Decision-Making Styles in an Evolutionary Perspective

  • Silvia Dell’OrcoEmail author
  • Raffaele Sperandeo
  • Ciro Punzo
  • Mario Bottone
  • Anna Esposito
  • Antonietta M. Esposito
  • Vincenzo Bochicchio
  • Mauro N. Maldonato
Part of the Smart Innovation, Systems and Technologies book series (SIST, volume 151)


Naturalistic decision-making (NDM) investigates the cognitive strategies used by experts in making decisions in real-world contexts. Unlike studies conducted in the laboratory, the NDM paradigm is applied to real human interactions, often characterized by uncertainty, risk, complexity, time pressures and so on. In this approach, the role of experience is crucial in making possible a quick classification of decision-making situations and therefore in making an effective, rapid and prudent choice. Models of behaviour resulting from these studies represent an extraordinary resource for research and for the application of decision-making strategies in high-risk environments. They particularly underline not only that most of the critical decisions that we take are based on our intuition, but that the ability to recognize patterns and other signals that allow us to act effectively is a natural extension of experience.


Decision-making Recognition-primed Naturalistic decision-making 


  1. 1.
    Zsambok, C.E., Klein, G. (eds.): Naturalistic Decision Making. Psychology Press, New York (2014)Google Scholar
  2. 2.
    Klein, G.A., Orasanu, J.E., Calderwood, R.E., Zsambok, C.E.: Decision making in action: models and methods. In: This Book is an Outcome of a Workshop Held in Dayton, OH, 25–27 Sep 1989. Ablex Publishing, New York (1993)Google Scholar
  3. 3.
    Klein, G.L.: A recognition-primed decision (RPD) model of rapid decision making. Decision Making in Action: Models and Methods. Ablex Publishing, New York (1993)Google Scholar
  4. 4.
    Beach, L.R., Lipshitz, R.: Why classical decision theory is an inappropriate standard for evaluating and aiding most human decision making. In: Decision Making in Aviation, 85 (2017)Google Scholar
  5. 5.
    Lipshitz, R.: Converging themes in the study of decision making in realistic settings. In: Klein, G.A., Orasanu, J., Calderwood, R., Zsambok, C.E. (eds.) Decision Making in Action: Models and Methods, pp. 103–137. Ablex, Norwood, NJ (1993)Google Scholar
  6. 6.
    Hammond, K.R., Hamm, R.M., Grassia, J., Pearson, T.: Direct comparison of the efficacy of intuitive and analytical cognition in expert judgment. IEEE Trans. Syst. Man Cybern. 17(5), 753–770 (1987)CrossRefGoogle Scholar
  7. 7.
    Rasmussen, J.: Skills, rules, and knowledge; signals, signs, and symbols, and other distinctions in human performance models. IEEE Trans. Syst. Man Cybern. 3, 257–266 (1983)CrossRefGoogle Scholar
  8. 8.
    Maldonato, N.M., Dell’Orco, S.: The natural logic of action. World Futures 69(3), 174–183 (2013)CrossRefGoogle Scholar
  9. 9.
    Morton, A.: Disasters and Dilemmas: Strategies for Real-Life Decision Making. Wiley, Hoboken (2017)Google Scholar
  10. 10.
    Klein, G.A., Calderwood, R., Clinton-Cirocco, A.: Rapid decision making on the fire ground. In: Proceedings of the Human Factors Society Annual Meeting (vol. 30, no. 6, pp. 576–580). Sage, Los Angeles, CA (1986)CrossRefGoogle Scholar
  11. 11.
    Lipshitz, R., Omodei, M., McLennan, J., Wearing, A.: What’s burning? The RAWFS heuristic on the fire ground. In: Expertise Out of Context, pp. 97–112 (2007)Google Scholar
  12. 12.
    Zsambok, C.E.: Implications of a recognitional decision model for consumer behavior. In: ACR North American Advances (1993)Google Scholar
  13. 13.
    Schiebener, J., Brand, M.: Decision making under objective risk conditions—a review of cognitive and emotional correlates, strategies, feedback processing, and external influences. Neuropsychol. Rev. 25(2), 171–198 (2015)CrossRefGoogle Scholar
  14. 14.
    Maldonato, N.M., Dell’Orco, S., Sperandeo, R.: When intuitive decisions making, based on expertise, may deliver better results than a rational, deliberate approach. In: Esposito, A., Faundez-Zanuy, M., Morabito, F.C., Pasero, E. (eds.) Multidisciplinary Approaches to Neural Computing. Springer, Cham (2018)Google Scholar
  15. 15.
    Simon, H.A.: Theories of bounded rationality. Decis. Organ. 1(1), 161–176 (1972)MathSciNetGoogle Scholar
  16. 16.
    Klein, G.: A naturalistic decision making perspective on studying intuitive decision making. J. Appl. Res. Mem. Cogn. 4(3), 164–168 (2015)CrossRefGoogle Scholar
  17. 17.
    Juanchich, M., Dewberry, C., Sirota, M., Narendran, S.: Cognitive reflection predicts real-life decision outcomes, but not over and above personality and decision-making styles. J. Behav. Decis. Mak. 29(1), 52–59 (2016)CrossRefGoogle Scholar
  18. 18.
    Mata, R., Josef, A.K., Lemaire, P.: Adaptive decision making and aging. In: Aging and Decision Making, pp. 105–126 (2015)CrossRefGoogle Scholar
  19. 19.
    Lin, X., Featherman, M., Brooks, S.L., Hajli, N.: Exploring gender differences in online consumer purchase decision making: an online product presentation perspective. In: Information Systems Frontiers, pp. 1–15 (2018)CrossRefGoogle Scholar
  20. 20.
    Stanovich, K.E., West, R.F.: Individual differences in rational thought. J. Exp. Psychol. Gen. 127(2), 161 (1998)CrossRefGoogle Scholar
  21. 21.
    Scott, S.G., Bruce, R.A.: Decision-making style: the development and assessment of a new measure. Educ. Psychol. Measur. 55(5), 818–831 (1995)CrossRefGoogle Scholar
  22. 22.
    Riding, R.J., Glass, A., Douglas, G.: Individual differences in thinking: cognitive and neurophysiological perspectives. Educ. Psychol. 13(3–4), 267–279 (1993)CrossRefGoogle Scholar
  23. 23.
    Pask, G.: Learning strategies, teaching strategies, and conceptual or learning style. Learning Strategies and Learning Styles, pp. 83–100. Springer, Boston, MA (1988)CrossRefGoogle Scholar
  24. 24.
    Epstein, S., Pacini, R., Denes-Raj, V., Heier, H.: Individual differences in intuitive—experiential and analytical—rational thinking styles. J. Pers. Soc. Psychol. 71(2), 390 (1996)CrossRefGoogle Scholar
  25. 25.
    Maldonato, N.M., Dell’Orco, S.: The predictive brain. World Futures 68(6), 381–389 (2012)CrossRefGoogle Scholar
  26. 26.
    Bruine de Bruin, W., Parker, A.M., Fischhoff, B.: Individual differences in adult decision-making competence. J. Pers. Soc. Psychol. 92(5), 938 (2007)CrossRefGoogle Scholar
  27. 27.
    Scheibehenne, B., Von Helversen, B.: Selecting decision strategies: the differential role of affect. Cogn. Emot. 29(1), 158–167 (2015)CrossRefGoogle Scholar
  28. 28.
    Hollnagel, E.: Decisions about “what” and decisions about “how”. In: Decision Making in Complex Environments, pp. 37–46. CRC Press, Boca Rotan (2017)CrossRefGoogle Scholar
  29. 29.
    Payne, J.W., Bettman, J.R., Johnson, E.J.: The Adaptive Decision Maker. Cambridge University Press, Cambridge (1993)CrossRefGoogle Scholar
  30. 30.
    Maldonato, N.M., Dell’Orco, S.: How to make decisions in an uncertain world: heuristics, biases, and risk perception. World Futures 67(8), 569–577 (2011)CrossRefGoogle Scholar
  31. 31.
    Gigerenzer, G.: Towards a rational theory of heuristics. Minds, Models and Milieux, pp. 34–59. Palgrave Macmillan, London (2016)Google Scholar
  32. 32.
    Glöckner, A., Hilbig, B.E., Jekel, M.: What is adaptive about adaptive decision making? A parallel constraint satisfaction account. Cognition 133(3), 641–666 (2014)CrossRefGoogle Scholar
  33. 33.
    Laureiro-Martínez, D., Brusoni, S.: Cognitive flexibility and adaptive decision-making: evidence from a laboratory study of expert decision-makers. Strateg. Manag. J. 39, 1031–1058 (2018)CrossRefGoogle Scholar
  34. 34.
    Jekel, M., Glöckner, A.: How to identify strategy use and adaptive strategy selection: the crucial role of chance correction in weighted compensatory strategies. J. Behav. Decis. Mak. 31, 265–279 (2016)CrossRefGoogle Scholar
  35. 35.
    Shevchenko, Y., Bröder, A.: The effect of mood on integration of information in a multi-attribute decision task. Acta Physiol. (Oxf.) 185, 136–145 (2018)Google Scholar
  36. 36.
    Maldonato, N.M.: Undecidable decisions: rationality limits and decision-making heuristics. World Futures 63(1), 28–37 (2007)CrossRefGoogle Scholar
  37. 37.
    Hogarth, R.M., Reder, M.W.: Rational Choice: The Contrast Between Economics and Psychology. University of Chicago Press, Chicago (1987)Google Scholar
  38. 38.
    Zipf, G.K.: Human Behaviour and the Principle of Least-Effort. Addison-Wesley, Reading, Cambridge MA (1949)Google Scholar
  39. 39.
    Gigerenzer, G.: The adaptive toolbox: toward a Darwinian rationality. Nebr. Symp. Motiv. 47, 113–144 (2001)Google Scholar
  40. 40.
    Mousavi, S.: Ecological rationality of heuristics in psychology and economics. In: Routledge Handbook of Behavioral Economics, 88 (2016)Google Scholar
  41. 41.
    Lipshitz, R., Strauss, O.: Coping with uncertainty: a naturalistic decision-making analysis. Organ. Behav. Hum. Decis. Process. 69(2), 149–163 (1997)CrossRefGoogle Scholar
  42. 42.
    Maldonato, N.M., Dell’Orco, S.: Making decisions under uncertainty emotions, risk and biases. Advances in Neural Networks: Computational and Theoretical Issues, pp. 293–302. Springer, Cham (2015)CrossRefGoogle Scholar
  43. 43.
    Gore, J., Ward, P.: Naturalistic decision making under uncertainty: theoretical and methodological developments–an introduction to the special section. J. Appl. Res. Mem. Cogn. (2018)Google Scholar
  44. 44.
    Klein, G.: The power of Intuition. Currency-Doubleday, New York, NY (2003)Google Scholar
  45. 45.
    Sperandeo, R., Picciocchi, E., Valenzano, A., Cibelli, G., Ruberto, V., Moretto, E., Monda, V., Messina, A., Dell’Orco, S., Di Sarno, A.D., Marsala, G., Polito, A.N., Longobardi, T., Maldonato, N.M.: Exploring the relationships between executive functions and personality dimensions in the light of “embodied cognition” theory: a study on a sample of 130 subjects. Acta Medica Mediterranea 34(5), 1271–1279 (2018)Google Scholar
  46. 46.
    Sperandeo, R., Moretto, E., Baldo, G., Dell’Orco, S., Maldonato, N.M.: Executive functions and personality features: a circular interpretative paradigm. In: 8th IEEE International Conference on Cognitive Infocommunications (CogInfoCom), pp. 000063–000066. IEEE (2017)Google Scholar

Copyright information

© Springer Nature Singapore Pte Ltd. 2020

Authors and Affiliations

  • Silvia Dell’Orco
    • 1
    Email author
  • Raffaele Sperandeo
    • 2
  • Ciro Punzo
    • 3
  • Mario Bottone
    • 4
  • Anna Esposito
    • 5
  • Antonietta M. Esposito
    • 6
  • Vincenzo Bochicchio
    • 7
  • Mauro N. Maldonato
    • 4
  1. 1.Department of Humanistic StudiesUniversity of Naples Federico IINaplesItaly
  2. 2.SiPGI—Postgraduate School of Integrated Gestalt PsychotherapyTorre AnnunziataItaly
  3. 3.Pontifical Lateran UniversityRomeItaly
  4. 4.Department of Neuroscience and Reproductive and Odontostomatological SciencesUniversity of Naples Federico IINaplesItaly
  5. 5.Department of PsychologyUniversity of Campania Luigi VanvitelliNaplesItaly
  6. 6.National Institute of Geophysics and VolcanologyNaplesItaly
  7. 7.Department of HumanitiesUniversity of CalabriaRendeItaly

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