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Regions of Rationality: Maps for bounded agents

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  • Robin Hogarth
  • Natalia Karelaia

Abstract

An important problem in descriptive and prescriptive research in decision making is to identify "regions of rationality," i.e., the areas for which simple, heuristic models are and are not effective. To map the contours of such regions, we derive probabilities that models identify the best of m alternatives (m >= 2) characterized by k attributes (k >= 1). The models include a single variable (lexicographic), variations of elimination-by-aspects, equal weighting, hybrids of the preceding, and models exploiting dominance. We compare all with multiple regression. We illustrate the theory with twenty simulated and four empirical datasets. Fits between predictions and realizations are excellent. However, the terrain mapped by our work is complex and no single model is "best". We further provide an overview by regressing the performance of the different models on factors characterizing environments. We conclude by outlining how our work can be extended to exploring the effects of different loss functions as well as suggesting further topics for future research.

Suggested Citation

  • Robin Hogarth & Natalia Karelaia, 2005. "Regions of Rationality: Maps for bounded agents," Working Papers 269, Barcelona School of Economics.
  • Handle: RePEc:bge:wpaper:269
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    References listed on IDEAS

    as
    1. 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.
    2. 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.
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    8. Laura Martignon & Ulrich Hoffrage, 2002. "Fast, frugal, and fit: Simple heuristics for paired comparison," Theory and Decision, Springer, vol. 52(1), pages 29-71, February.
    9. Robin Hogarth & Natalia Karelaia, 2003. "Take-the-best and other simple strategies: Why and when they work 'well' in binary choice," Economics Working Papers 709, Department of Economics and Business, Universitat Pompeu Fabra.
    10. Goldstein,William M. & Hogarth,Robin M. (ed.), 1997. "Research on Judgment and Decision Making," Cambridge Books, Cambridge University Press, number 9780521483346, September.
    11. Karelaia, Natalia, 2006. "Thirst for confirmation in multi-attribute choice: Does search for consistency impair decision performance?," Organizational Behavior and Human Decision Processes, Elsevier, vol. 100(1), pages 128-143, May.
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    Citations

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    Cited by:

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    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. L. Robin Keller, 2011. "Investment and Defense Strategies, Heuristics, and Games: From the Editor ..," Decision Analysis, INFORMS, vol. 8(1), pages 1-3, March.
    5. Marc Jekel & Andreas Glockner & Arndt Broder & Viktoriya Maydych, 2014. "Approximating rationality under incomplete information: Adaptive inferences for missing cue values based on cue-discrimination," Judgment and Decision Making, Society for Judgment and Decision Making, vol. 9(2), pages 129-147, March.
    6. 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.
    7. 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.
    8. 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.
    9. 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.
    10. repec:cup:judgdm:v:9:y:2014:i:5:p:403-419 is not listed on IDEAS
    11. Berg, Nathan & Hoffrage, Ulrich, 2008. "Rational ignoring with unbounded cognitive capacity," Journal of Economic Psychology, Elsevier, vol. 29(6), pages 792-809, December.
    12. 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.

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    More about this item

    Keywords

    decision making; bounded rationality; Lexicographic rules; Choice theory;
    All these keywords.

    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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