Spring 2015
Title: Psychology of Decision Making in Uncertain World: Introduction to Behavioral Decision Theory and Its Application
Teacher:
Kazuhisa Takemura, Ph.D(System Science)& Ph.D.(Medicine)
Exchange Professor, Venice International University
Professor, Department of Psychology, Waseda University
Director, Institute of Decision Research, Waseda University
Outline: This course examines basic concepts of behavioral decision theory in uncertain world. Behavioral decision theory is described briefly as the general term for descriptive theories to explain the psychological knowledge related to people’s decision-making behavior. It is called theory, but it is a combination of various psychological theories, for which no axiomatic systems such as those with which the utility theory widely used in economics have been established, but it is often limited to qualitative knowledge. As the studies of H. A. Simon, who won the Nobel Prize for economics in 1978, and D. Kahneman, who won the prize in 2002 suggest, however, the psychological methodology and knowledge of behavioral decision theory have been applied widely in such fields as economics, business administration, and engineering, and are expected to become useful in the future. This course will explain various behavioral decision theories related to decision-making processes. Numerous models have been proposed to explain the psychological processes related to such a selection of decision strategies. This course will also introduce some new models that are useful to explain decision-making processes. It ends with some speculation about the future of modern behavioral decision theories while referring to their relation with fields related to neuroscience, such as neuroeconomics, that have been developed in recent years.
Although decision-making broadly refers to the function of consciousness to make a decision, it can also be defined technically as the act of selecting an option from a group of alternatives, i.e. the choice of action. For instance, selecting the preferred means of transportation, deciding which product to purchase, and determining which proposal to adopt are examples of decision-making. We, as consumers, make decisions about purchasing various goods, and at times, must make decisions related to corporate activities and political issues. Examining optimal decision-making reveals that rationality is necessary in the course of making the decision. A decision for which the purpose and method are contradictory is somehow not right. When we intend to make a good decision, it appears that we often assume that we will select the optimal alternative, i.e. the best decision-making. This is what is called the "best decision-making” in the world of business. This course also examines the possibility of best decision, better decision, and good decision thinking through findings of decision research.
Goal of the course
The student will learn descriptive theories of decision-making in uncertain and complex world, and will learn recent psychological findings and behavioral theories of human decision making process in social situations. Student will also learn typical normative decision theories such as expected utility theory and practical applications of decision research to marketing and policy making.
Pre-requisite: None.
Evaluation:
The course is composed of lectures ,discussions, and presentations by students.
Evaluation is structured in four steps: attendance and participation to class (30%); final exam (40%), and research paper (30%).
Contents: What follow are to be discussed in this order.
1. Psychology of decision making in uncertain world
2. What is behavioral decision theory: Its history and concepts
3. What is decision-making in global society ?
4. Structure of preference relations and decision-making problems
5. Decision-making and uncertainty
5-1. Decision-making under certainty
5-2. Decision-making under risk
5-3. Decision-making under uncertainty
6. Utility and measurement
7. The idea of the St. Petersburg paradox and expected utility
8. Empirical research on the value function and reflection effect
9. Empirical research on probability weighting function
10. Cumulative prospect theory
11. Experiments on cumulative prospect theory
12. What type of phenomenon is the framing effect?
13. Why can utility theory not explain the framing effect?
14. Framing and mental accounting in social life
15. Contingent focus model explaining framing effect
16 .Multi-attribute decision-making and decision strategy
17. Process models of decision making and empirical findings
18. Behavioral decision theory towards good decision making
Bibliography
Bell, D. E., Raiffa, H. and Tversky, A. (1988). “Descriptive, Normative, and Prescriptive Interactions in Decision Making”, In D. E. Bell, H. Raiffa, A. Tversky (eds.), Decision
Making: Descriptive, Normative, and Prescriptive Interactions, New York: Cambridge
University Press. 9-30.
Camerer, C. F., Loewenstein, G. and Rabin, M. (eds.) (2004). Advances in Behavioral
Economics, Princeton, N. J., Princeton University Press.
Edwards, W. (1961). “Behavioral Decision Theory”, Annual Review of Psychology. 12,
473-498.
Gigerenzer, G. and Goldstein, D. (1996). “Reasoning the fast and frugal way: Models of
bounded rationality” Psychological Review. 103, 650–669.
Gilboa, I. (2009). Theory of decision under uncertainty. New York:NY: Cambridge
University Press
Krantz, D. H., Luce, R. D., Suppes, P. and Tversky, A. (1971). “Foundations of
measurement Volume 1: Additive and polynomial representations”, New York:
Academic Press.
Luce, R. D. and Tukey, J. W. (1964). “ Simultaneous conjoint measurement: A new type
of fundamental measurement”, Journal of Mathematical Psychology. 1, 1–27.
Montgomery, H. (1983). Decision rules and the search for a dominance structure:
Towards a process model of decision-making. In P. C. Humphreys, O. Svenson, and
A Vari (Eds.), Analyzing and aiding decision processes. Amsterdam: North-Holland.
343– 369.
Montgomery, H. (1993). The search for a dominance structure in decision-making:
Examining the evidence. In G.A. Klein, J. Orasanu, R. Calderwood, and C. E. Zsambok
(Eds.), Decision-making in action: Models and methods. Norwood, N.J.: Ablex. 182–
187.
Schwartz, B., Ward, A., Monterosso, J., Lyubomirsky, S., White, K. and Lehman, D. R.
(2002). “Maximizing versus satisficing: Happiness is a matter of choice.” Journal of Personality and Social Psychology. 83, 1178–1197.
Takemura, K. (2000). “Vagueness in Human Judgment and Decision Making”, In Z. Q.
Liu and S. Miyamoto, Soft Computing for Human Centered Machines, Tokyo: Springer
Verlag. 249-281.
Takemura, K. (2014), Behavioral decision theory: Mathematical and psychological
descriptions of human choice behavior, New York: Springer,
Tversky, A. and Kahneman, D. (1981). “The framing decisions and the psychology of
choice”, Science. 211, 453–458.
Tversky, A. and Kahneman, D. (1992). “Advances in the prospect theory: Cumulative
representation of uncertainty”, Journal of Risk and Uncertainty. 5, 297–323.
Tversky, A. and Wakker, P. (1995). “Risk attitudes and decision weight”, Econometrica.
63, 1255–1280.
Wu, G. and Gonzalez, R. (1996). “Curvature of the probability weighting function”,
Management Science. 42, 1676–1690.
Title: Psychology of Decision Making in Uncertain World: Introduction to Behavioral Decision Theory and Its Application
Teacher:
Kazuhisa Takemura, Ph.D(System Science)& Ph.D.(Medicine)
Exchange Professor, Venice International University
Professor, Department of Psychology, Waseda University
Director, Institute of Decision Research, Waseda University
Outline: This course examines basic concepts of behavioral decision theory in uncertain world. Behavioral decision theory is described briefly as the general term for descriptive theories to explain the psychological knowledge related to people’s decision-making behavior. It is called theory, but it is a combination of various psychological theories, for which no axiomatic systems such as those with which the utility theory widely used in economics have been established, but it is often limited to qualitative knowledge. As the studies of H. A. Simon, who won the Nobel Prize for economics in 1978, and D. Kahneman, who won the prize in 2002 suggest, however, the psychological methodology and knowledge of behavioral decision theory have been applied widely in such fields as economics, business administration, and engineering, and are expected to become useful in the future. This course will explain various behavioral decision theories related to decision-making processes. Numerous models have been proposed to explain the psychological processes related to such a selection of decision strategies. This course will also introduce some new models that are useful to explain decision-making processes. It ends with some speculation about the future of modern behavioral decision theories while referring to their relation with fields related to neuroscience, such as neuroeconomics, that have been developed in recent years.
Although decision-making broadly refers to the function of consciousness to make a decision, it can also be defined technically as the act of selecting an option from a group of alternatives, i.e. the choice of action. For instance, selecting the preferred means of transportation, deciding which product to purchase, and determining which proposal to adopt are examples of decision-making. We, as consumers, make decisions about purchasing various goods, and at times, must make decisions related to corporate activities and political issues. Examining optimal decision-making reveals that rationality is necessary in the course of making the decision. A decision for which the purpose and method are contradictory is somehow not right. When we intend to make a good decision, it appears that we often assume that we will select the optimal alternative, i.e. the best decision-making. This is what is called the "best decision-making” in the world of business. This course also examines the possibility of best decision, better decision, and good decision thinking through findings of decision research.
Goal of the course
The student will learn descriptive theories of decision-making in uncertain and complex world, and will learn recent psychological findings and behavioral theories of human decision making process in social situations. Student will also learn typical normative decision theories such as expected utility theory and practical applications of decision research to marketing and policy making.
Pre-requisite: None.
Evaluation:
The course is composed of lectures ,discussions, and presentations by students.
Evaluation is structured in four steps: attendance and participation to class (30%); final exam (40%), and research paper (30%).
Contents: What follow are to be discussed in this order.
1. Psychology of decision making in uncertain world
2. What is behavioral decision theory: Its history and concepts
3. What is decision-making in global society ?
4. Structure of preference relations and decision-making problems
5. Decision-making and uncertainty
5-1. Decision-making under certainty
5-2. Decision-making under risk
5-3. Decision-making under uncertainty
6. Utility and measurement
7. The idea of the St. Petersburg paradox and expected utility
8. Empirical research on the value function and reflection effect
9. Empirical research on probability weighting function
10. Cumulative prospect theory
11. Experiments on cumulative prospect theory
12. What type of phenomenon is the framing effect?
13. Why can utility theory not explain the framing effect?
14. Framing and mental accounting in social life
15. Contingent focus model explaining framing effect
16 .Multi-attribute decision-making and decision strategy
17. Process models of decision making and empirical findings
18. Behavioral decision theory towards good decision making
Bibliography
Bell, D. E., Raiffa, H. and Tversky, A. (1988). “Descriptive, Normative, and Prescriptive Interactions in Decision Making”, In D. E. Bell, H. Raiffa, A. Tversky (eds.), Decision
Making: Descriptive, Normative, and Prescriptive Interactions, New York: Cambridge
University Press. 9-30.
Camerer, C. F., Loewenstein, G. and Rabin, M. (eds.) (2004). Advances in Behavioral
Economics, Princeton, N. J., Princeton University Press.
Edwards, W. (1961). “Behavioral Decision Theory”, Annual Review of Psychology. 12,
473-498.
Gigerenzer, G. and Goldstein, D. (1996). “Reasoning the fast and frugal way: Models of
bounded rationality” Psychological Review. 103, 650–669.
Gilboa, I. (2009). Theory of decision under uncertainty. New York:NY: Cambridge
University Press
Krantz, D. H., Luce, R. D., Suppes, P. and Tversky, A. (1971). “Foundations of
measurement Volume 1: Additive and polynomial representations”, New York:
Academic Press.
Luce, R. D. and Tukey, J. W. (1964). “ Simultaneous conjoint measurement: A new type
of fundamental measurement”, Journal of Mathematical Psychology. 1, 1–27.
Montgomery, H. (1983). Decision rules and the search for a dominance structure:
Towards a process model of decision-making. In P. C. Humphreys, O. Svenson, and
A Vari (Eds.), Analyzing and aiding decision processes. Amsterdam: North-Holland.
343– 369.
Montgomery, H. (1993). The search for a dominance structure in decision-making:
Examining the evidence. In G.A. Klein, J. Orasanu, R. Calderwood, and C. E. Zsambok
(Eds.), Decision-making in action: Models and methods. Norwood, N.J.: Ablex. 182–
187.
Schwartz, B., Ward, A., Monterosso, J., Lyubomirsky, S., White, K. and Lehman, D. R.
(2002). “Maximizing versus satisficing: Happiness is a matter of choice.” Journal of Personality and Social Psychology. 83, 1178–1197.
Takemura, K. (2000). “Vagueness in Human Judgment and Decision Making”, In Z. Q.
Liu and S. Miyamoto, Soft Computing for Human Centered Machines, Tokyo: Springer
Verlag. 249-281.
Takemura, K. (2014), Behavioral decision theory: Mathematical and psychological
descriptions of human choice behavior, New York: Springer,
Tversky, A. and Kahneman, D. (1981). “The framing decisions and the psychology of
choice”, Science. 211, 453–458.
Tversky, A. and Kahneman, D. (1992). “Advances in the prospect theory: Cumulative
representation of uncertainty”, Journal of Risk and Uncertainty. 5, 297–323.
Tversky, A. and Wakker, P. (1995). “Risk attitudes and decision weight”, Econometrica.
63, 1255–1280.
Wu, G. and Gonzalez, R. (1996). “Curvature of the probability weighting function”,
Management Science. 42, 1676–1690.
- Teacher: Hélène Duci
- Teacher: Kazuhisa Takemura