Sequential Decision Making : How Prior Choices Affect Subsequent Valuations

This paper develops and tests a model of sequential decision making where a first stage of ranking a set of alternatives is followed by a second stage of determining the value of these same alternatives. The model assumes a boundedly rational Bayesian decision maker who is uncertain about his/her underlying preferences over the relevant attributes, and who has to exert costly cognitive effort to resolve this uncertainty. Compared to when only valuation takes place, the analysis reveals that ranking a set of alternatives prior to determining their value has three primary effects: a) the spread (or dispersion) of valuations between most and least preferred alternatives increases, b) decision makers will, on expectation, exert more effort in the valuation phase, and c) the more each attribute contributes to overall utility the greater the relative impact of ranking is on valuation spread. The analysis also sheds light on how prior ranking impacts the demand for a product. These results are then corroborated in a series of controlled lab experiments with actual prizes. The findings have implications for many real life decision making situations ranging from auctions, where there is a tendency to prioritize items before determining a bid, to the ranking of job candidates prior to determining wages and benefits to be offered. More generally, the results bear on our understanding of how past decisions can affect future related decisions