Decision-Making Styles Associated with Accidents: Defining the High Risk Pilot

Abstract

This study involved an extensive experimental survey of 4000 pilots. It was designed to determine decision-making variables that could be used to identify high risk taking pilots who have had an accident (cases) vs. low risk pilots who have been accident free (controls). The information data set collected with this survey instrument provided a rich core of knowledge that has not been analyzed before as a whole. The ultimate goal was to use this core of information to develop a global index related to a pilot's propensity for accidents.

The analyses included: validating the risk taking hypotheses, the development of a discriminant functions to determine if cases and controls could be correctly classified using the instrument, and the development of a risk taking characteristic model. It was found that 80.1% of the cases and controls could be correctly classified using the entire 122 question set. If a simplified five question set was used, 68.2% of the cases and controls could be correctly classified.