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Psychological Heuristics for Making Inferences: Definition, Performance, and the Emerging Theory and Practice

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  • Konstantinos V. Katsikopoulos

    () (Center for Adaptive Behavior and Cognition, Max Planck Institute for Human Development, 14195 Berlin, Germany)

Abstract

Laypeople as well as professionals such as business managers and medical doctors often use psychological heuristics. Psychological heuristics are models for making inferences that (1) rely heavily on core human capacities (such as recognition, recall, or imitation); (2) do not necessarily use all available information and process the information they use by simple computations (such as lexicographic rules or aspiration levels); and (3) are easy to understand, apply, and explain. Psychological heuristics are a simple alternative to optimization models (where the optimum of a mathematical function that incorporates all available information is computed). I review studies in business, medicine, and psychology where computer simulations and mathematical analyses reveal conditions under which heuristics make better inferences than optimization and vice versa. The conditions involve concepts that refer to (i) the structure of the problem, (ii) the resources of the decision maker, or (iii) the properties of the models. I discuss open problems in the theoretical study of the concepts. Finally, I organize the current results tentatively in a tree for helping decision analysts decide whether to suggest heuristics or optimization to decision makers. I conclude by arguing for a multimethod, multidisciplinary approach to the theory and practice of inference and decision making.

Suggested Citation

  • Konstantinos V. Katsikopoulos, 2011. "Psychological Heuristics for Making Inferences: Definition, Performance, and the Emerging Theory and Practice," Decision Analysis, INFORMS, vol. 8(1), pages 10-29, March.
  • Handle: RePEc:inm:ordeca:v:8:y:2011:i:1:p:10-29
    DOI: 10.1287/deca.1100.0191
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    File URL: http://dx.doi.org/10.1287/deca.1100.0191
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    References listed on IDEAS

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    Cited by:

    1. Lutz Bornmann & Julian N. Marewski, 2019. "Heuristics as conceptual lens for understanding and studying the usage of bibliometrics in research evaluation," Scientometrics, Springer;Akadémiai Kiadó, vol. 120(2), pages 419-459, August.
    2. Karaliopoulos, Merkouris & Katsikopoulos, Konstantinos & Lambrinos, Lambros, 2017. "Bounded rationality can make parking search more efficient: The power of lexicographic heuristics," Transportation Research Part B: Methodological, Elsevier, vol. 101(C), pages 28-50.
    3. David Tucket & Antoine Mandel & Diana Mangalagiu & Allen Abramson & Jochen Hinkel & Konstantinos Katsikopoulos & Alan Kirman & Thierry Malleret & Igor Mozetic & Paul Ormerod & Robert Elliot Smith & To, 2015. "Uncertainty, Decision Science, and Policy Making: A Manifesto for a Research Agenda," PSE - Labex "OSE-Ouvrir la Science Economique" hal-02057279, HAL.
    4. Cinelli, Marco & Kadziński, Miłosz & Gonzalez, Michael & Słowiński, Roman, 2020. "How to support the application of multiple criteria decision analysis? Let us start with a comprehensive taxonomy," Omega, Elsevier, vol. 96(C).
    5. Katsikopoulos, Konstantinos V. & Durbach, Ian N. & Stewart, Theodor J., 2018. "When should we use simple decision models? A synthesis of various research strands," Omega, Elsevier, vol. 81(C), pages 17-25.
    6. Leighton Vaughan Williams & Ming‐Chien Sung & Peter A. F. Fraser‐Mackenzie & John Peirson & Johnnie E. V. Johnson, 2018. "Towards an Understanding of the Origins of the Favourite–Longshot Bias: Evidence from Online Poker Markets, a Real‐money Natural Laboratory," Economica, London School of Economics and Political Science, vol. 85(338), pages 360-382, April.
    7. L. Robin Keller & Ali Abbas & J. Eric Bickel & Vicki M. Bier & David V. Budescu & John C. Butler & Philippe Delquié & Kenneth C. Lichtendahl & Jason R. W. Merrick & Ahti Salo & George Wu, 2011. "From the Editors ---Probability Scoring Rules, Ambiguity, Multiattribute Terrorist Utility, and Sensitivity Analysis," Decision Analysis, INFORMS, vol. 8(4), pages 251-255, December.
    8. J. C. Hauff & A. Carlander & T. Gärling & G. Nicolini, 2020. "Retirement Financial Behaviour: How Important Is Being Financially Literate?," Journal of Consumer Policy, Springer, vol. 43(3), pages 543-564, September.
    9. L. Robin Keller, 2011. "Investment and Defense Strategies, Heuristics, and Games: From the Editor ..," Decision Analysis, INFORMS, vol. 8(1), pages 1-3, March.
    10. Konstantinos V. Katsikopoulos, 2013. "Why Do Simple Heuristics Perform Well in Choices with Binary Attributes?," Decision Analysis, INFORMS, vol. 10(4), pages 327-340, December.
    11. Gallice, Andrea, 2017. "An approximate solution to rent-seeking contests with private information," European Journal of Operational Research, Elsevier, vol. 256(2), pages 673-684.

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    Keywords

    inference; heuristics; medicine; optimization;

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