TY - GEN
T1 - Rational Inattention in Choice Overload
T2 - 55th Asilomar Conference on Signals, Systems and Computers, ACSSC 2021
AU - Sharma, Pankaj
AU - Varshney, Lav R.
N1 - Publisher Copyright:
© 2021 IEEE.
PY - 2021
Y1 - 2021
N2 - Discrete choice models in economics are often used to mathematically model the heuristic approaches that people use in decision-making. When faced with a large number of choices, however, people face information costs that lead to choice overload. Within the discrete choice framework, here we formulate a quantization-theoretic approach to optimally cluster choices into categories. This is a non-asymptotic form of rational inattention theory. Drawing on a recent equivalence result between discrete choice models and Bregman divergences, and on properties of Bregman clustering, our main result is that the same clustering algorithm is universally optimal for any additive random utility discrete choice model. Examples are given and hierarchical clustering is also discussed.
AB - Discrete choice models in economics are often used to mathematically model the heuristic approaches that people use in decision-making. When faced with a large number of choices, however, people face information costs that lead to choice overload. Within the discrete choice framework, here we formulate a quantization-theoretic approach to optimally cluster choices into categories. This is a non-asymptotic form of rational inattention theory. Drawing on a recent equivalence result between discrete choice models and Bregman divergences, and on properties of Bregman clustering, our main result is that the same clustering algorithm is universally optimal for any additive random utility discrete choice model. Examples are given and hierarchical clustering is also discussed.
KW - Bregman divergence
KW - clustering
KW - discrete choice models
KW - rational inattention theory
UR - http://www.scopus.com/inward/record.url?scp=85127079977&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85127079977&partnerID=8YFLogxK
U2 - 10.1109/IEEECONF53345.2021.9723230
DO - 10.1109/IEEECONF53345.2021.9723230
M3 - Conference contribution
AN - SCOPUS:85127079977
T3 - Conference Record - Asilomar Conference on Signals, Systems and Computers
SP - 1297
EP - 1301
BT - 55th Asilomar Conference on Signals, Systems and Computers, ACSSC 2021
A2 - Matthews, Michael B.
PB - IEEE Computer Society
Y2 - 31 October 2021 through 3 November 2021
ER -