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

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  • 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)

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.

Suggested Citation

  • Thomas Åstebro & Samir Elhedhli, 2006. "The Effectiveness of Simple Decision Heuristics: Forecasting Commercial Success for Early-Stage Ventures," Management Science, INFORMS, vol. 52(3), pages 395-409, March.
  • Handle: RePEc:inm:ormnsc:v:52:y:2006:i:3:p:395-409
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    File URL: http://dx.doi.org/10.1287/mnsc.1050.0468
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    References listed on IDEAS

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    Cited by:

    1. repec:elg:eechap:15532_7 is not listed on IDEAS
    2. Erin L. Scott & Pian Shu & Roman M. Lubynsky, 2015. "Are “Better” Ideas More Likely to Succeed? An Empirical Analysis of Startup Evaluation," Harvard Business School Working Papers 16-013, Harvard Business School.
    3. Woike, Jan K. & Hoffrage, Ulrich & Petty, Jeffrey S., 2015. "Picking profitable investments: The success of equal weighting in simulated venture capitalist decision making," Journal of Business Research, Elsevier, vol. 68(8), pages 1705-1716.
    4. repec:eee:hepoli:v:121:y:2017:i:8:p:870-879 is not listed on IDEAS
    5. Schweisfurth, Tim & Zaggl, Michael A. & Schöttl, Claus P. & Raasch, Christina, 2017. "Hierarchical similarity biases in idea evaluation: A study in enterprise crowdfunding," Kiel Working Papers 2095, Kiel Institute for the World Economy (IfW).
    6. Andreas Ortmann & Leonidas Spiliopoulos, 2017. "The beauty of simplicity? (Simple) heuristics and the opportunities yet to be realized," Chapters,in: Handbook of Behavioural Economics and Smart Decision-Making, chapter 7, pages 119-136 Edward Elgar Publishing.
    7. Brighton, Henry & Gigerenzer, Gerd, 2015. "The bias bias," Journal of Business Research, Elsevier, vol. 68(8), pages 1772-1784.
    8. 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.
    9. Basel, Jörn S. & Brühl, Rolf, 2013. "Rationality and dual process models of reasoning in managerial cognition and decision making," European Management Journal, Elsevier, vol. 31(6), pages 745-754.
    10. Loock, Moritz & Hinnen, Gieri, 2015. "Heuristics in organizations: A review and a research agenda," Journal of Business Research, Elsevier, vol. 68(9), pages 2027-2036.
    11. Chan, C.S. Richard & Park, Haemin Dennis, 2015. "How images and color in business plans influence venture investment screening decisions," Journal of Business Venturing, Elsevier, vol. 30(5), pages 732-748.
    12. 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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