363-1194-00L  An Introduction to Experiments in Consumer Behavior

Courses

Catalogue data

Abstract	Designed for master students, this course offers insights and practical experience in behavioral economics and marketing experiments. It includes: 1) Mastering experiment design (RCT, A/B testing, conjoint analysis), programming, and implementation of experiment through focused lectures. 2) Selecting a seminal experiment, replicating it, and presenting a poster on the key findings.
Learning objective	After taking a course, students will be able to: - design a simple (online) experiment with an open-source program, hands-on preregistration/replication - recruit participants - basic data analysis and analytical skills (in R) - present (a poster) and discussion skills - collaboratively work in groups
Content	The course is especially suitable for master students who plan to conduct empirical research for their master thesis, or students who wish to get hands-on experiences with experimental methods. The objective is to provide students with the theoretical foundations for designing, implementing, conducting, and analyzing experiments, and hands-on experiences on empirical methods in behavioral economics or marketing (consumer behavior focus). After a brief recap of the counterfactual approach to causal inference and experimental designs, the course will cover the theoretical and practical aspects of designing and conducting survey experiments. The course will be divided in two stages. In stage 1 (theoretical part), students will learn how to design, plan, program, and run an experiment by attending to lectures. In stage 2 (practical part), students will work in a group, and choose one experiment in the area of behavioral economics or marketing, conduct a replication of that experiment using the techniques acquired in stage 1, and make and present a poster on the results of the replication. Performance in both, the theoretical and the practical part contribute equally to the final grade. In more detail, 50% of the final grade will be based on regular assignments that have to be submitted online prior to class (25%), and active participation during the weekly meetings (25%). The 50% of the grade will be based on the quality of the conducted research project (experimental design, data collection, statistical analysis) and the final presentation on the last day of class. Upon completion of this course, students will be equipped with a robust set of skills. They will learn to design simple online experiments using open-source programs, emphasizing hands-on preregistration and replication methods. Students will also acquire the competence to recruit participants effectively, and hands-on experiences with basic data analysis and analytical skills, utilizing R, a powerful tool for statistical computing and graphics. Essential to the dissemination of research, students will enhance their ability to present findings and engage in scholarly discussions through poster presentations. Furthermore, this course emphasizes the importance of teamwork, preparing students to collaboratively work in groups, an essential skill in both academic and professional settings.
Competencies	Subject-specific Competencies Concepts and Theories fostered Techniques and Technologies assessed Method-specific Competencies Analytical Competencies assessed Decision-making assessed Media and Digital Technologies fostered Problem-solving fostered Project Management assessed Social Competencies Communication assessed Cooperation and Teamwork assessed Customer Orientation assessed Leadership and Responsibility fostered Self-presentation and Social Influence fostered Sensitivity to Diversity fostered Personal Competencies Adaptability and Flexibility assessed Creative Thinking assessed Critical Thinking assessed Integrity and Work Ethics fostered Self-awareness and Self-reflection assessed Self-direction and Self-management assessed

Performance assessment

Performance assessment information (valid until the course unit is held again)
Performance assessment as a semester course
ECTS credits	3 credits
Examiners	U. Bernardic
Type	graded semester performance
Language of examination	English
Repetition	Repetition only possible after re-enrolling for the course unit.
Additional information on mode of examination	Performance in both, the theoretical and the practical part contribute equally to the final grade. 50% of the final grade will be based on regular assignments that have to be submitted online prior to class (25%), and active participation during the weekly meetings (25%). The 50% of the grade will be based on the quality of the conducted research project (experimental design, data collection, statistical analysis) and the final presentation on the last day of class.

Learning materials

Groups

Restrictions

Offered in

Programme	Section	Type
Management, Technology and Economics Master	Natural Resources	W