Observational Learning in Broad Choice Sets

29 Pages Posted: 22 Feb 2015 Last revised: 18 Oct 2017

See all articles by Chen Jin

Chen Jin

National University of Singapore (NUS) - Department of Information Systems and Analytics

Laurens Debo

Dartmouth College - Tuck School of Business

Seyed Iravani

Northwestern University - Department of Industrial Engineering and Management Sciences

Mirko Kremer

Frankfurt School of Finance & Management

Date Written: October 18, 2017

Abstract

We study observational learning in environments where customers choose among multiple options with uncertain quality for which they observe the aggregate choices of previous customers (the sales of each option). When customers have heterogeneous knowledge about quality, the choices of better informed customers turn sales into informative signals, allowing less informed customers to learn about the options' quality. We characterize the equilibrium choices for environments with any number of options. Although uninformed customers avoid options with no sales, they often prefer minority options with low sales over majority options with higher sales. "Minority Wisdom" tends to arise when the number of options is large, and when the fraction of informed customers in the market is low. We test the predictions from our observational learning model in the laboratory. The data shows that human subjects learn from sales information, even though they follow minorities less often than predicted by the full rationality paradigm of our equilibrium model. Our results suggest that observational learning might be problematic even for high quality firms, which gain less market share than theoretically predicted, and may find it more difficult to match supply and demand, because observational learning tends to increase demand uncertainty.

Keywords: Queueing Game, Observational Learning, Wisdom of Crowds and Minorities, Contrarianism, Experiments, Probability, Markov processes, Game decisions

Suggested Citation

Jin, Chen and Debo, Laurens and Iravani, Seyed and Kremer, Mirko, Observational Learning in Broad Choice Sets (October 18, 2017). Chicago Booth Research Paper No. 15-08, Available at SSRN: https://ssrn.com/abstract=2567367 or http://dx.doi.org/10.2139/ssrn.2567367

Chen Jin

National University of Singapore (NUS) - Department of Information Systems and Analytics ( email )

Singapore

Laurens Debo (Contact Author)

Dartmouth College - Tuck School of Business ( email )

Hanover, NH 03755
United States

Seyed Iravani

Northwestern University - Department of Industrial Engineering and Management Sciences ( email )

Evanston, IL 60208-3119
United States

Mirko Kremer

Frankfurt School of Finance & Management ( email )

Adickesallee 32-34
Frankfurt am Main, 60322
Germany

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