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Provider-user differences in perceived usefulness of forecasting formats

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  • Önkal, Dilek
  • Bolger, Fergus

Abstract

This paper aims to examine potential differences in perceived usefulness of various forecasting formats from the perspectives of providers and users of predictions. Experimental procedure consists of asking participants to assume the role of forecast providers and to construct forecasts using different formats, followed by requesting usefulness ratings for these formats (Phase 1). Usefulness of the formats are rated again in hindsight after receiving individualized performance feedback (Phase 2). In the ensuing role switch exercise, given new series and external predictions, participants are required to assign usefulness ratings as forecast users (Phase 3). In the last phase, participants are given performance feedback and asked to rate the usefulness in hindsight as users of predictions (Phase 4). Results reveal that regardless of the forecasting role, 95% prediction intervals are considered to be the most useful format, followed by directional predictions, 50% interval forecasts, and lastly, point forecasts. Finally, for all formats and for both roles, usefulness in hindsight is found to be lower than usefulness prior to performance feedback presentation.

Suggested Citation

  • Önkal, Dilek & Bolger, Fergus, 2004. "Provider-user differences in perceived usefulness of forecasting formats," Omega, Elsevier, vol. 32(1), pages 31-39, February.
  • Handle: RePEc:eee:jomega:v:32:y:2004:i:1:p:31-39
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    References listed on IDEAS

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    1. Dalrymple, Douglas J., 1975. "Sales forecasting methods and accuracy," Business Horizons, Elsevier, vol. 18(6), pages 69-73, December.
    2. Fischhoff, Baruch, 1994. "What forecasts (seem to) mean," International Journal of Forecasting, Elsevier, vol. 10(3), pages 387-403, November.
    3. Goodwin, P., 1996. "Statistical correction of judgmental point forecasts and decisions," Omega, Elsevier, vol. 24(5), pages 551-559, October.
    4. Mahmoud, Essam & DeRoeck, Richard & Brown, Robert & Rice, Gillian, 1992. "Bridging the gap between theory and practice in forecasting," International Journal of Forecasting, Elsevier, vol. 8(2), pages 251-267, October.
    5. Tversky, Amos & Kahneman, Daniel, 1986. "Rational Choice and the Framing of Decisions," The Journal of Business, University of Chicago Press, vol. 59(4), pages 251-278, October.
    6. Goodwin, Paul, 2002. "Integrating management judgment and statistical methods to improve short-term forecasts," Omega, Elsevier, vol. 30(2), pages 127-135, April.
    7. Dalrymple, Douglas J., 1987. "Sales forecasting practices: Results from a United States survey," International Journal of Forecasting, Elsevier, vol. 3(3-4), pages 379-391.
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    Cited by:

    1. Du, Ning & Budescu, David V., 2007. "Does past volatility affect investors' price forecasts and confidence judgements?," International Journal of Forecasting, Elsevier, vol. 23(3), pages 497-511.
    2. Goodwin, Paul & Önkal, Dilek & Thomson, Mary, 2010. "Do forecasts expressed as prediction intervals improve production planning decisions?," European Journal of Operational Research, Elsevier, vol. 205(1), pages 195-201, August.
    3. 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.

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