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2018 | 28 | 3 | 5-16

Article title

Analysis of complex decision problems based on cumulative prospect theory

Content

Title variants

Languages of publication

EN

Abstracts

EN
Complex risky decision problems involve sequences of decisions and random events. The choice at a given stage depends on the decisions taken in the previous stages, as well as on the realizations of the random events that occurred earlier. In the analysis of such situations, decision trees are used, and the criterion for choosing the optimal decision is to maximize the expected monetary value. Unfortunately, this approach often does not reflect the actual choices of individual decision makers. In descriptive decision theory, the criterion of maximizing the expected monetary value is replaced by a subjective valuation that takes into account the relative outcomes and their probabilities. This paper presents a proposal to use the principles of cumulative prospect theory to analyse complex decision problems. The concept of a certainty equivalent is used to make it possible to compare risky and non-risky alternatives.

Year

Volume

28

Issue

3

Pages

5-16

Physical description

Contributors

  • Department of Operations Research, University of Economics in Katowice, ul. 1 Maja 50, 40-287 Katowice, Poland

References

  • BIRNBAUM M.H., NAVARRETE J.B., Testing descriptive utility theories: violations of stochastic dominance and cumulative independence, J. Risk Uncert., 1998, 17, 49–78.
  • DUDZIŃSKA-BARYŁA R., Influence of a change in the reference point on the valuation of decisions based on prospect theory, [In:] J.B. Gajda, R. Jadczak (Eds.), Operations Research. Examples of Application, Wydawnictwo Uniwersytetu Łódzkiego, Łódź 2015, 43–56 (in Polish).
  • DUDZIŃSKA-BARYŁA R., KOPAŃSKA-BRÓDKA D., Maximum expected utility portfolios versus prospect theory approach, [In:] J. Hanclova (Ed.), Proceedings of the International Academic Conference on Increasing Competitiveness or Regional, National and International Markets, VSB-Technical University of Ostrava, Ostrava 2007 (available on CD).
  • FENNEMA H., WAKKER P., Original and cumulative prospect theory. A discussion and empirical differences, J. Beh. Dec. Making, 1997, 10, 53–64.
  • GONZALES R., WU G., On the shape of the probability weighting function, Cogn. Psych., 1999, 38, 129–166.
  • KAHNEMAN D., TVERSKY A., Prospect theory. An analysis of decision under risk, Econometrica, 1979, 47, 263–291.
  • KRITZMAN M., What practitioners need to know... about utility, Fin. An. J., 1992, 48 (3), 17–20.
  • PRELEC D., The probability weighting function, Econometrica, 1998, 66 (3), 497–527.
  • STOTT H.P., Cumulative prospect theory’s functional menagerie, J. Risk Uncert., 2006, 32, 101–130.
  • TVERSKY A., KAHNEMAN D., Advances in prospect theory: cumulative representation of uncertainty, J. Risk Uncert., 1992, 5, 297–323.
  • WU G., GONZALEZ R., Curvature of the probability weighting function, Manage. Sci., 1996, 42 (12), 1676–1690.
  • https://github.com/SilverDecisions/SilverDecisions/wiki/Gallery#city-promotion-decision-model (date of access: 02.11.2017)

Document Type

Publication order reference

Identifiers

YADDA identifier

bwmeta1.element.desklight-6e7d97ae-775c-439f-bc4d-b9bd093d6c91
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