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On the relative importance of linear model and human judge(s) in combined forecasting

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  • Seifert, Matthias
  • Hadida, Allègre L.
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    Abstract

    When and to what extent should forecasts rely on linear model or human judgment? The judgmental forecasting literature suggests that aggregating model and judge using a simple 50:50 split tends to outperform the two inputs alone. However, current research disregards the important role that the structure of the task, judges’ level of expertise, and the number of individuals providing a forecasting judgment may play. Ninety-two music industry professionals and 88 postgraduate students were recruited in a field experiment to predict chart entry positions of pop music singles in the UK and Germany. The results of a lens model analysis show how task structure and domain-specific expertise moderate the relative importance of model and judge. The study also delineates an upper boundary to which aggregating multiple judgments in model-expert combinations adds predictive accuracy. It is suggested that ignoring the characteristics of task and/or judge may lead to suboptimal forecasting performance.

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    File URL: http://www.sciencedirect.com/science/article/pii/S0749597812001021
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    Bibliographic Info

    Article provided by Elsevier in its journal Organizational Behavior and Human Decision Processes.

    Volume (Year): 120 (2013)
    Issue (Month): 1 ()
    Pages: 24-36

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    Handle: RePEc:eee:jobhdp:v:120:y:2013:i:1:p:24-36

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    Web page: http://www.elsevier.com/locate/obhdp

    Related research

    Keywords: Judgmental forecasting; Combined forecasts; Bootstrapping models; Music industry;

    References

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    1. Makridakis, Spyros & Chatfield, Chris & Hibon, Michele & Lawrence, Michael & Mills, Terence & Ord, Keith & Simmons, LeRoy F., 1993. "The M2-competition: A real-time judgmentally based forecasting study," International Journal of Forecasting, Elsevier, vol. 9(1), pages 5-22, April.
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    3. de Menezes, Lilian M. & W. Bunn, Derek & Taylor, James W., 2000. "Review of guidelines for the use of combined forecasts," European Journal of Operational Research, Elsevier, vol. 120(1), pages 190-204, January.
    4. Ashton, Robert H., 1986. "Combining the judgments of experts: How many and which ones?," Organizational Behavior and Human Decision Processes, Elsevier, vol. 38(3), pages 405-414, December.
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    6. Camerer, Colin & Weber, Martin, 1992. " Recent Developments in Modeling Preferences: Uncertainty and Ambiguity," Journal of Risk and Uncertainty, Springer, vol. 5(4), pages 325-70, October.
    7. Clemen, Robert T., 1989. "Combining forecasts: A review and annotated bibliography," International Journal of Forecasting, Elsevier, vol. 5(4), pages 559-583.
    8. Deng, Pi-Sheng, 1996. "Using case-based reasoning approach to the support of ill-structured decisions," European Journal of Operational Research, Elsevier, vol. 93(3), pages 511-521, September.
    9. 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.
    10. M. J. Lawrence & R. H. Edmundson & M. J. O'Connor, 1986. "The Accuracy of Combining Judgemental and Statistical Forecasts," Management Science, INFORMS, vol. 32(12), pages 1521-1532, December.
    11. Goodwin, Paul, 2000. "Correct or combine? Mechanically integrating judgmental forecasts with statistical methods," International Journal of Forecasting, Elsevier, vol. 16(2), pages 261-275.
    12. Stewart, Thomas R. & Roebber, Paul J. & Bosart, Lance F., 1997. "The Importance of the Task in Analyzing Expert Judgment," Organizational Behavior and Human Decision Processes, Elsevier, vol. 69(3), pages 205-219, March.
    13. Stephen J. Hoch & David A. Schkade, 1996. "A Psychological Approach to Decision Support Systems," Management Science, INFORMS, vol. 42(1), pages 51-64, January.
    14. Hoch, Stephen J, 1988. " Who Do We Know: Predicting the Interests and Opinions of the American Consumer," Journal of Consumer Research, University of Chicago Press, vol. 15(3), pages 315-24, December.
    15. Alexander, John C, Jr, 1995. "Refining the Degree of Earnings Surprise: A Comparison of Statistical and Analysts' Forecasts," The Financial Review, Eastern Finance Association, vol. 30(3), pages 469-506, August.
    16. Wood, Robert E., 1986. "Task complexity: Definition of the construct," Organizational Behavior and Human Decision Processes, Elsevier, vol. 37(1), pages 60-82, February.
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