The chimera of time: Exploring the functional properties of an emergency response room in action

Abstract

A number of major accidents in the energy sector have increased global awareness of emergencies in terms of both injuries and fatalities, ecosystem damages and financial costs (AlKazimi & Grantham, 2015). Previous experience has shown how such accidents may originate either from natural hazards or human-made actions, or tight combinations of them (Cabrera Aguilera et al., 2016;Necci et al., 2019). The extension and effects of an emergency depend on the capacity of the Emergency Management System (EMS) to reduce the system's vulnerability. It also depends on a harmonic orchestration of human, technical and organizational components despite the complexity experienced during a contingency. This orchestration shapes by the extent of being prepared for, respond to, and recover from both expected and unexpected events. In other words, it depends on the resilience of the EMS (Tveiten et al., 2012).

Resilience in emergency management: Learning from COVID-19 in oil and gas platforms

“…Frequently interpreted as a core method within RE, the FRAM [ 46 ] represents a systems-wide modelling tool particularly helpful to deal with socio-technical aspects from a systems-theoretic perspective, including EM operations [ 47 ]. This assumption has been documented in a recent research dealing with accident analyses of O&G EMS [ 48 ]. Similarly, applications on management practices through the FRAM in emergency response can be retrieved in several case studies, (e.g.)…”

“…While there is a major overlapping between preparedness and mobilization, the other phases are usually divided among two steps. On the other hand, this operational categorization allows building a FRAM analysis into a multi-layered framework, one per each phase [ 48 ].

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“…While time during any emergency spans over a continuum, four different time moments have been identified in line with OFFB's four operational phases to reduce the analytical complexity of a single large-scale FRAM model. This multi-layer modelling choice has been previously successfully applied in the EM context [ 48 ].

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“…As introduced in the method section (cf. section 3.4), we utilized a four-layer FRAM [ 48 ], where wach layer is connected to other time layers via functions that belong to multiple layers, or via functions in a layer whose output constitutes one of the inputs (I, C, R, P) in another layer. For consistency, this model and the others in the following paragraphs are discussed using specific tags for functions and aspects as follows: < Name of Function> , ‘name of aspect'.…”

Effect of stress on safety‐critical behaviour: An examination of combined resilience engineering and naturalistic decision‐making approaches

“…From an operational perspective, affirming resilience in any safety‐critical operations is done with scenarios (Mendonça, 2008). Several empirical studies have explored how RE tools and concepts enhance the ability of emergency managers (Son et al, 2020; Steen, Patriarca, et al, 2021), police officers (Taylor, 2020), prison's performance management systems (Steen, Ingvaldsen, et al, 2021) or physicians (Fairbanks et al, 2014) to deal with complex situations, make decisions and prioritise actions. These studies use a systemic perspective and RE's analytical methods to enhance adaptive practices in EROs and thus the ability to deal with risks and vulnerabilities.…”