Using the Analytic Hierarchy Process to Examine Judgment Consistency in a Complex Multiattribute Task

This paper investigates the impact of framing and time pressure on human judgment performance in a complex multiattribute judgment task. We focus on the decision process of human participants who must choose between pairwise alternatives in a resource-allocation task. We used the Analytic Hierarchy Process (AHP) to calculate the relative weights of the four alternatives (i.e., C1, C2, C3, and C4) and the judgment consistency. Using the AHP, we examined two sets of hypotheses that address the impact of task conditions on the weight prioritization of choice alternatives and the internal consistency of the judgment behavior under varying task conditions. The experiment simulated the allocation of robotic assets across the battlefield to collect data about an enemy. Participants had to make a judgment about which asset to allocate to a new area by taking into account three criteria related to the likelihood of success. We manipulated the information frame and the nature of the task. We found that, in general, participants gave significantly different weights to the same alternatives under different frames and task conditions. Specifically, in terms of ln-transformed priority weights, participants gave significantly lower weights to C2 and C4 and higher weight to C3 under gain frame than under loss frame, and also, under different task conditions (i.e., Tasks #1, #2, and #3), participants gave significantly higher weight to C4 in Task #1, lower weights to C1 and C4, higher weight to C3 in Task #2, and lower weight to C3 in Task #3. Furthermore, we found that the internal consistency of the decision behavior was worse, first, in the loss frame than the gain frame and, second, under time pressure. Our methodology complements utility-theoretic frameworks by assessing judgment consistency without requiring the use of task-performance outcomes. This work is a step toward establishing a coherence criterion to investigate judgment under naturalistic conditions. The results will be useful for the design of multiattribute interfaces and decision aiding tools for real-time judgments in time-pressured task environments.