Skip to main content
Log in

Using ELECTRE to analyse the behaviour of economic agents

  • Focus
  • Published:
Soft Computing Aims and scope Submit manuscript

Abstract

According to behavioural finance, economic agents display cognitive bias, heuristics and emotional factors that generate preferences which systematically violate the rationality assumptions of the normative model of classical decision theory. Rather than maximizing the expected utility, representing the optimal choice, they attempt to accept a satisfactory solution. Morton and Fasolo (J Oper Res Soc 60:268–275, 2009) outlined some behavioural findings relevant to the practice of multicriteria approach. In this paper, we propose a multicriteria model for analysing some experiments proposed by Kahneman and Tversky (Econometrica 47:263–29 l, 1979). Our aim is to verify whether a multicriteria tool reduces or minimizes cognitive biases. We focus on ELECTRE due to its main features: it accepts the violation of some mathematical axioms. By a simulation study, we represent a set of prospects by means of decision matrices: the prospects are considered as alternatives, the events as criteria, the probabilities of events as the weights assigned to criteria. Then, we apply ELECTRE to verify whether the preference ranking among the alternatives confirms the results obtained by Kahneman–Tversky, that is, whether it is able to describe the emotional behaviours of economic agents.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1

Similar content being viewed by others

References

  • Allais M (1953) Le Comportement de l’Homme Rationnel devant le Risque: Critique des Postulats et Axiomes de l’Ecole Americaine. Econometrica 21(4):503–546

    Article  MathSciNet  Google Scholar 

  • Anscombe FJ, Aumann R (1963) Definition of subjective probability. Ann Math Stat 34(1):199–205

    Article  MathSciNet  Google Scholar 

  • Ellsberg D (1961) Risk, ambiguity and savage axioms. Q J Econ 75(4):643–669

    Article  MathSciNet  Google Scholar 

  • Ferretti R, Rubaltelli E, Rumiati R (2011) La mente finanziaria. Economia e psicologia al servizio dell’investitore. Il Mulino, Fiesole, pp 1–310

    Google Scholar 

  • Figueira J, Roy B (2002) Determining the weights of criteria in the ELECTRE type methods with a revised Simos’ procedure. Eur J Oper Res 139:317–326

    Article  Google Scholar 

  • Figueira J, Greco S, Slowinski R (2009) Building a set of additive value functions representing a reference preorder and intensities of preference: GRIP method. Eur J Oper Res 195(2):460–486

    Article  MathSciNet  Google Scholar 

  • Ishizaka A, Nemery P (2013) Multi-criteria decision analysis methods and software. Wiley, New York

    Book  Google Scholar 

  • Kahneman D, Tversky A (1979) Prospect theory: an analysis of decision under risk. Econometrica 47:263–291

    Article  MathSciNet  Google Scholar 

  • Kahneman D, Tversky A (1986) Rational choice and the framing of decisions. J Bus 59(4):251–278

    MATH  Google Scholar 

  • Korhonen P, Moskowitz H, Wallenius J (1990) Choice behavior in interactive multiple criteria decision making. Ann Oper Res 23:161–179

    Article  MathSciNet  Google Scholar 

  • Luce RD, Krantz DH (1971) Conditional expected utility. Econometrica 39:253–271

    Article  MathSciNet  Google Scholar 

  • Morton A, Fasolo B (2009) Behavioural decision theory for multi-criteria decision analysis: a guided tour. J Oper Res Soc 60:268–275

    Article  Google Scholar 

  • Roy B (1990) The outranking approach and the foundations of ELECTRE methods. In: Bana e Costa CA (ed) Readings in multiple criteria decision aid. Springer, Berlin, pp 155–183

    Chapter  Google Scholar 

  • Roy B (1991) The outranking approach and thinks of ELECTRE methods. Theor Decis 31:49–73

    Article  Google Scholar 

  • Roy B, Mousseau V (1996) A theoretical framework for analysing the notion of relative importance of criteria. J Multi-Criteria Decis Anal 5(2):145–159

    Article  Google Scholar 

  • Saaty T (1980) The analytic hierarchy process. McGraw-Hill, New York

    MATH  Google Scholar 

  • Saaty TL (1986) Axiomatic foundation of the analytic hierarchy process. Manag Sci 32:841–855

    Article  MathSciNet  Google Scholar 

  • Salminen P (1994) Solving the discrete multiple criteria problem using linear prospect theory. Eur J Oper Res 72:146–154

    Article  Google Scholar 

  • Savage LJ (1954) The foundation of statistics. Wiley, New York

    Google Scholar 

  • Shefrin H (2002) Behavioral decision making, forecasting, game theory, and role-play. Int J Forecast 18(3):375–382

    Article  Google Scholar 

  • Simon HA (1990) Bounded rationality. In: Eatwell J, Milgate M, Newman P (eds) Utility and probability. Palgrave Macmillan, London, pp 15–18

    Chapter  Google Scholar 

  • Slovic P, Lichtenstein S (1971) Comparison of Bayesian and regression approaches to the study of information processing in judgment. Organ Behav Hum Perform 6(6):649–744

    Article  Google Scholar 

  • Tversky A, Kahneman D (1974) Judgment under uncertainty: heuristics and biases. Science 185(4157):1124–1131

    Article  Google Scholar 

  • Tversky A, Kahneman D (1991) Loss aversion in riskless choice: a reference-dependent model. Quart J Econ 106(4):1039–1061

    Article  Google Scholar 

  • von Neumann J, Morgenstern O (1947) Theory of games and economic behavior, 2nd edn. Princeton University Press, Princeton

    MATH  Google Scholar 

  • Yücel MG, Görener A (2016) Decision making for company acquisition by ELECTRE method. Int J Supply Chain Manag 5(1):75–83

  • Zweig J (2007) Your money and your brain: how the new science of neuroeconomics can help make you rich. Simon & Schuster, New York

    Book  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Gabriella Marcarelli.

Ethics declarations

Conflict of interest

The authors declare that they have no conflict of interest.

Research involving human participants and/or animals

This article does not contain any studies with human participants or animals performed by any of the authors.

Informed consent

Informed consent was obtained from all individual participants included in the study.

Additional information

Communicated by M. Squillante.

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Fattoruso, G., Marcarelli, G., Olivieri, M.G. et al. Using ELECTRE to analyse the behaviour of economic agents. Soft Comput 24, 13629–13637 (2020). https://doi.org/10.1007/s00500-019-04397-2

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00500-019-04397-2

Keywords

Navigation