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  • 1. Ekenberg, Love
    et al.
    Boman, Magnus
    RISE, Swedish ICT, SICS, Decisions, Networks and Analytics lab.
    Linnerooth-Bayer, Joanne
    General risk constraints2001In: Journal of Risk Research, ISSN 1366-9877, E-ISSN 1466-4461, Vol. 4, no 1, p. 31-47Article in journal (Refereed)
    Abstract [en]

    The risk evaluation process is integrated with procedures for handling vague and numerically imprecise probabilities and utilities. A body of empirical evidence has shown that many managers would welcome new ways of highlighting catastrophic consequences, as well as means to evaluating decision situations involving high risks. When events occur frequently and their consequences are not severe, it is relatively simple to calculate the risk exposure of an organisation, as well as a reasonable premium when an insurance transaction is made, relying on variations of the principle of maximising the expected utility. When, on the other hand, the frequency of damages is low, the situation is considerably more difficult, especially if catastrophic events may occur. When the quality of estimates is poor, e.g., when evaluating low-probability/high-consequence risks, the customary use of quantitative rules together with unrealistically precise data could be harmful as well as misleading. We point out some problematic features of evaluations performed using utility theory and criticise the demand for precise data in situations where none is available. As an alternative to traditional models, we suggest a method that allows for interval statements and comparisons, which does not require the use of numerically precise statements of probability, cost, or utility in a general sense. In order to attain a reasonable level of security, and because it has been shown that managers tend to focus on large negative losses, it is argued that a risk constraint should be imposed on the analysis. The strategies are evaluated relative to a set of such constraints considering how risky the strategies are. The shortcomings of utility theory can in part be compensated for by the introduction of risk constraints.

  • 2.
    Ström, Mikael
    et al.
    RISE - Research Institutes of Sweden, Swerea, Swerea IVF.
    Koivisto, R.
    VTT Technical Research Centre of Finland.
    Andersson, Dag
    RISE - Research Institutes of Sweden, Swerea, Swerea IVF.
    UML modelling concepts of HAZOP to enhance the ability to identify emerging risks2013In: Journal of Risk Research, ISSN 1366-9877, E-ISSN 1466-4461, Vol. 16, p. 421-432Article in journal (Refereed)
    Abstract [en]

    Unified Modelling Language (UML) has a graphical notation for 13 different types of diagrams and can be used as a general modelling tool. Well-known examples of diagram types are class diagrams for modelling classes that can be instanced into objects, state machine diagrams for modelling states in systems and activity diagrams for modelling process flows. A literature survey shows that UML has been used to model concepts and methodologies of risk assessment and risk management. One example is the Coras Framework. The international standard CEI IEC 61882 Hazard and operability (HAZOP) studies describes concepts for investigating and detecting possible hazards in systems. In CEI IEC 6882, guide words like More and Less are applied to system parameters to invoke deviations in the system and assess possible hazards due to the deviation from the design intent. In this paper, we have used UML to model concepts of CEI IEC 61882 Hazards and operability studies. Diagrams of UML were used to show dependencies and relations between parts of the target system and concepts of CEI IEC 61882. Extensions of UML are suggested to better capture and display the concepts of CEI IEC 61882, the results of a HAZOP study and emerging risk. These extensions are referred to as UML for emerging risks (UML-ER). © 2013 Taylor and Francis Group, LLC.

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