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The Effectiveness of Simple Decision Heuristics: Forecasting Commercial Success for Early-Stage Ventures

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Author Info

  • Thomas Åstebro

    ()
    (Joseph L. Rotman School of Management, University of Toronto, 105 St. George Street, Toronto, Ontario M5S 3E6, Canada)

  • Samir Elhedhli

    ()
    (Department of Management Sciences, University of Waterloo, Waterloo, Ontario N2L 3G1, Canada)

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    Abstract

    We investigate the decision heuristics used by experts to forecast that early-stage ventures are subsequently commercialized. Experts evaluate 37 project characteristics and subjectively combine data on all cues by examining both critical flaws and positive factors to arrive at a forecast. A conjunctive model is used to describe their process, which sums "good" and "bad" cue counts separately. This model achieves a 91.8% forecasting accuracy of the experts' correct forecasts. The model correctly predicts 86.0% of outcomes in out-of-sample, out-of-time tests. Results indicate that reasonably simple decision heuristics can perform well in a natural and very difficult decision-making context.

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    File URL: http://dx.doi.org/10.1287/mnsc.1050.0468
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    Bibliographic Info

    Article provided by INFORMS in its journal Management Science.

    Volume (Year): 52 (2006)
    Issue (Month): 3 (March)
    Pages: 395-409

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    Handle: RePEc:inm:ormnsc:v:52:y:2006:i:3:p:395-409

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    Related research

    Keywords: judgment; heuristic; forecast; decision making; statistical prediction; early-stage ventures;

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    Cited by:
    1. Fildes, Robert & Goodwin, Paul & Lawrence, Michael & Nikolopoulos, Konstantinos, 2009. "Effective forecasting and judgmental adjustments: an empirical evaluation and strategies for improvement in supply-chain planning," International Journal of Forecasting, Elsevier, vol. 25(1), pages 3-23.
    2. Åstebro, Thomas & Thompson, Peter, 2011. "Entrepreneurs, Jacks of all trades or Hobos?," Research Policy, Elsevier, vol. 40(5), pages 637-649, June.
    3. Du, Juan & Chen, Chien-Ming & Chen, Yao & Cook, Wade D. & Zhu, Joe, 2012. "Additive super-efficiency in integer-valued data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 218(1), pages 186-192.

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