Remember Me
Or use your Academic/Social account:


Or use your Academic/Social account:


You have just completed your registration at OpenAire.

Before you can login to the site, you will need to activate your account. An e-mail will be sent to you with the proper instructions.


Please note that this site is currently undergoing Beta testing.
Any new content you create is not guaranteed to be present to the final version of the site upon release.

Thank you for your patience,
OpenAire Dev Team.

Close This Message


Verify Password:
Verify E-mail:
*All Fields Are Required.
Please Verify You Are Human:
fbtwitterlinkedinvimeoflicker grey 14rssslideshare1
Stewart, Neil (2011)
Publisher: Frontiers Research Foundation
Journal: Frontiers in Psychology
Languages: English
Types: Article
Subjects: Opinion Article, Psychology, BF
How is information integrated across the\ud attributes of an option when making risky\ud choices? In most descriptive models of\ud decision under risk, information about\ud risk, and reward is combined multiplicatively\ud (e.g., expected value; expected utility\ud theory, Bernouli, 1738/1954; subjective\ud expected utility theory, Savage, 1954;\ud Edwards, 1955; prospect theory, Kahneman\ud and Tversky, 1979; rank-dependent utility,\ud Quiggin, 1993; decision field theory,\ud Busemeyer and Townsend, 1993; transfer\ud of attention exchange model, Birnbaum,\ud 2008). That is, (some transform of) probability\ud is multiplied by (some transform of)\ud reward to give a value for a risky prospect,\ud and the prospect with the maximum value\ud is then chosen.
  • The results below are discovered through our pilot algorithms. Let us know how we are doing!

    • Anderson, N. H. (1981). Foundations of Information Integration Theory. New York: Academic Press.
    • Anderson, N. H., and Butzin, C. A. (1978). Integrationtheory applied to children's judgments of equity. Dev. Psychol. 14, 593-606.
    • Anderson, N. H., and Shanteau, J. C. (1970). Information integration in risky decision making. J. Exp. Psychol. 84, 441-451.
    • Bernouli, D. (1738/1954). Expositions of a new theory of the measurement of risk. Econometrica 22, 23-36.
    • Birnbaum,M.H.(2008).New paradoxes of risky decision making. Psychol. Rev. 115, 453-501.
    • Busemeyer, J. R., and Townsend, J. T. (1993). Decision eifld theory: a dynamic-cognitive approach to deci - sion making in an uncertain environment. Psychol. Rev. 100 432-459.
    • Dougherty, M. P. R., and Shanteau, J. (1999). Averaging expectancies and perceptual experiences in the assessment of quality. Acta Psychol. (Amst) 101, 49-67.
    • Edwards,W. (1955). The predictions of decisions among bets. J. Exp. Psychol. 50, 201-214.
    • Kahneman, D., and Tversky, A. (1979). Prospect theory: an analysis of decision under risk. Econometrica 47, 263-291.
    • Levin, I. R., Johnson, R. D., Russo, C. P., and Delden, P. J. (1985). Framing effects in judgment tasks with varying amounts of information. Organ. Behav. Hum. Decis. Process. 36, 362-377.
    • Massaro, D. W., and Friedman, D. (1990). Models of integration given multiple sources of information. Psychol. Rev. 97, 225-252.
    • Mellers, B. A., and Chang, S. (1994). Representations of risk judgments. Organ. Behav. Hum. Decis. Process. 57, 167-184.
    • Mellers, B. A., Chang, S. J., Birnbaum, M. H., and Ordóñez, L. D. (1992a). Preferences, prices, and ratings is risky decision-making. J. Exp. Psychol. Hum. Percept. Perform. 18, 347-361.
    • Mellers, B. A., Ordóñez, L. D., and Birnbaum, M. H. (1992b). A change-of-process theory for contextual effects and preference reversals in risky decision making. Organ. Behav. Hum. Decis. Process. 52, 331-369.
    • Mullet, E. (1992). The probability (utility rule in attractiveness judgments of positive gambles. Organ. Behav. Hum. Decis. Process. 52 246-255.
    • Oden, G. C., and Massaro, D. W. (1978). Integration of featural information in speech perception. Psychol. Rev. 85, 172-191.
    • Ordóñez, L. D., and Benson, L. (1997). Decisions under time pressure: how time constraint affects risky decision making.Organ.Behav.Hum.Decis.Process.71,121-140.
    • Quiggin, J. (1993). Generalized Expected Utility Theory: The Rank-Dependent Model. Norwell, MA: Kluwer Academic Publishers.
    • Rosenblatt, F. (1958). The perceptron: a probabilistic model for information storage and organization in the brain. Psychol. Rev. 65, 386-408.
    • Savage, L. J. (1954). The Foundations of Statistics. New York: Wiley.
    • Shanteau, J. (1974). Component processes in risky decision making. J. Exp. Psychol. 103, 680-691.
    • Shanteau, J. C., and Anderson, N. H. (1969). Test of a conflict model for preference judgment. J. Math. Psychol. 6, 312-325.
    • Sjöberg, L. (1968). Studies of the rated favorableness of offers to gamble. Scand. J. Psychol. 9, 257-273.
    • Stewart, N. (2009). Decision by sampling: the role of the decision environment in risky choice. Q. J. Exp. Psychol. 62, 1041-1062.
    • Stewart, N., Chater, N., and Brown, G. D. A. (2006). Decision by sampling. Cogn. Psychol. 53, 1-26.
    • Stewart, N., and Simpson, K. (2008). “A decisionby-sampling account of decision under risk,” in The Probabilistic Mind: Prospects for Bayesian Cognitive Science, eds L. N. Chater and M. Oaksford (Oxford, England: Oxford University Press), 261-276.
    • Troutman, C. M., and Shanteau, J. (1976). Do consumers evaluate products by adding or averaging attribute information? J. Consum. Res. 3, 101-106.
    • Tversky,A. (1967a). Utility theory and additivity analysis of risky choices. J. Exp. Psychol. 75, 27-36.
    • Tversky, A. (1967b). Additivity, utility, and subjective probability. J. Math. Psychol. 4, 175-201.
    • Wu, G., and Gonzalez, R. (1996). Curvature of the probability weighting function. Manage. Sci. 42, 1676-1690.
    • Zeisberger, S., Vrecko, D., and Langer, T. (2011). Measuring the time stability of prospect theory preferences. Theory Dec. doi: 10.1007/s11238-010-9234-3. [Epub ahead of print].
  • No related research data.
  • No similar publications.

Share - Bookmark

Cite this article