Process model analysis for a gamble lottery task
There are two theoretical approaches accounting for how people preferentially choose lotteries in the classical gamble task. Following the rationality postulate, a person chooses according to the utility associated with each lottery. For example, prospect theory (PT, Kahneman & Tversky, 1979) proposes that at a final decision stage, a decision maker calculates utilities for each gamble by combining the gamble’s attributes . Alternatively, following the bounded rationality postulate, a rule-based heuristic may be used to evaluate each gamble’s attributes one-at-a-time (e.g. Priority Heuristic, Brandstätter, et al, 2006). This approach implies serial information processing and that a decision is made when the critical difference between compared attributes is evaluated. To validate the core assumptions of these approaches we employed a parametric version of the Systems Factorial Technology (SFT), which can be used to diagnose whether processes are organized in serial or parallel mental architectures, whether a stopping rule is exhaustive or self-terminating, and whether the processes are interdependent. Using the joint analysis of preferential choice response time distributions, we compared stochastic versions of several decision-making models: serial, parallel, parallel interactive, mixture, and the full-parameter models. The results indicated differences in how participants processed gambles’ attributes. Some participants adopted either serial or parallel processing, while some relied on their trial-to-trial mixture. Some of the model fits, matched to those of the statistical full model, speaking strongly in favor of both the Take-the-Best and Weighted-Additive models. In general, these findings invite reconsiderations for heuristic-based approaches to decision making and on boundedly rational decision models.