Performance Shaping Factor Dependency Assessment Based on International Civil Aviation Accident Report Data

Abstract

The quantitative assessment of human error risk in computerized aircraft cockpit need a comprehensive understanding of performance shaping factor (PSF) effects on interaction tasks and the dependency between PSFs. This study employed stepwise logistic regression analysis and mediating effect analysis to explore PSF dependencies based on 872 air accident report data. Among the 14 PSFs of the established PSF taxonomy, five PSFs have significant influences on crew error. Further dependency analysis shows that a significant mediating effect exists in 16 PSF combinations, however, only 8 combinations should be considered in the actual human reliability analysis (HRA) process (indirect effect exceeds 20%). The study proposes an empirical method for identifying and assessing PSF dependencies. The results can be used to develop new or modify existing HRA methods according to the civil aviation context, as well as provide guidance to human error risk prevention and mitigation from broader perspectives in addition to interface facet.