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Regions of rationality: Maps for bounded agents

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Abstract

An important problem in descriptive and prescriptive research in decision making is to identify “regions of rationality,” i.e., the areas for which heuristics are and are not effective. To map the contours of such regions, we derive probabilities that heuristics identify the best of m alternatives (m > 2) characterized by k attributes or cues (k > 1). The heuristics include a single variable (lexicographic), variations of elimination-by-aspects, equal weighting, hybrids of the preceding, and models exploiting dominance. We use twenty simulated and four empirical datasets for illustration. We further provide an overview by regressing heuristic performance on factors characterizing environments. Overall, “sensible” heuristics generally yield similar choices in many environments. However, selection of the appropriate heuristic can be important in some regions (e.g., if there is low inter-correlation among attributes/cues). Since our work assumes a “hit or miss” decision criterion, we conclude by outlining extensions for exploring the effects of different loss functions.

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  • Robin Hogarth & Natalia Karelaia, 2005. "Regions of rationality: Maps for bounded agents," Economics Working Papers 828, Department of Economics and Business, Universitat Pompeu Fabra, revised Mar 2006.
  • Handle: RePEc:upf:upfgen:828
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    1. Manel Baucells & Juan A. Carrasco & Robin M. Hogarth, 2008. "Cumulative Dominance and Heuristic Performance in Binary Multiattribute Choice," Operations Research, INFORMS, vol. 56(5), pages 1289-1304, October.
    2. Simon, Herbert A, 1978. "Rationality as Process and as Product of Thought," American Economic Review, American Economic Association, vol. 68(2), pages 1-16, May.
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    4. Chris Starmer, 2000. "Developments in Non-expected Utility Theory: The Hunt for a Descriptive Theory of Choice under Risk," Journal of Economic Literature, American Economic Association, vol. 38(2), pages 332-382, June.
    5. Robin M. Hogarth & Natalia Karelaia, 2005. "Simple Models for Multiattribute Choice with Many Alternatives: When It Does and Does Not Pay to Face Trade-offs with Binary Attributes," Management Science, INFORMS, vol. 51(12), pages 1860-1872, December.
    6. Robin Hogarth & Natalia Karelaia, 2004. "Ignoring information in binary choice with continuous variables: When is less 'more'?," Economics Working Papers 742, Department of Economics and Business, Universitat Pompeu Fabra, revised Oct 2004.
    7. John Conlisk, 1996. "Why Bounded Rationality?," Journal of Economic Literature, American Economic Association, vol. 34(2), pages 669-700, June.
    8. Camerer, Colin, 1998. "Bounded Rationality in Individual Decision Making," Working Papers 1029, California Institute of Technology, Division of the Humanities and Social Sciences.
    9. Daniel Kahneman, 2003. "Maps of Bounded Rationality: Psychology for Behavioral Economics," American Economic Review, American Economic Association, vol. 93(5), pages 1449-1475, December.
    10. Goldstein,William M. & Hogarth,Robin M. (ed.), 1997. "Research on Judgment and Decision Making," Cambridge Books, Cambridge University Press, number 9780521483346.
    11. Colin Camerer, 1998. "Bounded Rationality in Individual Decision Making," Experimental Economics, Springer;Economic Science Association, vol. 1(2), pages 163-183, September.
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    Cited by:

    1. Soyer, Emre & Hogarth, Robin M., 2015. "The golden rule of forecasting: Objections, refinements, and enhancements," Journal of Business Research, Elsevier, vol. 68(8), pages 1702-1704.
    2. Kristina Gavin Bigsby & Jeffrey W. Ohlmann & Kang Zhao, 2017. "Online and Off the Field: Predicting School Choice in College Football Recruiting from Social Media Data," Decision Analysis, INFORMS, vol. 14(4), pages 261-273, December.
    3. Manel Baucells & Juan A. Carrasco & Robin M. Hogarth, 2008. "Cumulative Dominance and Heuristic Performance in Binary Multiattribute Choice," Operations Research, INFORMS, vol. 56(5), pages 1289-1304, October.
    4. Clintin Davis-Stober, 2011. "A Geometric Analysis of When Fixed Weighting Schemes Will Outperform Ordinary Least Squares," Psychometrika, Springer;The Psychometric Society, vol. 76(4), pages 650-669, October.
    5. Berg, Nathan & Hoffrage, Ulrich, 2008. "Rational ignoring with unbounded cognitive capacity," Journal of Economic Psychology, Elsevier, vol. 29(6), pages 792-809, December.
    6. 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.
    7. L. Robin Keller, 2011. "Investment and Defense Strategies, Heuristics, and Games: From the Editor ..," Decision Analysis, INFORMS, vol. 8(1), pages 1-3, March.
    8. Pantelis P. Analytis & Amit Kothiyal & Konstantinos Katsikopoulos, 2014. "Multi-attribute utility models as cognitive search engines," Judgment and Decision Making, Society for Judgment and Decision Making, vol. 9(5), pages 403-419, September.

    More about this item

    Keywords

    Decision making; Bounded rationality; Lexicographic rules; Choice theory; Leex;

    JEL classification:

    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty
    • M10 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Business Administration - - - General

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