Optimal and human performance buying airline tickets

Buying an airline ticket is a familiar optimal stopping problem. The goal is to minimize the cost of the ticket, but this is made difficult by changes in the price over time. Part of the change in ticket prices is unpredictable fluctuation, but part is a predictable change in the price distribution, which notoriously increases rapidly as the day of travel approaches. Managing this uncertainty is the key to good decisions, since if a cheap ticket is not purchased it is not possible to go back in time, but once a ticket is purchased future prices are not available. We study how people solve this problem in a controlled experiment, using changing price distributions based on airline industry analysis. Over a set of problems, people are given 12 opportunities to buy a ticket ranging from 6 months before travel to 1 day before. We characterize their behavior in terms of threshold models, and compare their performance to optimal purchasing behavior.