Barriers in Application of Rational Decision
Barriers in Application of Rational Decision and
Methods to Overcome
Based on the “Expected Utility Theory”, “Rational Decision Making Theory” describes the process of “Economic Man” making a rational choice. With the development of the theory, its overly idealistic assumptions and practicability have sparked criticism from various camps. Some paradoxes, such as Allais Paradox and St. Petersburg Paradox were difficult to interpret by it. Some “decision biases” deviating from the theoretically optimal behavior were also noticed in the actual choice process. In this paper, we shall first briefly review the rational decision theory. Then, under the framework of the behavioural decision science, we will discuss the barriers in application of the model by exploring the influences that three factors――bounded rationality, uncertainty, and cognitive bias――bring to it. In each section, the author first gives examples to demonstrate the existence of effects, then proposes theories to explain the generation of obstacles, and finally discusses selective methods to overcome the barriers.
1. Rational Decision Making Theory
James G. March (1994, p.2) pointed out that rational decision processes were consequential, based on the preference and aimed at maximizing the expected utility. They are consequential means that “action depends on anticipations of the future effects of current actions”. A list of alternatives is then generated according to these anticipations. They are preference-based means that the criteria of evaluating the alternatives are identified by individual preferences. Outcomes are reflected in terms of different expected utilities. They are expected utility maximization-aimed means that after calculating expected utility of each prospect, a decision-maker will finally choose the one with maximal expected utility.
After concluding the steps of rational choice above, we can sum up the inherent assumptions of the rational decision-making model combing
Methods to Overcome
Based on the “Expected Utility Theory”, “Rational Decision Making Theory” describes the process of “Economic Man” making a rational choice. With the development of the theory, its overly idealistic assumptions and practicability have sparked criticism from various camps. Some paradoxes, such as Allais Paradox and St. Petersburg Paradox were difficult to interpret by it. Some “decision biases” deviating from the theoretically optimal behavior were also noticed in the actual choice process. In this paper, we shall first briefly review the rational decision theory. Then, under the framework of the behavioural decision science, we will discuss the barriers in application of the model by exploring the influences that three factors――bounded rationality, uncertainty, and cognitive bias――bring to it. In each section, the author first gives examples to demonstrate the existence of effects, then proposes theories to explain the generation of obstacles, and finally discusses selective methods to overcome the barriers.
1. Rational Decision Making Theory
James G. March (1994, p.2) pointed out that rational decision processes were consequential, based on the preference and aimed at maximizing the expected utility. They are consequential means that “action depends on anticipations of the future effects of current actions”. A list of alternatives is then generated according to these anticipations. They are preference-based means that the criteria of evaluating the alternatives are identified by individual preferences. Outcomes are reflected in terms of different expected utilities. They are expected utility maximization-aimed means that after calculating expected utility of each prospect, a decision-maker will finally choose the one with maximal expected utility.
After concluding the steps of rational choice above, we can sum up the inherent assumptions of the rational decision-making model combing
References: Baron, J. (2000). Thinking and Deciding. Cambridge: Cambridge University Press. Camerer, C.F & Hogarth, R.M. (1999). The effects of financial incentives in experiments: A review and capital– labor – production framework. Journal of Risk and Uncertainty, 19(1), 7- 42. Edwards, W. (1954). Theory of decision making. Psychological Bulletin, 51(4), 380- 417. Esgate, A. & Groome, D. (2004). An introduction to applied cognitive psychology. New York: Psychology Press. Flannelly, L.T. & Flannelly, K.J. (2000). Reducing people 's judgment bias about their level of knowledge. The Psychological Record, 50(3), 587- 600. Kahneman, D. & Tversky, A. (1979). Prospect theory: An analysis of decision under risk. Econometrica, 47(2), 263-291. Kahneman, D. & Tversky, A. (1992). Advances in prospect theory: Cumulative representation of uncertainty. Journal of Risk & Uncertainty, 5(4), 297-323. Klayman, J. & Ha, Y. (1987). Confirmation, disconfirmation, and information in hypothesis testing. Psychological Review, 94(2), 211- 228. Larrick, R. P. (2004). Debiasing. In: D. J. Koehler and N. Harvey Blackwell Handbook of Judgement and Decision Making. Oxford: Blackwell. 316-337. Lerner, J.S. & Tetlock, P.E. (1999). Accounting for the effects of accountability. Psychological Bulletin, 125(2), 225-275. March, J.G. (1994). Primer on decision making: How decisions happen. New York: Free Press. Robbins, S.P. & Timothy, A.J. (2007). Organization Behavior. 12th ed. New Jersey: Pearson Prentice Hall. Simon, H.A. (1947). Administrative behavior: A study of decision-making processes in administrative organization. New York: Free Press. Tversky, A., & Kahneman, D. (1974). Judgement under uncertainty: Heuristics and biases. Science, 185(4157), 1124-1131. Tversky, A., & Kahneman, D. (1983). Extensional versus intuitive reasoning: The conjunction fallacy in probability judgments. Psychological Review, 90(4), 293-315. Willman, P., Fenton-O 'Creevy, M., Nicholson, N. & Soane, E. (2006). Noise trading and the management of operational risk; firms, traders and irrationality in financial markets. Journal of Management Studies, 43(6), 1357-1374.