Browsing by Author "Rocks, S."

Now showing 1 - 4 of 4
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    Development of a novel method for cross-disciplinary hazard identification
    (Cranfield University, 2013) Parchment, Ann; Oakey, John; Rocks, S.; Judd, Simon J.
    Hazards and risks are currently identified in generic risk silos using top-down tools and methods which are incorporated into whole system risk management frameworks such as enterprise risk management. The current methods of identification and documentation are linear in approach and presentation. However, the world is multi-dimensional requiring a method of identification which responds to complex non-linear relationships. A method is required to identify cross- disciplinary hazards and formulate a register method to evidence the identified hazards. This study uses expert elicitation, web, survey and case studies to develop a method for cross-disciplinary hazard identification by application of the dimensions of generic, interface, causation and accumulation. The results of the study found many of the tools and methods used for hazard and risk identification such as hazard and operability studies took a top down approach commencing with a known failure and establishing cause and effect. The starting position of a known failure or event precludes identification of new types of failure or events and perpetuates a linear approach to hazard identification. Additionally the linear design of a risk register does not facilitate the presentation of multidimensional hazards. The current methods do not accommodate multiple lifecycles and components within cross discipline relationships. The method was applied to three case studies. The first case study had an existing risk register of 50 risks, post method application an additional 531 hazards were identified; case study (2) a register of 49 hazards and post method application additional hazards of 261; case study (3) an initial register of 45 hazards and an additional 384 hazards after method application. The impact of the method application highlights inconsistencies in the initial risk register and provides a tool which will aid the identification understanding and communication of hazards. Additionally it documents previously unidentified cross-disciplinary hazards and provides a proactive register method for identification and documentation by application of the dimensions of interface, causation and accumulation.
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    A novel approach for indentifying uncertainties within environmental risk assessments
    (Cranfield University, 2012-10) Skinner, Daniel J. C.; Rocks, S.
    Uncertainties can manifest within the different aspects of environmental risk assessments, affecting the validity of the risk estimate and, in turn, weakening the basis for risk management actions. This research investigated the issues associated with uncertainty characterisation and identification in environmental risk assessments. This led to the creation of a defensible typology of uncertainties, and the creation and validation of a novel uncertainty identification system (UnISERA), based on the elicited views of experts regarding the levels (i.e. magnitudes), natures (i.e. reason for existence) and locations (i.e. where manifest) of uncertainties present within different risk domains. The developed typology, drawn from an analysis of existing assessments, contained seven locations of uncertainty (data, language, system, extrapolation, variability, model and decision), with 20 related sub-types. The output from UnISERA, based on 19 aggregated elicitations across three risk domains (genetically modified higher plants, particulate matter and pesticides), showed that: the risk characterisation phase of assessments contained the highest magnitudes of uncertainty (the level dimension); uncertainties across all four phases of assessments existed primarily through a combination of lack of knowledge and randomness (the nature dimension); and data uncertainty was dominant in the first three phases, and extrapolation uncertainty in the final phase (the location dimension). In comparing the output from UnISERA to similarly produced results in the risk domain of engineered nanomaterials, the nature of uncertainty showed the highest degree of validation (90%), followed by the location (80%) and level (55%) dimensions. The novel approach to uncertainty characterisation and identification presented here will be of use during environmental risk assessments and uncertainty analyses, promoting an understanding of potential uncertainties, and allowing risk analysts to perform assessments with prioritised uncertainties in mind.
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    Towards an agent-based model for risk-based regulation
    (Cranfield University, 2010-09) Davies, Gareth J.; Pollard, Simon J. T.; Rocks, S.
    Risk-based regulation has grown rapidly as a component of Government decision making, and as such, the need for an established evidence-based framework for decisions about risk has become the new mantra. However, the process of brokering scientific evidence is poorly understood and there is a need to improve the transparency of this brokering process and decisions made. This thesis attempts to achieve this by using agent-based simulation to model the influence that power structures and participating personalities has on the brokering of evidence and thereby the confidence-building exercise that characterises risk-based regulation. As a prerequisite to the adoption of agent-based techniques for simulating decisions under uncertainty, this thesis provides a critical review of the influence power structure and personality have on the brokering of scientific evidence that informs risk decisions. Three case studies, each representing a different perspective on risk-based regulation are presented: nuclear waste disposal, the disposal of avian-influenza infected animal carcases and the reduction of dietary salt intake. Semi-structured interviews were conducted with an expert from each case study, and the logical sequence in which decisions were made was mapped out and used to inform the development of an agent-based simulation model. The developed agent-based model was designed to capture the character of the brokering process by transparently setting out how evidence is transmitted from the provider of evidence to the final decision maker. It comprises of two agents, a recipient and provider of evidence, and draws upon a historic knowledge base to permit the user to vary components of the interacting agents and of the decision-making procedure, demonstrating the influence that power structure and personality has on agent receptivity and the confidence attached to a number of different lines of evidence. This is a novel step forward because it goes beyond the scope of current risk management frameworks, for example, permitting the user to explore the influence that participants have in weighing and strengthening different lines of evidence and the impact this has on the final decision outcome.
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    Validating the strategic risk appraisals of policy experts
    (Cranfield University, 2013-06) Dagonneau, J.; Rocks, S.; Pollard, Simon J. T.
    The emergence and evolution of environmental risks increases the need of government organisations to prioritise their resources for efficient risk management in a manner that is transparent and auditable. Many different data sources (including expert opinion and published data) can be used to inform assessments. This work evaluates and compares the use of two different data sources for environmental strategic risk assessment (SRA). Here, a developed SRA framework (Prpich et al., 2012) was applied to 12 environmental risks within the UK to characterise the environmental, economic and social impacts of a risk on semi-qualitative scales and provide a descriptive narrative. A structured literature search of peer-reviewed and grey literature was assessed for relevance and quality and impact values were determined giving equal weighting to evidence. It was not possible to identify likelihood data from the literature evidence, therefore the expert assessment was used for all risks. Individual assessments for the different risks were compared to expert elicitation data (n ≥ 3) where it was found that they provided similar risk assessments and referred to similar evidence. Where the assessments differed, differences in evidence were noted possibly due to publication delays or method rigidity. Knowledge gaps were noted in the assessment of ‘economic services’ and ‘social cohesion’ sub-attributes for both data sources. These results suggest that the expert elicitation validated the use of literature evidence for SRAs impact assessment, but in order to provide a robust SRA, future assessments could combine both evidence sources.