IDEAS home Printed from https://ideas.repec.org/a/eee/jomega/v22y1994i6p553-568.html
   My bibliography  Save this article

Heuristics, biases and improvement strategies in judgmental time series forecasting

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/0305-0483(94)90047-7
    Download Restriction: Full text for ScienceDirect subscribers only
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    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. 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.
    3. 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.
    4. 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.
    5. 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.
    6. 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.
    7. 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.
    8. 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.
    9. 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.
    10. 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.
    11. 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.
    12. Goodwin, P., 1996. "Statistical correction of judgmental point forecasts and decisions," Omega, Elsevier, vol. 24(5), pages 551-559, October.
    13. 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.
    14. JS Armstrong & Fred Collopy, 2004. "Integration of Statistical Methods and Judgment for Time Series," General Economics and Teaching 0412024, University Library of Munich, Germany.
    15. 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.
    16. 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.
    17. 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.
    18. 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.
    19. 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.
    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.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:jomega:v:22:y:1994:i:6:p:553-568. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/375/description#description .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.