98756 - BEHAVIORAL DECISION MAKING

Learning outcomes

This course is intended to allow students to become familiar with the literature in behavioral economics and decision making. The course has two facets: first it will uncover the inner workings of human biases and judgment and the students will gain insights into how inherent bias or poorly structured information can affect business decisions. Second, it will provide students with practical advice about applying these findings to topics in marketing, management, and finance.

Course contents

1. From economic men to behavioral decision making
2. Human biases and emotional states: Systematic error in decision making?
3. Perception of risks and decision making under uncertainty
4. Intertemporal decision making: the sophisticated and naïve decision makers
5. Mental accounting and sunk costs.
6. Motives and Motivational Bias
7. Group Decision Making and social influence
8. Nudging: Understanding of choice architecture
9. Experimentation and data to optimize performance
10. How businesses and governments are using behavioral economics to design decision making

Readings/Bibliography

Angner. A. (2021) A Course in Behavioral Economics, London: Palgrave Macmillan, 2021, 3. , p. 327

Kahneman, D. (2011). Thinking Fast and Slow. New York: Farrar, Straus and Giroux.

Thaler, R. and Sunstein, C. (2009) Nudge: Improving Decisions about Health, Wealth and Happiness, London: Penguin.

Additional readings will be provided by the teacher during the course.

Lecture notes:

The lecture notes will be made available on the IOL platform before each class (but might be corrected/updated shortly after the class). They should NOT be taken as the only reference, as they often do not cover the analytical details discussed in the manual, which are important for a thorough understanding of the subject matter.

Teaching methods

Lectures will be based on slides and other teaching materials.

Students are invited to read in advance the suggested readings and they are encouraged to actively participate to the discussion in class.

Assessment methods

All (attending and non-attending students) will be evaluated with a written exam based on multiple choice questions and open questions.

The dates of the final exams are fixed and cannot be changed. Requests for additional dates will not be accepted.

The maximum possible grade is 30 cum laude. The grading scale is the following:

<18: Fail
18-23: Sufficient
24-27: Good
28-29: Very good
30: Excellent
30 cum laude: Outstanding (the instructor was impressed)

Grade rejection: students can reject the grade obtained at the exam only once. To this end, they must email a request to the instructor within the date set for registration. The instructor will confirm reception of the request within the same date.

Teaching tools

The Virtuale platform will provide the following resources:

• Updated information and notices
  
• Lecture notes
• Research articles

Office hours

See the website of Natalia Montinari