A new framework to measure intuitiveness in decision problems

Intuition in decision-making is often seen as a set of heuristic or holistic mental processes applied to decision problems when they exceed cognitive capacity, or whenever there is a will to achieve a solution that does not exhaust cognitive resources. In this regard, to date it has been solely treated as a personal and frequently solipsist tendency. This paper tests whether different types of problems carry different degrees of 'intuitiveness' and whether it would be possible to produce a realistic experimental model of such problems. To cope with both demands, standardized stimuli (mostly IAPS figures) were used to model decision problems as conflicts (approach-avoidance, approach-approach, and avoidance approach conflicts). Intuitiveness was argued to be inversely related to arousal, as measured by GSR levels. Several solutions to methodological problems involving decision-making designs in the environment of the software BioExplorer were created. Kruskal-Wallis and Mann-Whitney-Wilcoxon tests were used to rank problems. According to our analyses, ap-av conflicts are by far less intuitive than av-ap, and av-av (p <.0001). The latter two are not very different in this regard (p = .5712).