17O Predicting Experiential (Vs. Monetary) Risk Preferences From Consumers’ Memory: a Behavioral and Neuroimaging Experiment

This experiment shows that risk preferences for everyday consumption experiences (vs. those for money) can be predicted based on neuroimaging data. We apply recent advances in deep learning to model the neurophysiological representations associated with experiential choices, showing that deep learning predicts choice more accurately than traditional machine-learning methods.



Citation:

Chinmai Basavaraj, Martin Reimann, Kobus Barnard, and Michael Norton (2019) ,"17O Predicting Experiential (Vs. Monetary) Risk Preferences From Consumers’ Memory: a Behavioral and Neuroimaging Experiment", in NA - Advances in Consumer Research Volume 47, eds. Rajesh Bagchi, Lauren Block, and Leonard Lee, Duluth, MN : Association for Consumer Research, Pages: 958-958.

Authors

Chinmai Basavaraj, University of Arizona, USA
Martin Reimann, University of Arizona, USA
Kobus Barnard, University of Arizona, USA
Michael Norton, Harvard Business School, USA



Volume

NA - Advances in Consumer Research Volume 47 | 2019



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