IDEAS home Printed from https://ideas.repec.org/
MyIDEAS: Login to save this article or follow this journal

The impact of task properties feedback on time series judgmental forecasting tasks

  • Sanders, N. R.
Registered author(s):

    This study evaluates the impact of task properties feedback on the time series forecast accuracy of four different judgmental forecasting processes. Specifically, we test the impact of providing information on time series data patterns amd degree of noise level to knowledgeable subjects to interpret this information. Ninety eight subjects were used as the source of the individual and three-person group forecasts for eight artificial time series with varying patterns and noise levels. Our findings show that such task properties feedback leads to improvements in forecast accuracy for all forecasting processes tested, particularly for high noise series. This is true for both individual and group judgmental forecasting processes, as well as combination forecasts. These findings have important implications for business practitioners who continue to rely on judgmental forecasting processes. The information provided to subjects in our study is such that it could readily be obtained as output from most statistical software packages. Our findings imply that all judgmental forecasting processes could benefit by relying on this type of cognitive aid as an input to their judgments.

    If you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.

    File URL: http://www.sciencedirect.com/science/article/B6VC4-3SWVJ58-1/2/3c0307a44a0c53537c24f39b4fc5057d
    Download Restriction: Full text for ScienceDirect subscribers only

    As the access to this document is restricted, you may want to look for a different version under "Related research" (further below) or search for a different version of it.

    Article provided by Elsevier in its journal Omega.

    Volume (Year): 25 (1997)
    Issue (Month): 2 (April)
    Pages: 135-144

    as
    in new window

    Handle: RePEc:eee:jomega:v:25:y:1997:i:2:p:135-144
    Contact details of provider: Web page: http://www.elsevier.com/wps/find/journaldescription.cws_home/375/description#description

    Order Information: Postal: http://www.elsevier.com/wps/find/supportfaq.cws_home/regional
    Web: https://shop.elsevier.com/order?id=375&ref=375_01_ooc_1&version=01

    References listed on IDEAS
    Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:

    as in new window
    1. Lawrence, Michael J. & Edmundson, Robert H. & O'Connor, Marcus J., 1985. "An examination of the accuracy of judgmental extrapolation of time series," International Journal of Forecasting, Elsevier, vol. 1(1), pages 25-35.
    2. Goodwin, Paul & Wright, George, 1993. "Improving judgmental time series forecasting: A review of the guidance provided by research," International Journal of Forecasting, Elsevier, vol. 9(2), pages 147-161, August.
    3. Fred Collopy & JS Armstrong, 2004. "Rule-Based Forecasting: Development and Validation of an Expert Systems Approach to Combining Time Series Extrapolations," General Economics and Teaching 0412004, EconWPA.
    4. Alison Hubbard Ashton & Robert H. Ashton, 1985. "Aggregating Subjective Forecasts: Some Empirical Results," Management Science, INFORMS, vol. 31(12), pages 1499-1508, December.
    5. Robert C. Blattberg & Stephen J. Hoch, 1990. "Database Models and Managerial Intuition: 50% Model + 50% Manager," Management Science, INFORMS, vol. 36(8), pages 887-899, August.
    6. Benson, P. George & Onkal, Dilek, 1992. "The effects of feedback and training on the performance of probability forecasters," International Journal of Forecasting, Elsevier, vol. 8(4), pages 559-573, December.
    7. Ang, Soon & O'Connor, Marcus, 1991. "The effect of group interaction processes on performance in time series extrapolation," International Journal of Forecasting, Elsevier, vol. 7(2), pages 141-149, August.
    8. Remus, William & O'Conner, Marcus & Griggs, Kenneth, 1996. "Does Feedback Improve the Accuracy of Recurrent Judgmental Forecasts?," Organizational Behavior and Human Decision Processes, Elsevier, vol. 66(1), pages 22-30, April.
    9. Clemen, Robert T., 1989. "Combining forecasts: A review and annotated bibliography," International Journal of Forecasting, Elsevier, vol. 5(4), pages 559-583.
    Full references (including those not matched with items on IDEAS)

    This item is not listed on Wikipedia, on a reading list or among the top items on IDEAS.

    When requesting a correction, please mention this item's handle: RePEc:eee:jomega:v:25:y:1997:i:2:p:135-144. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Zhang, Lei)

    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.

    If references are entirely missing, you can add them using this form.

    If the full references list an item that is present in RePEc, but the system did not link to it, you can help with 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 profile, as there may be some citations waiting for confirmation.

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

    This information is provided to you by IDEAS at the Research Division of the Federal Reserve Bank of St. Louis using RePEc data.