Dr Barbara Fasolo

This course is compulsory on the Executive MSc in Behavioural Science. This course is not available as an outside option.

This course introduces students to Behavioural Decision Science: the science that explains and predicts how humans make decisions (the decision ‘process’) and how well (the decision ‘outcome’). The course will focus on the process, and unveil the subtle and sometimes unconscious influences played by our mind (biases) and the context in which decisions are faced: What has been chosen in the past? Is there positive or negative affect - perhaps because of risk and uncertainty? Can AI be involved? All of these (and more) are factors that often determine how information is searched before choosing, how decisions are made, and the quality of the decision made.

In this course, you will be guided to the scientific language of decisions, judgments and biases. Each day you will work as a group and apply the steps of our proprietary tool ‘Decision Canvas’ to improve a real decision that you will select, applying different behavioural interventions – from ‘process nudges’ to ‘debiasing’ and ‘choice architecture.

The course is entirely seminar-based and balances theory, evidence and experience. It involves group-work throughout the course. We will alternate teaching with interactive activities designed to observe and feel the process of decision making from the ‘inside’, before reviewing behavioural decision theories and evidence from lab and field studies.

The assessment is designed to give students the opportunity to work as a group and apply their new skills to support a real decision, as well as produce, individually, a rigorous and scholarly report on a specific aspect of decision making, of their interest.

15 hours of lectures and 8 hours of seminars in the MT.

The formative assignment will take place on the final day of the course after all the lectures and seminars have been completed. The assignment will consist of a plenary presentation in which students divided into small groups will be asked to give a short presentation discussing an intervention that can be used to tackle the most important biases in a decision making problem of their choice. Student groups will develop their plenary presentations during seminars while interacting with the course teachers and other students. The formative feedback will be given at a team level, and will focus on the rigour and use of behavioural science concepts learned in the course.

Bazerman, M. (2017) Judgment in Managerial Decision Making. New York: Wiley. 8th edition;

Kahneman, D. (2011) Thinking Fast and Slow. London: Allen Lane;

Russo, J. E. & Schoemaker, P. J. H. (2002) Winning decisions: How to make the right decision the first time, Piatkus Publ. Limited.

Larrick, R.P. (2004). Debiasing (Chapter 16). In D.J. Koehler, & N. Harvey, Blackwell Handbook of Judgement and Decision Making. Malden: Blackwell Publishing

Coursework (100%, 3000 words) in the MT.

The summative assignment consists of two parts. In Part 1 (no more than 1,000 words), you will be asked to report on the decision, the bias and behavioural interventions recommended within the ‘Decision Canvas’ work that you did with your group. Part 2 (no more than 2,000 words) will be an essay where you will zoom in on a particular aspect of the decision process (e.g. decision frame, a judgement, a bias, a de-biasing or choice architecture technique) which you as a developing behavioural scientist have found intriguing and important (be it as a ‘buddy’ or as a ‘decision maker’). This is done in a scholarly and rigorous manner. Part 1 will count for 25% of your mark while 75% will come from Part 2. You will be required to provide full essay-style referencing. Although the summative assignment will tackle the decision problems presented in groups, all students will write both parts of the summative assessment on their own and receive an individual mark.

Some departments have produced short videos to introduce their courses. Please refer to the course selection videos index page for further information.