An eye‐tracking study on information processing in risky decisions: Evidence for compensatory strategies based on automatic processes

Many everyday decisions have to be made under risk and can be interpreted as choices between gambles with different outcomes that are realized with specific probabilities. The underlying cognitive processes were investigated by testing six sets of hypotheses concerning choices, decision times, and information search derived from cumulative prospect theory, decision field theory, priority heuristic and parallel constraint satisfaction models. Our participants completed 40 decision tasks of two gambles with two non-negative outcomes each. Information search was recorded using eye-tracking technology. Results for choices, decision time, the amount of information searched for, fixation durations, the direction of the information search, and the distribution of fixations conflict with the prediction of the non-compensatory priority heuristic and indicate that individuals use compensatory strategies. Choice proportions are well in line with the predictions of cumulative prospect theory. Process measures indicate that individuals thereby do not rely on deliberate calculations of weighted sums. Information integration processes seem to be better explained by models that partially rely on automatic processes such as decision field theory or parallel constraint satisfaction models. Copyright © 2010 John Wiley & Sons, Ltd.

[1]  O. Svenson,et al.  Judgment and Decision Making Under Time Pressure , 1993 .

[2]  P. Hoffman The paramorphic representation of clinical judgment. , 1960, Psychological bulletin.

[3]  Boris M. Velichkovsky 7. From levels of processing to stratification of cognition: Converging evidence from three domains ofresearch , 1999 .

[4]  A. Tversky,et al.  Prospect theory: analysis of decision under risk , 1979 .

[5]  Michael Schulte-Mecklenbeck,et al.  Process Models Deserve Process Data: Comment on Brandstatter, Gigerenzer, and Hertwig (2006) , 2008, Psychological review.

[6]  Boris M. Velichkovsky,et al.  Towards an express-diagnostics for level of processing and hazard perception , 2002 .

[7]  T. Pearson,et al.  Direct comparison of the efficacy of intuitive and analytical cognition in expert judgment , 1987, IEEE Transactions on Systems, Man, and Cybernetics.

[8]  H. Ritter,et al.  Disambiguating Complex Visual Information: Towards Communication of Personal Views of a Scene , 1996, Perception.

[9]  S. Ayal,et al.  Ignorance or integration: the cognitive processes underlying choice behavior , 2009 .

[10]  B. Hilbig One-reason decision making in risky choice? A closer look at the priority heuristic , 2008 .

[11]  M. Birnbaum,et al.  Dimension integration: Testing models without trade-offs , 2008 .

[12]  Gerd Gigerenzer,et al.  Risky choice with heuristics: Reply to Birnbaum , Johnson, Schulte-Mecklenbeck, and Willemsen , and Rieger and Wang , 2008 .

[13]  Ulrich Hoffrage,et al.  When do people use simple heuristics, and how can we tell? , 1999 .

[14]  Ola Svenson,et al.  Judgment and decision making under time pressure: studies and findings , 1993 .

[15]  Thorstein Veblen,et al.  Why Economics is not an Evolutionary Science , 1898 .

[16]  Ola Svenson,et al.  Time pressure and stress in human judgment and decision making , 1993 .

[17]  Eric J. Johnson,et al.  The validity of verbal protocols , 1989, Memory & cognition.

[18]  Andreas Glöckner,et al.  Can We Trust Intuitive Jurors? An Experimental Analysis , 2008 .

[19]  P. Todd,et al.  Simple Heuristics That Make Us Smart , 1999 .

[20]  Kenneth L. Bernhardt Association For Consumer Research 1983 Presidential Address: ACR - Yesterday, Today, and Tomorrow , 1984 .

[21]  J. Townsend,et al.  Decision field theory: a dynamic-cognitive approach to decision making in an uncertain environment. , 1993, Psychological review.

[22]  S. Sloman Two systems of reasoning. , 2002 .

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

[24]  A. Maule,et al.  A componential investigation of the relation between structural modelling and cognitive accounts of human judgement. , 1994, Acta psychologica.

[25]  Robert S. Billings,et al.  Measures of compensatory and noncompensatory models of decision behavior: Process tracing versus policy capturing , 1983 .

[26]  Lee Roy Beach,et al.  Image theory: Principles, goals, and plans in decision making , 1987 .

[27]  Margaret G. Meloy,et al.  The goal of consistency as a cause of information distortion. , 2008, Journal of experimental psychology. General.

[28]  K. Rayner Eye movements in reading and information processing: 20 years of research. , 1998, Psychological bulletin.

[29]  Andreas Glöckner,et al.  Outcome-based strategy classification , 2010 .

[30]  Eric J. Johnson,et al.  Adaptive Strategy Selection in Decision Making. , 1988 .

[31]  L. Beach,et al.  “… Do i love thee? Let me count …” toward an understanding of intuitive and automatic decision making , 1990 .

[32]  Andreas Glöckner,et al.  How Distinct are Intuition and Deliberation? An Eye-Tracking Analysis of Instruction-Induced Decision Modes , 2009, Judgment and Decision Making.

[33]  Keith J. Holyoak,et al.  PSYCHOLOGICAL SCIENCE Research Article Construction of Preferences by Constraint Satisfaction , 2022 .

[34]  H. Montgomery,et al.  A think aloud study of dominance structuring in decision processes , 1989 .

[35]  A. Glöckner,et al.  Do People Make Decisions Under Risk Based on Ignorance? An Empirical Test of the Priority Heuristic Against Cumulative Prospect Theory , 2008 .

[36]  P. Thagard,et al.  Explanatory coherence , 1993 .

[37]  S. Read,et al.  The redux of cognitive consistency theories: evidence judgments by constraint satisfaction. , 2004, Journal of personality and social psychology.

[38]  N. Pennington,et al.  Explaining the evidence: Tests of the Story Model for juror decision making. , 1992 .

[39]  A. Tversky,et al.  The framing of decisions and the psychology of choice. , 1981, Science.

[40]  Daniel C. Krawczyk,et al.  (www.interscience.wiley.com) DOI: 10.1002/bdm.575 The Transience of Constructed Preferences , 2008 .

[41]  W. Rogers Regression standard errors in clustered samples , 1994 .

[42]  Eric,et al.  Effort and Accuracy in choice Technical C 14 , .

[43]  H. Raiffa,et al.  Games and Decisions: Introduction and Critical Survey. , 1958 .

[44]  J. Rieskamp The probabilistic nature of preferential choice. , 2008, Journal of experimental psychology. Learning, memory, and cognition.

[45]  M. Dekay,et al.  Distortion of Probability and Outcome Information in Risky Decisions. , 2009 .

[46]  Peter C. Fishburn,et al.  LEXICOGRAPHIC ORDERS, UTILITIES AND DECISION RULES: A SURVEY , 1974 .

[47]  A. Hayes,et al.  Using heteroskedasticity-consistent standard error estimators in OLS regression: An introduction and software implementation , 2007, Behavior research methods.

[48]  Gerd Gigerenzer,et al.  Risky choice with heuristics: reply to Birnbaum (2008), Johnson, Schulte-Mecklenbeck, and Willemsen (2008), and Rieger and Wang (2008). , 2008, Psychological review.

[49]  Andreas Glöckner,et al.  Modeling Option and Strategy Choices with Connectionist Networks: Towards an Integrative Model of Automatic and Deliberate Decision Making , 2008, Judgment and Decision Making.

[50]  A. K. Basu A Theory of Decision-Making , 1973, The Journal of Sociology & Social Welfare.

[51]  K. Holyoak,et al.  Bidirectional reasoning in decision making by constraint satisfaction , 1999 .

[52]  R. Luce Utility of Gains and Losses: Measurement-Theoretical and Experimental Approaches , 2000 .

[53]  H A Simon,et al.  How Big Is a Chunk? , 1974, Science.

[54]  Gerald L. Lohse,et al.  A Comparison of Two Process Tracing Methods for Choice Tasks , 1996 .

[55]  A. Glöckner,et al.  Coherence Shifts in Probabilistic Inference Tasks , 2009 .

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

[57]  Margaret G. Meloy,et al.  Predecisional Distortion of Product Information , 1998 .

[58]  Larry D. Rosen,et al.  An eye fixation analysis of multialternative choice , 1975, Memory & cognition.

[59]  P. Thagard,et al.  Inference to the best plan: A coherence theory of decision. , 1997 .

[60]  James L. McClelland,et al.  An interactive activation model of context effects in letter perception: I. An account of basic findings. , 1981 .

[61]  Boris M. Velichkovsky,et al.  Visual fixations and level of attentional processing , 2000, ETRA.

[62]  D. Kahneman,et al.  Representativeness revisited: Attribute substitution in intuitive judgment. , 2002 .

[63]  A. Tversky,et al.  Advances in prospect theory: Cumulative representation of uncertainty , 1992 .

[64]  B M Velichkovsky,et al.  [Working memory and work with memory: visual-spatial and further components of processing]. , 1995, Zeitschrift fur experimentelle Psychologie : Organ der Deutschen Gesellschaft fur Psychologie.

[65]  J. Edward Russo,et al.  Eye Fixations Can Save the World: a Critical Evaluation and a Comparison Between Eye Fixations and Other Information Processing Methodologies , 1978 .

[66]  R. Hertwig,et al.  The priority heuristic: making choices without trade-offs. , 2006, Psychological review.

[67]  Stephen E. Palmer Gestalt Theory , 2019, Theories and Applications of Counseling and Psychotherapy: Relevance Across Cultures and Settings.

[68]  Tilmann Betsch,et al.  Does Intuition Beat Fast and Frugal Heuristics? A Systematic Empirical Analysis , 2011 .

[69]  M. Birnbaum Evaluation of the priority heuristic as a descriptive model of risky decision making: comment on Brandstätter, Gigerenzer, and Hertwig (2006). , 2008, Psychological review.

[70]  A. Tversky,et al.  Prospect theory: an analysis of decision under risk — Source link , 2007 .

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

[72]  Robert L. Slonim,et al.  Combining a Theoretical Prediction with Experimental Evidence , 2002 .

[73]  Benjamin E. Hilbig,et al.  Ignorance- versus evidence-based decision making: a decision time analysis of the recognition heuristic. , 2009, Journal of experimental psychology. Learning, memory, and cognition.

[74]  Jerome R. Busemeyer,et al.  Computational Models of Decision Making , 2003 .

[75]  M. Birnbaum New tests of cumulative prospect theory and the priority heuristic: Probability-outcome tradeoff with branch splitting , 2008, Judgment and Decision Making.

[76]  A. Tversky Elimination by aspects: A theory of choice. , 1972 .