A fuzzy bayesian quantitative risk assessment for language and communication induced accidents in maritime operations

Abstract

Language and communication issues pose a formidable risk to maritime safety. In maritime transportation, the effectiveness of speech acts and closed-loop communication is vulnerable to a wide array of factors. However, literature quantifying the impact of these factors on language and communication-induced accident risk is scarce. To that end, this study conducts a holistic quantitative risk assessment for the language and communication issues induced accidents in maritime transportation. The methodology consists of employing expert judgments, past literature, and accident reports to identify causation factors and a Fuzzy Bayesian approach to risk analysis. Bidirectionally propagated inferential analysis was conducted to determine the impact of factors under consideration in various scenarios. Lack of language proficiency and violations of the roles and regulations of communication were identified as prominent accident causation factors. Simultaneous evidence-setting analysis was conducted to determine the domino effect of the causation factors. A sensitivity analysis was performed to reveal the most critical factors causing language and communication issues induced accident risk. This study unravels the nuanced dynamics of language-related risk in maritime safety. The findings of this study can be used to propose guidelines and policies for effective communication and hence safer maritime operations.