Why We Screw Up Small Decisions
Abstract (via Barron & Erev)
The present paper explores situations in which the information available to decision makers is limited to feedback concerning the outcomes of their previous decisions. The results reveal that experience in these situations can lead to deviations from maximization in the opposite direction of the deviations observed when the decisions are made based on a description of the choice problem. Experience was found to lead to a reversed common ratio/certainty effect, more risk seeking in the gain than in the loss domain, and to an underweighting of small probabilities. Only one of the examined properties of description-based decisions, loss aversion, seems to emerge robustly in these ‘feedback-based’ decisions. These results are summarized with a simple model that illustrates that all the unique properties of feedback-based decisions can be a product of a tendency to rely on recent outcomes.
Introduction (via Barron & Erev)
Many common activities involve ‘small’ decision problems. Driving, for example, requires repeated selection among routes, speeds, and various other options. Although little time and effort is typically invested in these and similar small decisions, they can be consequential. The estimated cost of traffic accidents in the USA is more than 100 billion dollars a year (see e.g. Blincoe, 19941), and many of the accidents are at least partially products of ex-post unwise decisions.
The current paper focuses on an important subset of the small decision problems exemplified above that can be referred to as ‘small feedback-based’ decisions. These problems are defined by three main properties. First, they are repeated; decision makers face the same problem many times in similar situations. Second,each single choice is not very important; the alternatives tend to have similar expected values that may be quite small. Finally, the decision makers do not have ‘objective’ prior information concerning the payoff distributions. In selecting among the possible options, they have to rely on the immediate feedback obtained in similar situations in the past.