ABSTRACT
Studies underpinned by systems thinking have significantly altered the viewpoint of safety for sociotechnical systems. Safety is characterized as an emergent property (Leveson et al., 2006) that arises when the system components interact with each other (Dulac, 2007; Qureshi, 2007). The unsafe behaviors and inadequate control actions occurred at various levels within the socio-technical system allow it to migrate towards a state where a simple deviation can lead to a cataclysmic loss (Rasmussen, 1997). Accordingly, accident causation should be seen as a complex process (Woods et al., 1994; Leveson, 2011) involving actors from all levels within the socio-technical system (i.e., designers, legislators, managers, operators, etc.). Traditional even-based accident analysis models, i.e., Fault Tree Analysis (FTA), Event Tree Analysis (ETA), Failure Modes and Effects Analysis (FMEA) have revealed their limitations to capture the hazardous and dysfunctional interactions between and among system components that led to the accident (Leveson, 2011). Moreover, the events that are selected to explain the accident causation are also subject to bias.
