Ontology highlight
ABSTRACT:
SUBMITTER: Bruch E
PROVIDER: S-EPMC5035909 | biostudies-other | 2016 Sep
REPOSITORIES: biostudies-other
Proceedings of the National Academy of Sciences of the United States of America 20160830 38
This paper presents a statistical framework for harnessing online activity data to better understand how people make decisions. Building on insights from cognitive science and decision theory, we develop a discrete choice model that allows for exploratory behavior and multiple stages of decision making, with different rules enacted at each stage. Critically, the approach can identify if and when people invoke noncompensatory screeners that eliminate large swaths of alternatives from detailed con ...[more]