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Heuristic Decision Making Strategies

  • Teacher(s):   J.Marewski  
  • Course given in: English
  • ECTS Credits: 6 credits
  • Schedule: Autumn Semester 2019-2020, 4.0h. course (weekly average)
  •  séances
  • site web du cours course website
  • Related programmes:
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    Master of Science (MSc) in Management, Orientation Business Analytics

    Maîtrise universitaire ès Sciences en management, Orientation Behaviour, Economics and Evolution

    Master of Science (MSc) in Management, Orientation Marketing

[warning] This course syllabus is currently edited by the professor in charge. Please come back in a few days. --- For your information only, here is the old syllabus :


In the real world, decision makers often have incomplete or uncertain information. Not all options, their consequences, and probability of occurrence might be knowable and it might be impossible to reliably estimate them. Moreover, decision tasks themselves can be fuzzy, and decision makers might be able to rely on rather limited information-processing capacities. Models for managing such situations of uncertainty are heuristics. Heuristics are simple decision making strategies that ignore information. In so doing, they reduce complexity and aid humans and other animals make accurate, fast, or otherwise adaptive decisions. Heuristics can yield adaptive decisions, because they exploit both the structure of information available in the environment and the workings of basic cognitive capacities, such as memory or perception.

This course teaches cutting-edge research on heuristic decision making strategies, focusing on theory and research methodology. In so doing, the course takes a scientific lens: the course is designed to introduce students to, and aid them to prepare for, research activities-- be they carried out in academia itself, or in a company setting. Particularly, the course also targets those students who might want to pursue doctoral studies or who are already pursuing doctoral studies on topic areas related to decision making (be it e.g., management, strategy, organizational behavior, behavioral economics, marketing, finance, human cognition, biology, or some other topic area). Overall, the course offers a stimulating environment for those who want to grow, intellectually, by diving into the world of science.

The course has three interrelated goals.

First, the course aims to introduce students to the scientific literature on decision making processes. Particularly, students will become familiar with the fast-and-frugal heuristics research program for studying decision making (e.g., Gigerenzer, Todd, & the ABC Research Group, 1999). Originally developed in the cognitive and decision sciences, this framework has found applications in many areas, including business, medicine, crime, aviation, and sports, to name but a few (see e.g., Gigerenzer, Hertwig, & Pachur, 2011). This course will acquaint students with the basics of research on heuristics, introduce different areas of research on heuristics, and finally allow them to focus on one area that is of specific interest to them – be it strategy consulting, marketing, business intelligence, financial investment, management, animal cognition, or something else.

Second, the fast-and-frugal heuristics research program breaks up conventional disciplinary boundaries. Research on fast-and-frugal heuristics is not only applied to many fields other than the cognitive and decision sciences; it is also informed by research from many different disciplines, including the computer sciences, biology, and economics, to offer just a few examples. Similarly, that line of research makes use of different scientific methods, ranging from detailed computational model building to mathematical analysis, and encompassing both field studies and experimental work. The course will thus allow students to be introduced to different streams thinking and scientific inquiry, this way broadening horizons and perspectives on behavioral research. For instance, outside of research on humans, we might cover aspects of animal (e.g., Chimpanzee) cognition and foraging behavior. Similarly, in leaving the realm of business and economic research, we might turn to the decision-making aspects of medical diagnosis and airplane flying. In terms of methodological aspects, students will be introduced to important statistical notions, including model complexity/flexibility, overfitting, robustness, generalizability, and the bias-variance-dilemma. To drop a few more examples, students learn about model selection, model recovery, and signal detection theory; and they might become acquainted with Egon Brunswik’s notion of representative experimental design (which speaks to the distinction between external and internal validity).

Third, in covering the scientific literature on a particular topic (i.e., decision making processes) the course aims to offer students an opportunity to improve their (e.g., academic) writing and presentation skills, this way endowing them with an opportunity to acquire skills useful for setting up their own research projects, be in the realm of their Master thesis, a doctoral dissertation, or a company-project.


Research on heuristics focuses on four interrelated questions.

Descriptive: What heuristics do humans and other animals use?

Ecological: In what environment does each heuristic yield clever decisions, and when will it fail?

Applied: How can decision making be improved, for instance, by changing the heuristics people rely upon or by changing their environment?

Methodological: How can the usage and performance of heuristics be studied, for example, in experiments, with computer simulations, or via mathematical analyses?

In this course, we will cover research on all four questions. Specifically, after an overview on different theories of decision making, we will start out by trying to search for answers for the descriptive and the ecological questions. Thereafter, we will cover different areas of applied research, ranging from medicine to business and crime. Finally, students will dig deeper into a topic of their own choice. Within the chosen areas of specialization, students will develop a research project. Tangible outcome of this project development phase include formulating a research proposal or, for advanced students (e.g., PhD students), the possibility of doing actual empirical work, to be written up in a project report (e.g., a short journal article draft).

Teaching method:

Most sessions of this course are set up as an academic discussion seminar. Prior to the different sessions, we will read selected materials (e.g., scientific articles), and then discuss those together in class. The idea is that course participants acquire knowledge not only by reading and thinking for themselves, but also by discussing and reflecting as a group. Depending on participants’ needs, those discussion sessions will come accompanied by presentations. As the course progresses, those discussion sessions are meant to inspire students to develop a research project on their own, with later sessions in the course allowing students to get feedback on their projects.


Participants are required to read all assigned papers prior to the sessions in which the corresponding papers will be discussed. This preparation is essential for verbally participating in the class discussion (which is graded; see below), following the course contents, and acquiring knowledge.

To further facilitate the learning process, all participants will be grouped into teams for the duration of the course. The teams are expected to meet in order to prepare the assigned papers together, and to recapitulate them were needed. The members of each team will be expected to help each other. The teams will also work on group tasks together, notably a presentation on one of the areas of research covered in this course (graded; see below).

Students’ efforts will culminate in developing their own research project. While students are free to choose their own topic, the topic itself will come out of the course contents. Project development will happen throughout the semester, and not during the break. That is, students are required to consistently work on development of their project, including by seeking out additional literature whenever needed. Put differently, the course sets opportunities for developing a project, including by providing first pointers to the relevant literature and by offering an environment for reflection and discussion. But just like in regular research activities outside of course settings, the course set-up cannot (and is not meant to) replace independent inquiries into the literature, and persistent, self-managed work. Students are expected to not only manage (parts of) their knowledge acquisition independently; they should also be prepared to manage their time throughout the semester wisely so that they can, by the end of course, submit a written report (graded; see below) on their chosen research topic.

Finally, participants are required to give spontaneous (ungraded) presentations on the course topics, to coordinate and lead the class discussions, and to produce various pieces of writing, including summaries and critical reflections of readings.

Overall, this course places emphasis on self-responsible and independent (and hence largely intrinsically motivated) efforts for learning. In short, students attending this course are expected to be motivated to seek out and create learning opportunities for themselves, and the course is meant to give them a platform for doing so.


Required readings:

Compulsory readings for this course are selected journal articles and chapters from books. References to those materials will be given in class by the instructor. Other “compulsory” readings will be chosen by the students themselves, namely in order to develop their research projects.

From the instructor’s side, among others we will focus on articles that are included in the following collection:

Gigerenzer, G., Hertwig, R., & Pachur, T. (Eds.). (2011). Heuristics: The foundations of adaptive behavior. New York: Oxford University Press.

We will also consult chapters in a series of books on fast-and-frugal heuristics. A foundational book is:

Gigerenzer, G., Todd, P. M., & the ABC Group (1999). Simple heuristics that make us smart. New York: Oxford University Press.

Students who wish to read up (e.g. already prior to the course) more on heuristics on heuristics (e.g., in order to find out if they would be interested in taking the course), can get introductions to the fast-and-frugal heuristics research program here:

A general overview:

Gigerenzer, G., & Gaissmaier, W. (2011). Heuristic decision making. Annual Review of Psychology, 62, 451–482.

An overview of applications (e.g., ranging from business to medicine):

Hafenbrädl, S., Waeger, D., Marewski, J. N., & Gigerenzer, G. (2016). Applied decision making with fast-and-frugal heuristics. Journal of Applied Research in Memory and Cognition, 5, 215-231.

Popular (non-scientific) books on the fast-and-frugal heuristics research program do not form part of the required readings for this course, yet also such books might aid potential course participants to decide if they are interested in following this course:

Gigerenzer, G. (2014). Risk savvy: How to make good decisions. New York: Viking.

Gigerenzer, G. (2007). Gut feelings: The intelligence of the unconscious. New York: Viking Press.

Gigerenzer, G. (2002). Calculated risks: How to know when numbers deceive you. New York: Simon & Schuster.


This course does not come with specific requirements in terms of prior knowledge and skills. As a matter of fact, the course is open to both students who are completely unfamiliar with the decision sciences as well as to students who have had ample prior exposure to corresponding research. While the course specifically targets students who are interested in a career in academia (e.g., PhD students and those who might be interesting in pursuing a PhD), the course will also be particularly useful for those who plan to have a career outside of academia, for instance, by introducing those students to usable knowledge on how to steer and improve their and others’ decision making (e.g., in management, strategy, marketing, governance, or finance), or by offering opportunities to acquire, practice, and refine important skills, such as presenting in front of group, searching for relevant literature, understanding data, or writing clearly.



First attempt

Without exam (cf. terms)  

The final grade depends on:

- individual verbal participation during class (30%),

- individual written report on a research project (50%), and

- group presentations in class (20%).

Except for the group presentations, all grades are assigned as a function of individual performance. The group presentations are team work. The grade of the team applies to all team members.

The participation grade (30%) hinges on the in-depth preparation of the materials for each session. In order to receive satisfactory evaluations, participants are requested to demonstrate via active in-class verbal participation (i.e., speaking up in the class discussion) that they have read and critically reflected upon on the materials.

Also individual presentations participants might give contribute to their verbal participation. Such individual presentations include formal project reports as they might be given, for instance, in an academic or company setting, and more informal “feedback presentations”, that aim at obtaining helpful comments, ideas, and insights form the class in order to advance a research project.

The individual written report on a research project (50%) focuses on one of the topics covered in the course. The report represents, in a way, a tangible outcome of the students’ reflections during the semester. Each student chooses her or his own research topic from those covered in the course. The written report on that research topic can take two forms. First, the report can come as a concrete research proposal for work that has not yet been done, but that the student would like to conduct. Such research proposals can be set up, for instance, like applications to scientific funding agencies, or like research plans written in a company context. Second, the report can cover actual (e.g., exploratory) research conducted by the student during the course. Such a report can be set up, for example, like a short scientific article. In both cases (i.e., proposal for research to be conducted or summary of actual research) the report includes a discussion of the relevant scientific literature (including theory, models, and methodology), (possible) predictions and results, (envisioned) methods, (envisioned) implications and limitations. In addition to a written report, students must be prepared to present their project verbally in class if they are asked to do so. PhD students who wish to take this course as part of their PhD studies will be required to develop their respective research projects in more depth than Master students. Moreover, PhD students’ research reports will be submitted to stricter evaluation criteria concerning the treatment of the relevant scientific literature (including theory, models, and methodology), (possible) predictions and results, (envisioned) methods, and (envisioned) implications and limitations.

Graded group presentations (20%) are short introductions to the various areas of research we will cover in class. Such presentation also include managing clarification and discussion questions from other students. The precise topic (and hence content) of those presentations will be determined during the course.



Without exam (cf. terms)  

In case of a retake, 50% of the grade (individual verbal participation, group presentation) will be retained. A new individual written report on a research project will have to be submitted.

In the exceptional event that a pass cannot be obtained by writing a new individual report on a research project, then also the individual participation grade (30%) can be re-assessed. In this case, individual participation grading will be replaced by an individual oral examination.

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