On heuristic and linear models of judgment: Mapping the demand for knowledge
AbstractResearch on judgment and decision making presents a confusing picture of human abilities. For example, much research has emphasized the dysfunctional aspects of judgmental heuristics, and yet, other findings suggest that these can be highly effective. A further line of research has modeled judgment as resulting from “as if” linear models. This paper illuminates the distinctions in these approaches by providing a common analytical framework based on the central theoretical premise that understanding human performance requires specifying how characteristics of the decision rules people use interact with the demands of the tasks they face. Our work synthesizes the analytical tools of “lens model” research with novel methodology developed to specify the effectiveness of heuristics in different environments and allows direct comparisons between the different approaches. We illustrate with both theoretical analyses and simulations. We further link our results to the empirical literature by a meta-analysis of lens model studies and estimate both human and heuristic performance in the same tasks. Our results highlight the trade-off between linear models and heuristics. Whereas the former are cognitively demanding, the latter are simple to use. However, they require knowledge – and thus “maps” – of when and which heuristic to employ.
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Bibliographic InfoPaper provided by Department of Economics and Business, Universitat Pompeu Fabra in its series Economics Working Papers with number 974.
Date of creation: Jun 2006
Date of revision:
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Web page: http://www.econ.upf.edu/
Decision making; heuristics; linear models; lens model; judgmental biases;
Find related papers by JEL classification:
- D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty
- M10 - Business Administration and Business Economics; Marketing; Accounting - - Business Administration - - - General
This paper has been announced in the following NEP Reports:
- NEP-KNM-2006-10-21 (Knowledge Management & Knowledge Economy)
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- 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.
- Manel Baucells & Juan A. Carrasco & Robin Hogarth, 2005.
"Cumulative dominance and heuristic performance in binary multi-attribute choice,"
Economics Working Papers
895, Department of Economics and Business, Universitat Pompeu Fabra.
- Baucells Alibés Manel & Carrasco López Juan Antonio, 2006. "Cumulative Dominance and Heuristic Performance in Binary Multi - Attribute Choice," Working Papers 201047, Fundacion BBVA / BBVA Foundation.
- Robin Hogarth & Natalia Karelaia, 2004. "Simple models for multi-attribute choice with many alternatives: When it does and does not pay to face tradeoffs with binary attributes," Economics Working Papers 739, Department of Economics and Business, Universitat Pompeu Fabra, revised Apr 2005.
- Rothstein, Howard G., 1986. "The effects of time pressure on judgment in multiple cue probability learning," Organizational Behavior and Human Decision Processes, Elsevier, vol. 37(1), pages 83-92, February.
- David Leiser & Dov-Ron Schatzberg, 2008. "On the complexity of traffic judges' decisions," Judgment and Decision Making, Society for Judgment and Decision Making, vol. 3(8), pages 667-678, December.
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