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Journal of Risk and Uncertainty

, Volume 34, Issue 2, pp 145–154 | Cite as

Dual process theories: A key for understanding the diversification bias?

  • Christoph Kogler
  • Anton Kühberger
Article

Abstract

The diversification bias in repeated lotteries is the finding that a majority of participants fail to select the option offering the highest probability. This phenomenon is systematic and immune to classical manipulations (e.g. monetary rewards). We apply dual process theories and argue that the diversification bias is a consequence of System 1 (automatic, intuitive, associative) triggering a matching response, which fails to be corrected by System 2 (intentional, analytic, rational). Empirically, supporting the corrective functions of System 2 through appropriate contextual cues (describing the task as a statistical test rather than as a lottery) led to a decrease of diversification.

Keywords

Dual process theories Diversification Probability matching Statistical independence 

JEL Classification

D83 D81 

References

  1. Arkes, Hal R., Robyn M. Dawes, and Caryn Christensen. (1986). “Factors Influencing the Use of a Decision Rule in a Probabilistic Task,” Organizational Behavior and Human Decision Processes 37, 93–110.CrossRefGoogle Scholar
  2. Baron, Jonathan, Leonardo Granato, Mark Spranca, and Eva Teubal. (1993). “Decision Making Biases in Children and Early Adolescents: Exploratory Studies,” Merril Palmer Quarterly 39, 23–47.Google Scholar
  3. Chaiken, Shelly, and Yaacov Trope (eds.). (1999). Dual-Process Theories in Social Psychology. New York: Guilford.Google Scholar
  4. Epstein, Seymour. (1994). “Integration of the Cognitive and Psychodynamic Unconscious,” American Psychologist 49, 709–724.CrossRefGoogle Scholar
  5. Estes, William K., and J. H. Straughan. (1954). “Analysis of a Verbal Conditioning Situation in Terms of Statistical Learning Theory,” Journal of Experimental Psychology 47, 225–234.CrossRefGoogle Scholar
  6. Fantino, Edmund, and Ali Esfandiari. (2002). “Probability Matching: Encouraging Optimal Responding in Humans,” Canadian Journal of Experimental Psychology 56, 58–63.Google Scholar
  7. Fisher, Wayne W., and James E. Mazur. (1997). “Basic and Applied Research on Choice Responding,” Journal of Applied Behavior Analysis 30, 387–410.CrossRefGoogle Scholar
  8. Friedman, Daniel, Dominic W. Massaro, Stephen Kitzis, and Michael Cohen. (1995). “A Comparison of Learning Models,” Journal of Mathematical Psychology 39, 164–178.CrossRefGoogle Scholar
  9. Gal, Ido, and Jonathan Baron. (1996). “Understanding Repeated Simple Choices,” Thinking and Reasoning 2, 81–98.CrossRefGoogle Scholar
  10. Gallistel, Charles R. (1990). The Organization of Learning. Cambridge, MA: MIT.Google Scholar
  11. Gilbert, Daniel T. (1989). “Thinking Lightly About Others: Automatic Components of the Social Inference Process.” In James Uleman and John A. Bargh (eds.), Unintended Thought (pp. 189–211). Englewood Cliffs, NJ: Prentice-Hall.Google Scholar
  12. Gilbert, Daniel T. (1999). “What the Mind’s Not.” In Shelly Chaiken and Yaacov Trope (eds.), Dual-process Theories in Social Psychology (pp. 3–11). New York: Guilford.Google Scholar
  13. Goel, Vinod, and Raymond Dolan. (2003). “Explaining Modulation of Reasoning by Belief,” Cognition 87, B11–B22.CrossRefGoogle Scholar
  14. Healy, Alice F., and Michael Kubovy. (1981). “Probability Matching and the Formation of Conservative Decision Rules in a Numerical Analog of Signal Detection,” Journal of Experimental Psychology: Human Learning and Memory 7, 344–354.CrossRefGoogle Scholar
  15. Herrnstein, R. J. (1961). “Relative and Absolute Strength of Response as a Function of Frequency of Reinforcement,” Journal of the Experimental Analysis of Behavior 4, 267–272.CrossRefGoogle Scholar
  16. Kacelnik, Alex, and Melissa Bateson. (1997). “Risk-sensitivity: Crossroads for Theories of Decision-making,” Trends in Cognitive Sciences 1, 304–309.CrossRefGoogle Scholar
  17. Kahneman, Daniel. (2003). “A Perspective on Judgement and Choice: Mapping Bounded Rationality,” American Psychologist 58, 697–720.CrossRefGoogle Scholar
  18. Kahneman, Daniel, and Shane Frederick. (2002). “Representativeness Revisited: Attribute Substitution in Intuitive Judgement.” In Thomas Gilovich, Dale Griffin, and Daniel Kahneman (eds.), Heuristics and Biases: The Psychology of Intuitive Judgment (pp. 49–81). New York: Cambridge University Press.Google Scholar
  19. Kogler, Christoph. (2006). “How Robust is the Diversification Bias? The Role of Dual Cognitive Process-theories in Multiple Decision Problems with Objective Probabilities.” Ph.D., University of Salzburg.Google Scholar
  20. Kogler, Christoph, and Anton Kühberger. (2006). “Dual Process Theories and the Diversification Bias.” In Bartosz Gula, Rainer Alexandrowizc, Sabine Strauß, Eva Brunner, Barbara Jenull-Schiefer, and Oliver Vitouch (eds.), Perspektiven psychologischer Forschung in Österreich (pp.62–70). Lengerich: Pabst.Google Scholar
  21. Loomes, Graham. (1998). “Probability vs. Money: A Test of Some Fundamental Assumptions about Rational Decision Making,” The Economic Journal 108, 477–489.CrossRefGoogle Scholar
  22. Myers, Jerome L., Jane G. Fort, Leonard Katz, and Mary M. Suydam. (1963). “Differential Memory Gains and Losses and Event Probability in a Two-choice Situation,” Journal of Experimental Psychology 66, 521–522.CrossRefGoogle Scholar
  23. Read, Daniel, and George Loewenstein. (1995). “Diversification Bias: Explaining the Discrepancy in Variety Seeking Between Combined and Separate Choices,” Journal of Experimental Psychology: Applied 1, 34–49.CrossRefGoogle Scholar
  24. Rohde, Catrin, Leda Cosmides, Wolfgang Hell, and John Tooby. (1999). “When and Why do People Avoid Unknown Probabilities in Decisions Under Uncertainty? Testing Some Predictions from Optimal Foraging Theory,” Cognition 72, 269–304.CrossRefGoogle Scholar
  25. Rubinstein, Ariel. (2002). “Irrational Diversification in Multiple Decision Problems,” European Economic Review 46, 1369–1378.CrossRefGoogle Scholar
  26. Shanks, David R., Richard J. Tunney, and John D. McCarthy. (2002). “A Re-examination of Probability Matching and Rational Choice,” Journal of Behavioral Decision Making 15, 233–250.CrossRefGoogle Scholar
  27. Simonson, Itmar. (1990). “The Effect of Purchase Quantity and Timing on Variety Seeking Behavior,” Journal of Marketing Research 32, 150–162.CrossRefGoogle Scholar
  28. Stanovich, Keith E., and Richard F. West. (2000). “Individual Differences in Reasoning: Implications for the Rationality Debate,” Behavioral and Brain Sciences 23, 645–726.CrossRefGoogle Scholar
  29. Stanovich, Keith E., and Richard F. West. (2002). “Individual Differences in Reasoning: Implications for the Rationality Debate?” In Thomas Gilovich, Dale W. Griffin, and Daniel Kahneman (eds.), Heuristics and Biases: The Psychology of Intuitive Judgment (pp. 421–440). New York: Cambridge University Press.Google Scholar
  30. Suppes, Patrick, and Richard C. Atkinson. (1960). Markov Learning Models for Multiperson Interactions. Stanford: Stanford University Press.Google Scholar
  31. Vulkan, Nir. (2000). “An Economist’s Perspective on Probability Matching,” Journal of Economic Surveys 14, 101–118.CrossRefGoogle Scholar
  32. West, Richard F., and Keith E. Stanovich. (2003). “Is Probability Matching Smart? Associations Between Probabilistic Choices and Cognitive Ability,” Memory & Cognition 31, 243–251.Google Scholar

Copyright information

© Springer Science+Business Media, LLC 2007

Authors and Affiliations

  1. 1.Department of PsychologyUniversity of SalzburgSalzburgAustria

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