An Exploration of General Aviation Occurrences in South Africa (2015- 2017): Application of the Human Factors Analysis and Classification System using Bayes’ Theorem

Abstract

A mixed-method research design was utilised by combining thematic content analysis (TCA) and Bayesian statistical modelling. The research investigated the prevalence of adverse general aviation (GA) occurrences in the Republic of South Africa between 2015 and 2017. The study used the Human Factors Analysis and Classification System (HFACS) framework to categorise human and organisational failures. The Bayesian probability analysis was used to quantify the likelihood of failures leading to accidents, serious incidents, or incidents. The qualitative findings revealed that latent failures at the organisational, supervisory, and preconditions levels played a major role in adverse GA occurrences. Inadequate training, resource constraints, weather conditions, physiological state, poor oversight, and ineffective safety policies created conditions where active failures such as pilot decision errors, skill errors, and routine violations were more likely to occur. The Bayesian analysis confirmed that organisational level failures significantly increased the risk of adverse GA occurrences. The findings highlight a safety culture gap within the GA sector in South Africa. The physical environment, company policy, unsafe supervision, condition of the operators, and decision errors were associated with accidents. This suggests that these factors have serious consequences in the GA sector. This study could inform a multi-tiered approach to risk management and safety interventions rather than an overreliance on individual error mitigation, encourage training programmes that focus on the importance of decision-making under pressure, and error management, and encourage a safety culture, and provide evidence to the benefits of data-driven approaches such as the Bayes’ theorem. This model can be integrated into routine safety assessments to measure the effectiveness of implemented safety interventions over time.