Advertisement

Instrumental and Value Rationality of the Self-regulation Model of Decision-Making

  • Alexander M. YemelyanovEmail author
  • Inna S. Bedny
Conference paper
  • 5 Downloads
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 1201)

Abstract

This paper offers further development of the self-regulation model of decision-making, which is based on the self-regulation model of the thinking process developed within the framework of the systemic-structural activity theory (SSAT). The role of instrumental and value rationality in decision-making under uncertainty is described. In this paper, we further specify the role of the factors of significance and difficulty in the self-regulation process of decision-making by considering the energy and information component of these factors, along with the instrumental (processing) and value rationality related to them. Eight core energy- and information-based shaping factors that regulate instrumental and value rationality are presented.

Keywords

Systemic-structural activity theory Decision making under uncertainty Self-regulation model Instrumental and value rationality Bounded rationality Shaping factors of instrumental and value rationality 

References

  1. 1.
    Bell, D.E., Raiffa, H., Tversky, A.: Descriptive, normative, and prescriptive interactions in decision making. In: Bell, D.E., Raiffa, H., Tversky, A. (eds.) Decision Making: Descriptive, Normative, and Prescriptive Interactions, pp. 9–30. Cambridge University Press, Cambridge (1988)CrossRefGoogle Scholar
  2. 2.
    Weber, M.: Economy and Society. In: Roth, G., Wittich, C. (eds.) University of California Press, Berkeley (1978)Google Scholar
  3. 3.
    Nozick, R.: The Nature of Rationality. Princeton University Press, Princeton (1993)Google Scholar
  4. 4.
    Djulbegovic, B., Elqayam, S.: Many faces of rationality: implications of the great rationality debate for clinical decision-making. J. Eval. Clin. Pract. 23, 915–922 (2017)CrossRefGoogle Scholar
  5. 5.
    Kahneman, D., Tversky, A.: Prospect theory: an analysis of decision under risk. Econometrica 47(2), 263–291 (1979)MathSciNetCrossRefGoogle Scholar
  6. 6.
    Kahneman, D., Tversky, A.: Choices, values, and frames. Am. Psychol. 39(4), 341–350 (1984)CrossRefGoogle Scholar
  7. 7.
    Yemelyanov, A.M.: Modeling and Mobile Device Support of Goal-Directed Decision Making under Risk and Uncertainty, Chapter 4. In: Bedny, G., Bedny, I. (eds.) Study of Human Performance: Applied and Systemic-Structural Activity Theory Approach, pp. 69–102. CRC Press, Taylor & Francis Group, Boca Raton (2019)CrossRefGoogle Scholar
  8. 8.
    Bourgeois-Gironde, S., Giraud, R.: Framing effects as violations of extensionality. Theory Decis. 67(4), 385–404 (2009)MathSciNetCrossRefGoogle Scholar
  9. 9.
    Simon, H. A.: The scientist as problem solver. In: Simon, A., Klahr, D., Kotovsky, K. (eds.) Complex Information Processing: The Impact of Herbert. Hillsdale, NJ: Elbaum, pp. 375–398 (1989)Google Scholar
  10. 10.
    Simon, H.A.: Human nature in politics: the dialogue of psychology with political science. Am. Polit. Sci. Rev. 79, 293–304 (1985)CrossRefGoogle Scholar
  11. 11.
    Gigerenzer, G., Hertwig, R., Pachur, T. (eds.): Heuristics: The Foundation of Adaptive Behavior. Oxford University Press, New York (2011)Google Scholar
  12. 12.
    Gigerenzer, G., Gaissmaier, W.: Heuristic decision making. Ann. Rev. Psychol. 62, 451–482 (2011)CrossRefGoogle Scholar
  13. 13.
    Bedny, G.Z., Bedny, I.S.: Work Activity Studies Within the Framework of Ergonomics, Psychology, and Economics. CRC Press/Taylor & Francis Group, Boca Raton (2018)CrossRefGoogle Scholar
  14. 14.
    Damasio, A.R.: Descartes’ error: emotion, reason, and the human brain. Uncertainty 5(4), 297–323. New York: Avon Books (1994)Google Scholar
  15. 15.
    Kotik, M.A.: Self-regulation and reliability of operator. Tallinn, Estonia, Valgus (1974). (in Russian)Google Scholar
  16. 16.
    Yemelyanov, A.M.: Self-regulation model of decision-making. In: Ayaz, H. (Ed.) Advances in Neuroergonomics and Cognitive Engineering. Advances in Intelligent Systems and Computing, vol. 953, pp. 245–255. Springer International Publishing (2019)Google Scholar

Copyright information

© The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2021

Authors and Affiliations

  1. 1.College of Business and ComputingGeorgia Southwestern State UniversityAmericusUSA
  2. 2.Evolute, LLCWayneUSA

Personalised recommendations