Complexity and Choice

10/12/2021 10:00 am 10/12/2021 11:00 am Australia/Melbourne Complexity and Choice

Presented by Jörg Spenkuch (Northwestern University) with Y. Salant

We study two dimensions of complexity that may interfere with individual choice. The first one is object complexity, which corresponds to the difficulty of evaluating any given alternative in the choice set. The second dimension is composition complexity, which increases when suboptimal alternatives become more similar to optimal ones.

We develop a satisficing-with-evaluation-errors theory that incorporates both dimensions and delivers sharp empirical predictions about their effect on choice behavior. We confirm these predictions in a novel data set with information on hundreds of millions of decisions in chess endgames. First, as the object complexity of an optimal (suboptimal) alternative increases, it becomes less (more) likely to be chosen. Second, even highly experienced decision-makers are more likely to make mistakes when choosing from sets with higher composition complexity.

These findings help to shed some of the first light on the effect of complexity on choice behavior outside of the laboratory.

Speaker

Jörg Spenkuch (Northwestern University)

Jörg Spenkuch is Associate Professor of Managerial Economics and Decision Sciences at the Kellogg School of Management, Northwestern University. He received his Ph.D. in economics from the University of Chicago. His current research focus is in political economy, with a substantive focus on ideology, elections, and strategic behavior in collective decision-making. His work has been published in leading economics and political science journals, including the American Economic Review, American Journal of Political Science, Journal of Political Economy, Journal of Politics, and Quarterly Journal of Economics.

SoDa Labs webinar series

The SoDa Labs webinar series provides a platform for researchers around the world to present work that uses novel and alternative data and/or tools from data science and beyond to answer social science questions.

Event Details

Date:
12 October 2021 at 10:00 am – 11:00 am
Venue:
Online
Categories:
General; SoDa Labs; SoDa Labs Webinars

Description

Presented by Jörg Spenkuch (Northwestern University) with Y. Salant

We study two dimensions of complexity that may interfere with individual choice. The first one is object complexity, which corresponds to the difficulty of evaluating any given alternative in the choice set. The second dimension is composition complexity, which increases when suboptimal alternatives become more similar to optimal ones.

We develop a satisficing-with-evaluation-errors theory that incorporates both dimensions and delivers sharp empirical predictions about their effect on choice behavior. We confirm these predictions in a novel data set with information on hundreds of millions of decisions in chess endgames. First, as the object complexity of an optimal (suboptimal) alternative increases, it becomes less (more) likely to be chosen. Second, even highly experienced decision-makers are more likely to make mistakes when choosing from sets with higher composition complexity.

These findings help to shed some of the first light on the effect of complexity on choice behavior outside of the laboratory.

Speaker

Jörg Spenkuch (Northwestern University)

Jörg Spenkuch is Associate Professor of Managerial Economics and Decision Sciences at the Kellogg School of Management, Northwestern University. He received his Ph.D. in economics from the University of Chicago. His current research focus is in political economy, with a substantive focus on ideology, elections, and strategic behavior in collective decision-making. His work has been published in leading economics and political science journals, including the American Economic Review, American Journal of Political Science, Journal of Political Economy, Journal of Politics, and Quarterly Journal of Economics.

SoDa Labs webinar series

The SoDa Labs webinar series provides a platform for researchers around the world to present work that uses novel and alternative data and/or tools from data science and beyond to answer social science questions.


E-Mail
SoDaLabs@monash.edu