Neuroeconomics & Decision Science
Niveau
Master
Learning outcomes of the courses/module
The participants:
• know key concepts and models of neuroeconomics and decision science.
• understand cognitive, emotional, and neural foundations of decision-making.
• apply behavioral economic and neuroeconomic approaches to real-world decision problems.
• analyze decision-making behavior under uncertainty, risk, and social influences.
• critically evaluate empirical studies and methods in neuroeconomics.
• develop well-founded interpretations and applications for business, organizations, and society.
• know key concepts and models of neuroeconomics and decision science.
• understand cognitive, emotional, and neural foundations of decision-making.
• apply behavioral economic and neuroeconomic approaches to real-world decision problems.
• analyze decision-making behavior under uncertainty, risk, and social influences.
• critically evaluate empirical studies and methods in neuroeconomics.
• develop well-founded interpretations and applications for business, organizations, and society.
Prerequisites for the course
None
Course content
• Introduction & Foundations (neuroeconomics as an interdisciplinary field of economics, psychology, and neuroscience; decision models vs. actual behavior)
• Behavioral Economics (bounded rationality; heuristics & biases; social preferences; decisions under risk and uncertainty)
• Neuroscientific Foundations (brain structures; reward and emotion systems; neural processes of decision-making)
• Biological Influences (hormones; neurotransmitters; individual differences in decision-making behavior)
• Decisions in Context (emotions; time; social interaction; framing effects; environmental factors)
• Neuroeconomic Methods (experiments; behavioral data; basic neuroscientific measurement methods such as fMRI/EEG – conceptual)
• Applications (financial decisions; consumer behavior; neuromarketing; organizations and management)
• Integration & Interdisciplinary Approaches (linking behavior, brain, and economic models)
• Criticism & Limitations (methodological, theoretical, and ethical challenges of neuroeconomics)
• Behavioral Economics (bounded rationality; heuristics & biases; social preferences; decisions under risk and uncertainty)
• Neuroscientific Foundations (brain structures; reward and emotion systems; neural processes of decision-making)
• Biological Influences (hormones; neurotransmitters; individual differences in decision-making behavior)
• Decisions in Context (emotions; time; social interaction; framing effects; environmental factors)
• Neuroeconomic Methods (experiments; behavioral data; basic neuroscientific measurement methods such as fMRI/EEG – conceptual)
• Applications (financial decisions; consumer behavior; neuromarketing; organizations and management)
• Integration & Interdisciplinary Approaches (linking behavior, brain, and economic models)
• Criticism & Limitations (methodological, theoretical, and ethical challenges of neuroeconomics)
Recommended specialist literature
• Dreher, L. (2022). Neuroökonomie: Eine wissenschaftstheoretische Analyse. Wiesbaden: Springer.
• González, J., Arguello, K., & Mendoza, C. (2025). Neuroeconomics: The bridge between the market and the mind. London, UK: Sciencia Scripts.
• Peyrolón, P. (2020). Grundzüge der Neuroökonomie: So entstehen Entscheidungen. Wiesbaden: Springer.
• Pfister, K.-R., Jungermann, H., & Fischer, K. (2017). Die Psychologie der Entscheidung: Eine Einführung. Berlin: Springer.
• Reuter, M., & Montag, C. (2018) (Hrsg.). Neuroeconomics. Berlin: Springer.
• González, J., Arguello, K., & Mendoza, C. (2025). Neuroeconomics: The bridge between the market and the mind. London, UK: Sciencia Scripts.
• Peyrolón, P. (2020). Grundzüge der Neuroökonomie: So entstehen Entscheidungen. Wiesbaden: Springer.
• Pfister, K.-R., Jungermann, H., & Fischer, K. (2017). Die Psychologie der Entscheidung: Eine Einführung. Berlin: Springer.
• Reuter, M., & Montag, C. (2018) (Hrsg.). Neuroeconomics. Berlin: Springer.
Assessment methods and criteria
Exam
Presentation
Presentation
Language
German
Number of ECTS credits awarded
6
Semester hours per week
Planned teaching and learning method
The course is based on an e-learning concept that incorporates a didactically aligned combination of online and in-person phases. During the online phases, an inductive learning approach is applied, fostering the independent acquisition of knowledge and the completion of tasks. The in-person phases follow a deductive approach, in which learning processes are guided and deepened, and content is systematically delivered through lectures as well as practical examples.
Semester/trimester in which the course/module is offered
2