Special issue: Data-driven risk analysis Abbassi, Rouzbeh; Salehi, Fatemeh; Cholette, Michael
Process safety and environmental protection,
June 2021, 2021-06-00, 20210601, Letnik:
150
Journal Article
•Two-stage risk analysis framework for maritime transportation risk is proposed.•Bayesian Network is used as a modeling tool for risk quantification.•Tools are presented for qualitatively extending ...the model-based argumentation.•Framework is applied to a case study for oil spill risk in the Gulf of Finland.•Evaluation criteria and tests indicate that the model and analysis are plausible.
This paper proposes a framework for risk analysis of maritime transportation systems, where risk analysis is understood as a tool for argumentative decision support. Uncertainty is given a more prominent role than in the current state of art in the maritime transportation application area, and various tools are presented for analyzing uncertainty. A two-stage risk description is applied. In the first stage, Bayesian Network (BN) modeling is applied for probabilistic risk quantification. The model functions as a communication and argumentation tool, serving as an aid to thinking in a qualitative evidence and assumption effect assessment. The evidence assessment is used together with a sensitivity analysis to select alternative hypotheses for the risk quantification, while the assumption effect assessment is used to convey an argumentation beyond the model. Based on this, a deliberative uncertainty judgment is made in the second risk analysis stage, which is supplemented with a global strength of evidence assessment. The framework is applied to a case study of oil spill from tanker collisions, aimed at response capacity planning and ecological risk assessment. The BN-model is a proactive and transferable tool for assessing the occurrence of various spill sizes in a sea area. While the case study uses evidence specific to the Gulf of Finland, the model and risk analysis approach can be applied to other areas. Based on evaluation criteria and tests for the risk model and risk analysis, it is found that the model is a plausible representation of tanker collision oil spill risk.
The Risk Analysis Quality Test Release 1.0 (RAQT1.0) was developed as a framework to encourage mutual understanding between technical risk analysts and risk management decision makers of risk ...assessment quality indicators. The initial version (release 1.0) was published by the Society for Risk Analysis (SRA) in 2020 with the intent of learning from early test applications whether the approach was useful and whether changes in approach or contents would be helpful. The results of applications across three diverse fields are reported here. The applications include both retrospective evaluations of past risk assessments and prospective guidance on the design of future risk assessment projects or systems. The fields represented include Quantitative Microbial Risk Assessment, Cultural Property Risk Analysis, and Software Development Cyber Risk Analysis. The RAQT1.0 proved helpful for identifying shortcomings in all applications. Ways in which the RAQT1.0 might be improved are also identified.
The evaluation of clustering algorithms is intrinsically difficult because of the lack of objective measures. Since the evaluation of clustering algorithms normally involves multiple criteria, it can ...be modeled as a multiple criteria decision making (MCDM) problem. This paper presents an MCDM-based approach to rank a selection of popular clustering algorithms in the domain of financial risk analysis. An experimental study is designed to validate the proposed approach using three MCDM methods, six clustering algorithms, and eleven cluster validity indices over three real-life credit risk and bankruptcy risk data sets. The results demonstrate the effectiveness of MCDM methods in evaluating clustering algorithms and indicate that the repeated-bisection method leads to good 2-way clustering solutions on the selected financial risk data sets.
Today, supply chain finance is a very important topic. Traditional supply chains rely on banks to support the related financing activities and services. With the emergence of blockchain technology, ...more and more companies in different industries have considered using it to support supply chain finance. In this paper, we study supply chain financing problems in supply chains selling fashionable products. Modeling under the standard newsvendor problem setting with a single manufacturer and a single retailer employing a revenue sharing contract, we develop analytical models for both the traditional and blockchain-supported supply chains. We derive the optimal contracting and quantity decisions in each supply chain with Nash bargaining between the manufacturer and retailer. We analytically show how the revenue sharing contract can coordinate both types of supply chains. We then compare the optimal systems performances between the two supply chains. We prove that the blockchain-supported supply chain incurs a lower level of operational risk than the traditional supply chain. We have shown that if the service fees by banks are sufficiently high, adopting blockchain technology is a mean-risk dominating policy which brings a higher expected profit and a lower risk for the supply chain and its members. For robustness checking, we examine other commonly seen supply chain contracts and alternative risk measures, and analytically reveal that the results remain valid.
With the rapid increase of distributed generation (DG) in the distribution network (DN), the analysis of DG maximum bearing capacity (DGMBC) is paid more attention. However, the existing methods can ...not precisely simulate the overvoltage risk concerning occurrence probability and severity. To this end, the overvoltage scenario classification method and overvoltage severity coefficient correction method are proposed in this paper, which can effectively reflect the real overvoltage risk in DN. The IEEE 33-bus test feeder is used to compare the calculation results of overvoltage risk with other methods.
•Scientific work on validity and validation of safety-related quantitative risk analysis is reviewed.•Theoretical, methodological and empirical contributions are distinguished.•Four generic methods ...for validation have been proposed.•These are benchmark exercises, reality checks, independent peer review and quality control.•More evidence is needed about the efficacy of these methods and about the cost-effective usefulness of QRA.
Quantitative risk analysis (QRA) is widely applied in several industries as a tool to improve safety, as part of design, licensing or operational processes. Nevertheless, there is much less academic research on the validity and validation of QRA, despite their importance both for the science of risk analysis and with respect to its practical implication for decision-making and improving system safety. In light of this, this paper presents a review focusing on the validity and validation of QRA in a safety context. Theoretical, methodological and empirical contributions in the scientific literature are reviewed, focusing on three questions. Which theoretical views on validity and validation of QRA can be found? Which features of QRA are useful to validate a particular QRA, and which frameworks are proposed to this effect? What kinds of claims are made about QRA, and what evidence is available for QRA being valid for the stated purposes? A discussion follows the review, focusing on the available evidence for the validity of QRA and the effectiveness of validation methods.
Many methods and applications for maritime transportation risk analysis have been presented in the literature. In parallel, there is a recent focus on foundational issues in risk analysis, with calls ...for intensified research on fundamental concepts and principles underlying the scientific field. This paper presents a review and analysis of risk definitions, perspectives and scientific approaches to risk analysis found in the maritime transportation application area, focusing on applications addressing accidental risk of shipping in a sea area. For this purpose, a classification of risk definitions, an overview of elements in risk perspectives and a classification of approaches to risk analysis science are applied. Results reveal that in the application area, risk is strongly tied to probability, both in definitions and perspectives, while alternative views exist. A diffuse situation is also found concerning the scientific approach to risk analysis, with realist, proceduralist and constructivist foundations co-existing. Realist approaches dominate the application area. Very few applications systematically account for uncertainty, neither concerning the evidence base nor in relation to the limitations of the risk model in relation to the space of possible outcomes. Some suggestions are made to improve the current situation, aiming to strengthen the scientific basis for risk analysis.
•Risk analyses in maritime transportation analysed in light of foundational issues.•Focus on definitions, perspectives and scientific approaches to risk analysis.•Probability-based definitions and realist approaches dominate the field.•Findings support calls for increased focus on foundational issues in risk research.•Some suggestions are made to improve the current situation.
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