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Overcoming Ineffective Mental Representations in Base-Rate Problems

Author

Listed:
  • Marie Christine Roy

    (Faculté des Sciences de L'Administration, Université Laval, Québec, Canada G1K 7P4)

  • F. Javier Lerch

    (Graduate School of Industrial Administration, Carnegie Mellon University, Pittsburgh, Pennsylvania 15213)

Abstract

Many biases have been observed in probabilistic reasoning, hindering the ability to follow normative rules in decision-making contexts involving uncertainty. One systematic error people make is to neglect base rates in situations where prior beliefs in a hypothesis should be taken into account when new evidence is obtained. Incomplete explanations for the phenomenon have impeded the development of effective debiasing procedures or tools to support decision making in this area. In this research, we show that the main reason behind these judgment errors is the causal representation induced by the problem context. In two experiments we demonstrate that people often possess the appropriate decision rules but are unable to apply them correctly because they have an ineffective causal mental representation. We also show how this mental representation may be modified when a graph is used instead of a problem narrative. This new understanding should contribute to the design of better decision aids to overcome this bias.

Suggested Citation

  • Marie Christine Roy & F. Javier Lerch, 1996. "Overcoming Ineffective Mental Representations in Base-Rate Problems," Information Systems Research, INFORMS, vol. 7(2), pages 233-247, June.
  • Handle: RePEc:inm:orisre:v:7:y:1996:i:2:p:233-247
    DOI: 10.1287/isre.7.2.233
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    Cited by:

    1. Philipp N. Herrmann & Dennis O. Kundisch & Mohammad S. Rahman, 2015. "Beating Irrationality: Does Delegating to IT Alleviate the Sunk Cost Effect?," Management Science, INFORMS, vol. 61(4), pages 831-850, April.
    2. Daniel J. Benjamin, 2018. "Errors in Probabilistic Reasoning and Judgment Biases," NBER Working Papers 25200, National Bureau of Economic Research, Inc.
    3. Kai H. Lim & Izak Benbasat & Lawrence M. Ward, 2000. "The Role of Multimedia in Changing First Impression Bias," Information Systems Research, INFORMS, vol. 11(2), pages 115-136, June.
    4. Yigitbasioglu, Ogan M. & Velcu, Oana, 2012. "A review of dashboards in performance management: Implications for design and research," International Journal of Accounting Information Systems, Elsevier, vol. 13(1), pages 41-59.
    5. Klein, Barbara D., 2001. "Detecting errors in data: clarification of the impact of base rate expectations and incentives," Omega, Elsevier, vol. 29(5), pages 391-404, October.

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