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The similarity heuristic
Author(s) -
Read Daniel,
GrushkaCockayne Yael
Publication year - 2011
Publication title -
journal of behavioral decision making
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.136
H-Index - 76
eISSN - 1099-0771
pISSN - 0894-3257
DOI - 10.1002/bdm.679
Subject(s) - heuristics , representativeness heuristic , heuristic , similarity (geometry) , computer science , social heuristics , artificial intelligence , machine learning , mathematics , statistics , social competence , economics , image (mathematics) , social change , economic growth , operating system
Decision makers often make snap judgments using fast‐and‐frugal decision rules called cognitive heuristics. Research into cognitive heuristics has been divided into two camps. One camp has emphasized the limitations and biases produced by the heuristics; another has focused on the accuracy of heuristics and their ecological validity. In this paper we investigate a heuristic proposed by the first camp, using the methods of the second. We investigate a subset of the representativeness heuristic we call the “similarity” heuristic, whereby decision makers who use it judge the likelihood that an instance is a member of one category rather than another by the degree to which it is similar to others in that category. We provide a mathematical model of the heuristic and test it experimentally in a trinomial environment. In this environment, the similarity heuristic turns out to be a reliable and accurate choice rule and both choice and response time data suggest it is also how choices are made. We conclude with a theoretical discussion of how our work fits in the broader “fast‐and‐frugal” heuristics program, and of the boundary conditions for the similarity heuristic. Copyright © 2009 John Wiley & Sons, Ltd.