting is nonlinearly related to length of data series," Omega, Elsevier, vol. 87(C), pages 10-19.
    17. Wilkie-Thomson, Mary E. & Onkal-Atay, Dilek & Pollock, Andrew C., 1997. "Currency forecasting: an investigation of extrapolative judgement," International Journal of Forecasting, Elsevier, vol. 13(4), pages 509-526, December.
    18. Lawrence, Michael & Goodwin, Paul & O'Connor, Marcus & Onkal, Dilek, 2006. "Judgmental forecasting: A review of progress over the last 25 years," International Journal of Forecasting, Elsevier, vol. 22(3), pages 493-518.
    19. Larissa Koupriouchina & Jean-Pierre van der Rest & Zvi Schwartz, 2023. "Judgmental Adjustments of Algorithmic Hotel Occupancy Forecasts: Does User Override Frequency Impact Accuracy at Different Time Horizons?," Tourism Economics, , vol. 29(8), pages 2143-2164, December.
    20. Fischer, Ilan & Harvey, Nigel, 1999. "Combining forecasts: What information do judges need to outperform the simple average?," International Journal of Forecasting, Elsevier, vol. 15(3), pages 227-246, July.

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