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

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  • Sanders, N. R.
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    Abstract

    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.

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    Bibliographic Info

    Article provided by Elsevier in its journal Omega.

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

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    Handle: RePEc:eee:jomega:v:25:y:1997:i:2:p:135-144

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    Related research

    Keywords: judgmental forecasting time series forecasting feedback information value;

    References

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    1. 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.
    2. 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.
    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. 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.
    5. 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.
    6. Clemen, Robert T., 1989. "Combining forecasts: A review and annotated bibliography," International Journal of Forecasting, Elsevier, vol. 5(4), pages 559-583.
    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. Alison Hubbard Ashton & Robert H. Ashton, 1985. "Aggregating Subjective Forecasts: Some Empirical Results," Management Science, INFORMS, vol. 31(12), pages 1499-1508, December.
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    Cited by:
    1. Thomson, Mary E. & Pollock, Andrew C. & Gönül, M. Sinan & Önkal, Dilek, 2013. "Effects of trend strength and direction on performance and consistency in judgmental exchange rate forecasting," International Journal of Forecasting, Elsevier, vol. 29(2), pages 337-353.
    2. Van Swol, Lyn M., 2011. "Forecasting another's enjoyment versus giving the right answer: Trust, shared values, task effects, and confidence in improving the acceptance of advice," International Journal of Forecasting, Elsevier, vol. 27(1), pages 103-120, January.
    3. Becker, Otwin & Leitner, Johannes & Leopold-Wildburger, Ulrike, 2007. "Heuristic modeling of expectation formation in a complex experimental information environment," European Journal of Operational Research, Elsevier, vol. 176(2), pages 975-985, January.
    4. 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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