Selection of Decision Strategies After Conscious and Unconscious Thought

It is commonly assumed that the use of simple, non-compensatory strategies is especially pronounced in memory-based decisions, where information costs are high. At the same time, there is evidence that in memory-based decisions, a compensatory processing of attributes is facilitated when the processing occurs unconsciously rather than consciously. We applied a strategy classification approach—developed in research on non-compensatory heuristics—to test two key tenets of unconscious thought theory: the capacity principle and the weighting principle. Participants memorized attribute information about cars and were subsequently either directed to or diverted from thinking consciously about their preferences between the cars (conscious versus unconscious thought). Then, participants indicated in pair-wise choices which car they would prefer and were classified (based on their choices) as using either one of two compensatory strategies (equal weight or weighted additive) or a non-compensatory strategy (lexicographic heuristic). In line with the capacity principle, the number of participants best described by a compensatory strategy (the equal-weight strategy) tended to be higher after unconscious thought than after conscious thought, whereas the number of participants best described by the lexicographic heuristic tended to be lower. Inconsistent with the weighting principle, participants in the unconscious thought condition were better described by the equal-weight strategy than by the weighted-additive strategy. In Experiment 2, in which participants were not instructed to form an impression while learning the attribute information, the use of the equal-weight strategy was not more prevalent after unconscious thought. Copyright © 2013 John Wiley & Sons, Ltd.

[1]  Julian N. Marewski,et al.  Using the ACT-R architecture to specify 39 quantitative process models of decision making , 2011, Judgment and Decision Making.

[2]  H. Simon,et al.  A Behavioral Model of Rational Choice , 1955 .

[3]  Thorsten Pachur,et al.  Type of learning task impacts performance and strategy selection in decision making , 2012, Cognitive Psychology.

[4]  Davy Lerouge,et al.  Evaluating the benefits of distraction on product evaluations: The mindset effect , 2009 .

[5]  P. Todd,et al.  The Quest for Take The Best - Insights and Outlooks from Experimental Research , 2011 .

[6]  Claudia González-Vallejo,et al.  The Deliberation-Without-Attention Effect , 2009, Psychological science.

[7]  Gregory Ashby,et al.  A neuropsychological theory of multiple systems in category learning. , 1998, Psychological review.

[8]  Annika Wallin,et al.  From Meehl (1954) to fast and frugal heuristics (and back): new insights into how to bridge the clinical–actuarial divide. , 2008 .

[9]  A. Glöckner,et al.  Multiple-reason decision making based on automatic processing. , 2008, Journal of experimental psychology. Learning, memory, and cognition.

[10]  A. Dijksterhuis,et al.  Introduction: Still Thinking Different , 2011 .

[11]  Thorsten Pachur,et al.  Memory-based Decision-making with Heuristics: Evidence for a Controlled Activation of Memory Representations , 2011, Journal of Cognitive Neuroscience.

[12]  G. Wallas The art of thought , 1926 .

[13]  Arnaud Rey,et al.  Does unconscious thought improve complex decision making? , 2009, Psychological research.

[14]  A. Dijksterhuis,et al.  A Theory of Unconscious Thought , 2006, Perspectives on psychological science : a journal of the Association for Psychological Science.

[15]  Julian N. Marewski,et al.  Cognitive niches: an ecological model of strategy selection. , 2011, Psychological review.

[16]  Rick B. van Baaren,et al.  Predicting Soccer Matches After Unconscious and Conscious Thought as a Function of Expertise , 2009, Psychological science.

[17]  F. James Rohlf,et al.  Biometry: The Principles and Practice of Statistics in Biological Research , 1969 .

[18]  D. C. Howell Statistical Methods for Psychology , 1987 .

[19]  Matthew J. Lindberg,et al.  “Save Angels Perhaps”: A Critical Examination of Unconscious Thought Theory and the Deliberation-Without-Attention Effect , 2008 .

[20]  A. Bröder,et al.  Take the best versus simultaneous feature matching: probabilistic inferences from memory and effects of representation format. , 2003, Journal of experimental psychology. General.

[21]  Maarten W. Bos,et al.  A Meta-Analysis on Unconscious Thought Effects , 2011 .

[22]  J. Rieskamp,et al.  SSL: a theory of how people learn to select strategies. , 2006, Journal of experimental psychology. General.

[23]  Madelijn Strick,et al.  Unconscious-Thought Effects Take Place Off-Line, Not On-Line , 2010, Psychological science.

[24]  John W. Payne,et al.  The adaptive decision maker: Name index , 1993 .

[25]  Sian L. Beilock,et al.  On the fragility of skilled performance: what governs choking under pressure? , 2001, Journal of experimental psychology. General.

[26]  Rick B. van Baaren,et al.  On Making the Right Choice: The Deliberation-Without-Attention Effect , 2006, Science.

[27]  Mary Frances Luce,et al.  Boundary Conditions on Unconscious Thought in Complex Decision Making , 2008, Psychological science.

[28]  Arndt Bröder,et al.  Bayesian strategy assessment in multi‐attribute decision making , 2003 .

[29]  Ruud Wetzels,et al.  Four empirical tests of unconscious thought theory , 2012 .

[30]  Edgar Erdfelder,et al.  GPOWER: A general power analysis program , 1996 .

[31]  N. Srinivasan,et al.  Attribute preference and selection in multi-attribute decision making: Implications for unconscious and conscious thought , 2010, Consciousness and Cognition.

[32]  R. Hertwig,et al.  Heuristics: The Foundations of Adaptive Behavior , 2015 .

[33]  Eric J. Johnson,et al.  The adaptive decision maker , 1993 .

[34]  M. F. Luce,et al.  Correlation, conflict, and choice. , 1993 .

[35]  Tim Rakow,et al.  Please Scroll down for Article the Quarterly Journal of Experimental Psychology Think, Blink or Sleep on It? the Impact of Modes of Thought on Complex Decision Making , 2022 .

[36]  Thorsten Pachur,et al.  Recognition-based inference: When is less more in the real world? , 2010, Psychonomic bulletin & review.

[37]  W. Gaissmaier,et al.  Sequential processing of cues in memory-based multiattribute decisions , 2007, Psychonomic bulletin & review.

[38]  G Gigerenzer,et al.  Reasoning the fast and frugal way: models of bounded rationality. , 1996, Psychological review.

[39]  K. Bühler,et al.  Tatsachen und Probleme zu einer Psychologie der Denkvorgänge: I Über Gedanken , 1907 .

[40]  Julian N. Marewski,et al.  The recognition heuristic in memory‐based inference: is recognition a non‐compensatory cue? , 2008 .

[41]  Felix Acker New findings on unconscious versus conscious thought in decision making: additional empirical data and meta-analysis. , 2008, Judgment and Decision Making.

[42]  Sanjoy Ghose,et al.  When Choice Models Fail: Compensatory Models in Negatively Correlated Environments , 1989 .

[43]  R. Dawes Judgment under uncertainty: The robust beauty of improper linear models in decision making , 1979 .

[44]  Wasserman,et al.  Bayesian Model Selection and Model Averaging. , 2000, Journal of mathematical psychology.

[45]  Ut Na Sio,et al.  Does incubation enhance problem solving? A meta-analytic review. , 2009, Psychological bulletin.

[46]  Ben R. Newell,et al.  Revising Beliefs about the Merit of Unconscious Thought: Evidence in Favor of the Null Hypothesis , 2011 .

[47]  M. Coltheart,et al.  358,534 nonwords: The ARC Nonword Database , 2002, The Quarterly journal of experimental psychology. A, Human experimental psychology.