Abstract: Theories intended to describe decision making under risk and uncertainty can be classified as two families according to their theoretical basis: the integrative model and heuristic model. The integrative model postulates that the decision maker is both willing and able to combine information from different dimensions through two fundamental processes: weighting and summing. The heuristic model assumes that people do not integrate these kinds of information but rely on a repertoire of simple decision strategies—called heuristics—to make inferences, choices, estimations, and other decisions.
A total of four experiments were conducted to compare these two sets of competing models from the view of the equate-to-differentiate model (Li, 1994, 2004a, 2004b) by using a response time approach. Experiment 1 re-examined the priority heuristic by using the decision questions employed by Brandstatter, Gigerenzer and Hertwig (2006), but failed to duplicate their results. The priority heuristic predicted that the increase of reasons (steps) required would be associated with the increase of time for making a choice. Experiment 2 tested the priority heuristic by manipulating the number of reasons (steps) assumed by the priority heuristic and the difference between two options on the best-outcome/worst-outcome dimension assumed by the equate-to- differentiate model. It was revealed that the decision time did not increase with the increasing number of reasons (steps) assumed by the priority heuristic but decreased with the increased difference between two options on the best-outcome/worst-outcome dimension. These results obtained in Experiments 1 and 2 were not friendly to the priority heuristic model. Experiments 3 and 4 were designed to test the integrative model. Experiment 3 tested the integrative model by comparing the decision time under risk and under ambiguity. Interestingly, the average decision time under risk was much longer than that under ambiguity. This was contrary to the implications of the integrative model because integrating an ambiguous probability with a given outcome will take longer time than integrating an exact probability with a given outcome to give an overall value or utility. Experiment 4 tested the integrative model by manipulating the difference between CPT (Cumulative Prospect Theory) values and the difference between two options on the best-outcome/worst-outcome dimension. The results showed that the decision time did not decrease with the increased difference between the CPT values but decreased with the increased difference between two options on the best-outcome/worst-outcome dimension, which were not consistent with integrative model but consistent with the equate-to-differentiate model.
In sum, neither integrative model nor priority heuristic could help account for the data on choice process that we observed. Future work may focus on testing these two sets of models by employing methods which can provide a much richer description of the decision process than the response time approach employed in the present paper.

Key words: integrative model, heuristic model, the equate-to-differentiate model, choice process, reaction time