Understanding how people assign subjective value to outcomes with multiple attributes, such as risk and delay, is central to understanding the structure and manifestation of economic preferences. However, multiattribute preference has been primarily studied through binary choices. The price at which a person would buy, sell, or equate each prospect offers another measure of subjective value that may diverge from multiattribute choice. In both risky and intertemporal domains, choice and price preferences exhibit systematic preference reversals, where a smaller, sooner, or safer option is chosen while a larger, later, or riskier alternative is assigned a higher price. The present study takes a deep dive into how subjective value is assigned in each case in an attempt to reconcile these diverging measurements and methods of assessing value. To explain how and why preferences change across choice and price, the domains of gains and losses, price frames of buying and selling, and varying levels of time pressure, we develop a two-step neural network-based modeling approach. First, we tested cognitive mechanisms underlying value-based judgments and decisions using a switchboard model comparison. Next, we fit and evaluated individualized joint models, where all data from an individual are modeled using parameters and mechanisms that are specific to their best fitting model structure. While mechanisms like delay discounting and risk aversion are common to both models, our results suggest that anchoring and payoff sensitivity diverged between pricing and choice. Extensive differences across elicitation procedures indicate that a common representation of value may remain elusive. (PsycInfo Database Record (c) 2025 APA, all rights reserved).
Fitch et al. (Thu,) studied this question.