Senior Research Scientist
Center for Adaptive Rationality
Phone: +49 30 82406-335
- Habilitation, 2012, University of Basel
- Dr. phil., 2006, Freie Universität Berlin
- Dipl.-Psych., 2002, Freie Universität Berlin
- MSc Health Psychology, 2002, University of Sussex
We often make decisions without having definite knowledge of the consequences that will follow from the decision—such as when choosing between stocks, mates, or medical treatments. I am interested the cognitive processes that underlie these decisions under risk. For instance, to what extent do decision makers trade off the possible consequences of an option with their probabilities of occurring? How do the cognitive processes deviate from a rational expectation calculus? And how does risky decision making change across the life span? Further issues are the role of affect and emotions in these decisions, and how different modeling approaches to risky choice relate to each other.
The Development of Decision Making Across the Life Span
Decision making taps into a variety of cognitive and affective functions. These functions are, to different degrees, subject to development and change from childhood to adolescence, and from young adulthood and to old age. I study how people at different stages of the life span differ in their judgment and decision making—including estimation, inference, preferential choice, intertemporal, and risky choice—and how these changes are linked to dynamics in the underlying cognitive and affective functions. For instance, how does the higher positive affect reported by older adults (relative to younger adults) impact their willingness to take a risk?
How Attention Guides Decisions
Before making a decision, we typically search for relevant information, either in memory or externally; subsequently, the acquired information is processed. These processes are accompanied by attentional processes, which can be measured by eye tracking or other process-tracing methodologies. In my research, I try to understand how attentional processes and subsequent decisions are linked. Can we predict what decision a person will make based on the patterns of attention allocation before a choice? How do decision makers decide when to stop information search? Which processes shape search in memory (e.g., controlled search vs. automatic activation) and what are the brain mechanisms involved?
Decision Making in a Social World
To make inferences about the world—such as when judging the prevalence of health risks, or consumer preferences—we often use observations from among the people we know. I study how our social memories are structured and how these structures guide search processes within our social memories. Finally, I am interested in how cooperation is affected by the structure of social networks—that is, whether social contacts are distributed equally across network members or mainly focused on a few members.
Adaptive Decision Making
The information processing steps preceding a decision can be described as cognitive strategies. The mind has a repertoire—or toolbox—of different strategies available that are most suitable under different circumstances and serve different purposes. In my research, I try to understand under which conditions the different strategies are selected. When do people use simple strategies, and when more elaborate strategies? Why do simple strategies often work rather well—for instance, by exploiting systematic structures in the world? How do people learn which strategy to use and which cognitive abilities are involved in strategy selection and execution? How do experts and novices differ in their strategy selection?
- Hertwig, R., Pleskac, T. J., Pachur, T., & the Center for Adaptive Rationality (2019). Taming uncertainty. Boston, MA: MIT Press.
- Dai, J., Pachur, T., Pleskac, T. J., & Hertwig, R. (in press). What the future holds and when: A description-experience gap in intertemporal choice. Psychological Science, 30, 1218–1233.
- Pachur, T., Schulte-Mecklenbeck, M., Murphy, R. O., & Hertwig, R. (2018). Prospect theory reflects selective allocation of attention. Journal of Experimental Psychology: General, 147 , 147-169.
- Fechner, H. B., Schooler, L. J., & Pachur, T. (2018). Cognitive costs of decision-making strategies: A resource demand decomposition with a cognitive architecture. Cognition, 170, 102-122.
- Stevens, J. R., Woike, J. K., Schooler, L. J., Lindner, S., & Pachur, T. (2018). Social contact patterns can buffer costs of forgetting in the evolution of cooperation. Proceedings of the Royal Society of London: B, Biological Sciences, 285:20180407.
- Pachur, T., Mata, R., & Hertwig, R. (2017). Who dares, who errs? Disentangling cognitive and motivational roots of age differences in decisions under risk. Psychological Science, 28, 504-518.
- Yechiam, E., Ashby, N. J. S., & Pachur, T. (2017). Who’s biased? A meta-analysis of buyer-seller differences in the pricing of lotteries. Psychological Bulletin, 143, 543–563.
- Pachur, T., Suter, R. S., & Hertwig, R. (2017). How the twain can meet: Prospect theory and models of heuristics in risky choice. Cognitive Psychology, 93, 44-73 .
- Kellen, D., Pachur, T., & Hertwig, R. (2016). How (in)variant are subjective representations of described and experienced risk and rewards? Cognition, 157, 126-138.
- Khader, P., Pachur, T., Weber, L., & Jost, K. (2016). Neural signatures of controlled and automatic retrieval processes in memory-based decision making. Journal of Cognitive Neuroscience, 28, 69–83.
- Horn, S. S., Ruggeri, A., & Pachur, T. (2016). The development of adaptive decision making: Recognition-based inference in children and adolescents. Developmental Psychology, 52, 1470-1485.
- Pachur, T., Hertwig, R., & Wolkewitz, R. (2014). The affect gap in risky choice: Affect-rich outcomes attenuate attention to probability information. Decision, 1, 64-78.
- Pachur, T., & Olsson, H. (2012). Type of learning task impacts performance and strategy selection in decision making. Cognitive Psychology, 65, 207-240.
- Pachur, T., & Scheibehenne, B. (2012). Constructing preference from experience: The endowment effect reflected in external information search. Journal of Experimental Psychology: Learning, Memory and Cognition, 38, 1108-1116.
- Glöckner, A., & Pachur, T. (2012). Cognitive models of risky choice: Parameter stability and predictive accuracy of prospect theory. Cognition, 123, 21-32.
- Gigerenzer, G., Hertwig, R., & Pachur, T. (Eds.) (2011). Heuristics: The foundations of adaptive behavior. NewYork: Oxford University Press.
- Pachur, T. (2010). Recognition-based inference: When is less more in the real world? Psychonomic Bulletin and Review, 17, 589-598.
- Pachur, T., Mata, R., & Schooler, L. J. (2009). Cognitive aging and the use of recognition in decision making. Psychology and Aging, 24, 901-915.
- Pachur, T., & Hertwig, R. (2006). On the psychology of the recognition heuristic: Retrieval primacy as a key determinant of its use. Journal of Experimental Psychology: Learning, Memory, and Cognition, 32, 983-1002.