Abstract
This chapter traces the parallel development of the constructs of bounded rationality in economics and cognitive capacity in psychology. Both perspectives led to the study of cognitive biases, the interdisciplinary field of behavioral economics, and artificial intelligence products that solved some of the original problems but created new and similar ones. The role of emotions in ideally rational decision processes also motivated the study of cognitive workload and fatigue in financial decision making, which is the primary focus of this book. The chapter concludes with elementary constructs of nonlinear dynamical systems theory that are intrinsic to the theory of cognitive workload and fatigue that is articulated in Chap. 2.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Amenc, N., Curtis, S., & Martellini, L. (2004). The alpha and omega of hedge fund performance measurement. Lille: EDHEC Risk and Asset Management Research Centre. Retrieved December 15, 2011, from http://www.edhecrisk.com/performance_and_style_analysis/Hendge_funds_performance
Arecchi, F. T. (2011). Phenomenology of consciousness: From apprehension to judgment. Nonlinear Dynamics, Psychology, and Life Sciences, 15, 359–376.
Ashby, W. R. (1956). Introduction to cybernetics. New York: Wiley.
Baddeley, A. (2003). Working memory: Looking back and looking forward. Nature Reviews Neuroscience, 4, 829–839.
Bruno, S. (2010). Optimization and “thoughtful conjecturing” as principles of analytical guidance in social decision making. In C. P. Vinci (Ed.), Decision theory and choices: A complexity approach. New York: Springer.
Blanchette, I. (Ed.). (2014). Emotion and reasoning. New York: Psychology Press.
Borges, L. A. J., & Guastello, S. J. (1998). Chaos theory applied to TQM: A survey. In W. L. Baker (Ed.), Proceedings of the 52nd annual quality congress (pp. 578–585). Philadelphia: American Society for Quality Control.
Broadbent, D. E. (1958). Perception and communication. Elmsford: Pergamon Press.
Dore, M. H. I., & Rosser, J. B., Jr. (2007). Do nonlinear dynamics in economics amount to a Kuhnian paradigm? Nonlinear Dynamics, Psychology, and Life Sciences, 11, 119–148.
Edwards, F. R., & Caglayan, M. O. (2001). Hedge fund performance and manager skill. Journal of Futures Markets, 21, 1003–1028.
Elliott, G., & Timmermann, A. (2008). Economic forecasting. Journal of Economic Literature, 46, 3–56.
Endsley, M. R., Bolté, B., & Jones, D. G. (2003). Designing for situation awareness: An approach to user-centered design. Boca Raton: CRC Press.
Epstein, J. M., & Axtell, R. (1996). Growing artificial societies: Social science from the bottom up. Cambridge, MA: MIT Press.
Faggini, M., & Vinci, C. P. (Eds.). (2010). Decision theory and choices: A complexity approach. New York: Springer.
Fisher, K. L., & Statman, M. (2000). Cognitive biases in market forecasts. Journal of Portfolio Management, Fall, 1–10.
Frantz, T. L., & Carley, K. M. (2009). Agent-based modeling within a dynamic network. In S. J. Guastello, M. Koopmans, & D. Pincus (Eds.), Chaos and complexity in psychology: The theory of nonlinear dynamical systems (pp. 475–505). New York: Cambridge University Press.
Friesen, G. C., & Weller, P. (2005). Quantifying cognitive biases in analyst earnings forecasts. Lincoln: University of Nebraska Finance Department. Retrieved December 15, 2011, from http://digicalcommons.unl.edu/financefacpub/23
Gärling, T., Kirchler, E., Lewis, A., & van Raaij, F. (2009). Psychology, financial decision making, and financial crises. Psychological Science in the Public Interest, 10, 1–47.
Géhin, W. (2003). Hedge fund performance. Lille: EDHEC Risk and Asset Management Research Centre. Retrieved December 15, 2011, from http://www.edhec-risk.com/performance_and_style_analysis/Hendge_funds_performance
Gibson, J. J. (1979). The ecological approach to visual perception. Boston: Houghton Mifflin.
Gomes, O. (2015). A model of animal spirits via sentiment spreading. Nonlinear Dynamics, Psychology, and Life Sciences, 19, 313–343.
Guastello, S. J. (2009). Chaos as a psychological construct: Historical roots, principal findings, and current growth directions. Nonlinear Dynamics, Psychology, and Life Sciences, 13, 289–310.
Guastello, S. J. (2014). Human factors engineering and ergonomics: A systems approach. Boca Raton: CRC Press.
Guastello, S. J., & Rieke, M. L. (1994). Computer–based test interpretations as expert systems: Validity and viewpoints from artificial intelligence theory. Computers in Human Behavior, 4, 435–495.
Kahneman, D., & Tversky, A. (1979). Prospect theory: An analysis of decision under risk. Econometrica, 47, 253–291.
Kantowitz, B. H. (1985). Channels and stages in human information processing: A limited analysis of theory and methodology. Journal of Mathematical Psychology, 29, 135–174.
Kaplan, D., & Glass, L. (1995). Understanding nonlinear dynamics. New York: Springer.
Keynes, J. M. (1965). General theory of employment, interest, and money (2nd ed.). New York: Harcourt Brace.
Lowenstein, L. (2006). Search for rational investors in a perfect storm: A behavioral perspective. The Journal of Behavioral Finance, 7, 66–74.
Mayer, J. D., & Salovey, P. (1997). What is emotional intelligence? In P. Salovey & D. Sluyter (Eds.), Emotional development and emotional intelligence: Educational implications (pp. 3–34). New York: Basic Books.
McClelland, D. C., Atkinson, J. W., Clark, R. A., & Lowell, E. L. (1953). The achievement motive. New York: Appleton-Century-Croft.
Meyer, J., & Lee, J. D. (2013). Trust, reliance, and compliance. In The Oxford handbook of cognitive engineering (pp. 109–124). New York: Oxford University Press.
Reason, J. (1997). Managing the risks of organizational accidents. Brookfield: Ashgate.
Rosser, J. B., Jr. (2000). From catastrophe to chaos: A general theory of economic discontinuities (2nd ed.). Norwell: Kluwer Academic Publishers.
Rosser, J. B., Jr. (Ed.). (2004). Complexity in economics. Cheltenham: Edward Elgar.
Rosser, J. B., Jr., & Rosser, M. V. (2015). Complexity and behavioral economics. Nonlinear Dynamics, Psychology, and Life Sciences, 19, 201–226.
Schachter, S., & Singer, J. (1962). Cognitive, social, and physiological determinants of emotional state. Psychological Review, 69, 379–399.
Schels, M., Thiel, C., Schwenker, F., & Palm, G. (2009). Classifier fusion applied to facial expression recognition: An experimental comparison. In H. Ritter, G. Sagerer, R. Dillmann, & M. Buss (Eds.), Human centered robot systems: Cognition, interaction, technology (pp. 121–130). New York: Springer.
Sheridan, T. B. (2002). Humans and automation: System design and research issues. New York: Wiley.
Simon, H. A. (1957). Administrative behavior (2nd ed.). Totowa: Littlefield Adams.
Simon, H. A. (1962/2004). The architecture of complexity. Proceedings of the American Philosophical Society, 106, 467–482. Reprinted in J. B. Rosser, Jr. (Ed.), Complexity in economics. Cheltenham: Edward Elgar.
Sprott, J. C. (2003). Chaos and time-series analysis. New York: Oxford.
Sternberg, R. J., & Lubart, T. I. (1991). An investment theory of creativity and its development. Human Development, 34, 1–31.
Thierry, B.-H. (2007). Rules of thumb and real option decision biases for optimally imperfect decisions: A simulation-based exploration. Investment Management and Financial Innovations, 4, 105–118.
Tolman, E. C. (1932). Purposive behavior in animals and man. New York: Century.
Van Duijvendoorde, A. C. K., Jansen, B. R. J., & Huizenga, H. M. (2015). Risky choice from childhood to adulthood: Change in decision strategies, affect, and control. In E. A. Wilhelms & V. F. Reyna (Eds.), Neuroeconomics, judgment, and decision making (pp. 203–218). New York: Psychology Press.
Wickens, C. D. (2002). Multiple resources and performance prediction. Theoretical Issues in Ergonomics Science, 3, 159–177.
Wilhelms, E. A., & Reyna, V. F. (Eds.). (2015). Neuroeconomics, judgment, and decision making. New York: Psychology Press.
Wilkins, I., & Dragos, B. (2013). Destructive destruction? An ecological study of high frequency trading. Retrieved February 16, 2013, from http://www.metamute.org/
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2016 Springer Japan
About this chapter
Cite this chapter
Guastello, S.J. (2016). Bounded Rationality in the Twenty-First Century. In: Guastello, S. (eds) Cognitive Workload and Fatigue in Financial Decision Making. Evolutionary Economics and Social Complexity Science, vol 13. Springer, Tokyo. https://doi.org/10.1007/978-4-431-55312-0_1
Download citation
DOI: https://doi.org/10.1007/978-4-431-55312-0_1
Published:
Publisher Name: Springer, Tokyo
Print ISBN: 978-4-431-55311-3
Online ISBN: 978-4-431-55312-0
eBook Packages: Business and ManagementBusiness and Management (R0)