February 25, 2020
About me
I have a strong interest in methods that facilitate high quality research: reproducible, replicable, relevant, and communicated in a clear and responsible manner also to non-scientific audiences. In terms of substantive interests, my research focuses on dynamic aspects of consumer decision making, more specifically on how preferences evolve over time until a final choice is expressed. In order to gain access to these latent processes, I am using dynamic Bayesian models calibrated on eye-tracking data, building on research in neuroeconomics that supports a strong link between attention and decision making. These models combine features of machine learning, multilevel latent growth, and choice models to infer the build-up of preferences from changes in attention. The aim is to understand how consumers make decisions, and to be able to predict future choices before they are implemented.
Expertise
