Risk Matrix Integrating Risk Attitudes Based on Utility Theory

Risk aggregation considering probabilistic and consequential interactions: A general formulation with computational cost handling

Complicated interaction between risk events is the critical obstacle preventing accurate risk aggregation, which is an important issue in risk management. Recent research integrates interaction into risk aggregation with different perspectives and lacks a comprehensive discussion of this issue, making the risk aggregation process not universal for diverse cases, especially in subjective risk assessment contexts. Therefore, this article proposes a theoretically convincing risk aggregation method embedding different types of interaction to support decision analysis more effectively. The main contributions of this article are as follows: (a) more in-depth and stricter definitions, measures, and graphical descriptions of different types of interaction are developed to ensure the accuracy of risk aggregation; (b) a formal risk aggregation approach that could apply in both objective and subjective risk assessment contexts while elegantly embedding risk interactions is proposed; (c) the additivity of risks and risk sets in the risk aggregation process is discussed in detail and the conditions for additivity are clarified; (d) the quasi-two/three-additive measures, which approximately obtain the aggregate risk value within sufficient reliability, are proposed to greatly reduce the computational cost. To examine the applicability of the proposed general risk aggregation method, a case study is finally presented to show the complete risk aggregation process and its application in the decision-making stage.

A framework for risk matrix design: A case of MASS navigation risk

Risk matrix, a tool for visualizing risk assessment results, is essential to facilitate the risk communication and risk management in risk-based decision-making processes related to new and unexplored socio-technical systems. The use of an appropriate risk matrix is discussed in the literature, but it is overlooked for emerging technologies such as Maritime Autonomous Surface Ships (MASS). In this study, a comprehensive framework for developing a risk matrix based on fuzzy Analytic Hierarchy Process (AHP) is proposed. In this framework, a linear function is defined where the risk index is treated as a response variable, while the probability and consequence indices are explanatory variables, with weights of these two indices representing their importance on given risk level. This significance is assessed by experts and quantified using AHP in interval type 2 fuzzy environment. A continuous risk diagram is then created and converted into a risk matrix that can be improved. To verify the feasibility of the proposed framework, a risk matrix is designed in the context of MASS grounding. The results show that the proposed approach is feasible. Our discussion results can provide new insights for the design of risk matrices and promote the management of MASS navigational risks.

An Evidential Software Risk Evaluation Model

Software risk management is an important factor in ensuring software quality. Therefore, software risk assessment has become a significant and challenging research area. The aim of this study is to establish a data-driven software risk assessment model named DDERM. In the proposed model, experts’ risk assessments of probability and severity can be transformed into basic probability assignments (BPAs). Deng entropy was used to measure the uncertainty of the evaluation and to calculate the criteria weights given by experts. In addition, the adjusted BPAs were fused using the rules of Dempster–Shafer evidence theory (DST). Finally, a risk matrix was used to get the risk priority. A case application demonstrates the effectiveness of the proposed method. The proposed risk modeling framework is a novel approach that provides a rational assessment structure for imprecision in software risk and is applicable to solving similar risk management problems in other domains.

Risk Assessment Matrices for Workplace Hazards: Design for Usability

In occupational safety and health (OSH), the process of assessing risks of identified hazards considers both the (i) foreseeable events and exposures that can cause harm and (ii) the likelihood or probability of occurrence. To account for both, a table format known as a risk assessment matrix uses rows and columns for ordered categories of the foreseeable severity of harm and likelihood/probability of that occurrence. The cells within the table indicate level of risk. Each category has a text description separate from the matrix as well as a word or phrase heading each row and column. Ideally, these header terms will help the risk assessment team distinguish among the categories. A previous project provided recommended sets of header terms for common matrices based on findings from a survey of undergraduate OSH students. This paper provides background on risk assessment matrices, discusses usability issues, and presents findings from a survey of people with OSH-related experience. The aim of the survey was to confirm or improve the prior recommended sets of terms. The prior recommendations for severity, likelihood, and extent of exposure were confirmed with minor modifications. Improvements in the probability terms were recommended.

Risk Analysis in Healthcare Organizations: Methodological Framework and Critical Variables

Purpose

A risk assessment matrix is a widely used tool for analyzing, assessing and setting priorities in risk management in many fields. This paper overviews critical variables, advantages, disadvantages, strengths and weaknesses of this tool, according to the ISO 31000 risk management framework.

Results

Risk assessment is one of the key stages in the Risk Management Process and involves specific steps: identifying hazards, analyzing and evaluating all possible risks. Several methods are developed to assess risks in the literature. A risk matrix method, also called “decision matrix risk assessment (DMRA) technique”, is a systematic approach used to determine the risk level and to compare different risks and define which threats need to be controlled first. The actors involved in risk assessment are called on to manage different issues related to the choice of the most appropriate methodological approach, the assessment of the adequacy of the existing control measures, the articulation of risk consequence domains, the definition of the impact-consequences, the explanation of risk likelihood scales and the development of a risk matrix.

Conclusion

We highlighted a number of recommendations in order to address these issues, especially useful when healthcare organizations provide insufficient guidance on how to use risk matrices as well as what to do in response to the existing criticisms on their use.

Worst Expected Best method for assessment of probabilistic network expected value at risk: application in supply chain risk management

Purpose

The purpose of this paper is to develop and operationalize a process for prioritizing supply chain risks that is capable of capturing the value at risk (VaR), the maximum loss expected at a given confidence level for a specified timeframe associated with risks within a network setting.

Design/methodology/approach

The proposed “Worst Expected Best” method is theoretically grounded in the framework of Bayesian Belief Networks (BBNs), which is considered an effective technique for modeling interdependency across uncertain variables. An algorithm is developed to operationalize the proposed method, which is demonstrated using a simulation model.

Findings

Point estimate-based methods used for aggregating the network expected loss for a given supply chain risk network are unable to project the realistic risk exposure associated with a supply chain. The proposed method helps in establishing the expected network-wide loss for a given confidence level. The vulnerability and resilience-based risk prioritization schemes for the model considered in this paper have a very weak correlation.

Originality/value

This paper introduces a new “Worst Expected Best” method to the literature on supply chain risk management that helps in assessing the probabilistic network expected VaR for a given supply chain risk network. Further, new risk metrics are proposed to prioritize risks relative to a specific VaR that reflects the decision-maker's risk appetite.

Impact of Risk Attitude on Risk, Opportunity, and Performance Assessment of Construction Projects

This article explores the impact of risk attitude on the assessment of project uncertainty encompassing both risk and opportunity and expected project performance. A survey was conducted involving project risk management experts from the construction industry, and the data collected were analyzed using various statistical techniques. The findings reveal that the impact of risk attitude significantly varies across multiple dimensions of project uncertainty and project performance. To the best of the authors’ knowledge, the association between risk attitude and project uncertainty and expected performance assessments has never been explored while capturing multiple dimensions of project uncertainty and performance.

The Role of Decision Analysis in Risk Analysis: A Retrospective

In commemorating the 40th anniversary of Risk Analysis, this article takes a retrospective look at some of the ways in which decision analysis (as a "sibling field") has contributed to the development both of the journal, and of risk analysis as a field. I begin with some early foundational papers from the first decade of the journal's history. I then review a number of papers that have applied decision analysis to risk problems over the years, including applications of related methods such as influence diagrams, multicriteria decision analysis, and risk matrices. The article then reviews some recent trends, from roughly the last five years, and concludes with observations about the parallel evolution of risk analysis and decision analysis over the decades-especially with regard to the importance of representing multiple stakeholder perspectives, and the importance of behavioral realism in decision models. Overall, the extensive literature surveyed here supports the view that the incorporation of decision-analytic perspectives has improved the practice of risk analysis.

Selecting Appropriate Words for Naming the Rows and Columns of Risk Assessment Matrices

The risk management systems used in occupational safety and health typically assess the risk of identified hazards using a tabular format commonly called a risk assessment matrix. Typically, columns are named with words indicating severity, and rows are named with words indicating likelihood or probability. Some risk assessment matrices use words reflecting the extent of exposure to a hazard. This project was undertaken with the aim of helping the designers of risk assessment matrices select appropriate names for the rows and columns. A survey of undergraduate students studying engineering or occupational safety and health obtained ratings of 16 English language words and phrases for each of the three factors. Analyses of 84 completed surveys included comparing average ratings on a 100-point scale. Using the averages, appropriately spaced sets of words and phrases were identified for naming the row and column categories. Based on results, the authors recommend word sets of three, four, and five for severity; three, four, five, and six for likelihood; and two and three for extent of exposure. The study methodology may be useful for future research, and the resulting word sets and numerical ratings may be helpful when creating a new, or reassessing an established, risk assessment matrix.

Are We Objective? A Study into the Effectiveness of Risk Measurement in the Water Industry

A survey of 77 water practitioners within Melbourne, Australia, highlighted the lack of objectiveness within current risk scoring processes. Each water authority adopted similar processes, all of which adhere to the ISO31000 standard on Risk Management, and these were tested within this study to determine the “objective” nature of technical risk assessments such as these. The outcome of the study indicated that current risk measurement approaches cannot be seen as objective. This is due to the high variation in risk scores between individuals, which indicates a level of subjectivity. The study confirms previous research that has been undertaken in assessing the effectiveness of risk matrices. This research is novel in its testing of the water sector’s risk measuring practices and may be of value to other industries that utilize similar risk approaches. This research posits whether this subjectivity is due to inherent bias of either a psychological or cultural risk nature that could produce the varied scores.

Injury Risk (Burden), Risk Matrices and Risk Contours in Team Sports: A Review of Principles, Practices and Problems

The aim of this review was to provide insights into and a critical assessment of injury burden, risk matrices and risk contours in the context of team sports. Injury burden is the product of injury incidence and mean severity, and is normally reported as days' absence/1000 player-hours. An important feature of injury burden is that equal values can reflect quite different numerical combinations of injury incidence and severity. The timeframe over which injury burden affects a team depends on the incidence and severity values of the injuries sustained. Injury burden is evaluated through the use of risk matrices and risk contours. The main benefits of using risk matrices, and the reasons for their widespread acceptance, are the minimal data inputs required, the ease of understanding the visual data presentation, the transparent nature of the evaluation criteria and the simplicity with which the conclusions can be communicated to stakeholders. Injury burden is most often used for the identification of injuries that cause the greatest loss of time for players, ranking the importance of injury risk factors and prioritising injury prevention plans. Although risk matrices are commonly used for evaluating risks during the risk assessment process, there is little evidence to demonstrate that they improve decision-making, as they have a number of limitations, including potential inconsistencies and discrepancies when evaluating and ranking risks. These limitations suggest that physicians, physiotherapists and sports scientists should only use injury burden, risk matrices and risk contours when they fully understand their strengths and weaknesses.

How to Design Rating Schemes of Risk Matrices: A Sequential Updating Approach

Risk matrices have been widely used as a risk evaluation tool in many fields due to their simplicity and intuitive nature. Designing a rating scheme, i.e., determining the number of ratings used in a risk matrix and assigning different ratings to different cells, is an essential part of risk matrix construction. However, most of the related literature has focused on applying a risk matrix to various fields, instead of researching how to design risk matrices. Based on the analysis of several current rules, we propose a new approach, namely, the sequential updating approach (SUA), to design the rating scheme of a risk matrix in a reliable way. In this article, we propose three principles and a rating algorithm based on these principles. The three principles, namely, adjusted weak consistency, consistent internality, and continuous screening, characterize a good rating scheme. The resulting rating scheme has been proven to be unique. A global rating algorithm is then proposed to create the design that satisfies the three principles. We then explore the performance of the SUA. An illustrative application is first given to explain the feasibility of our approach. The sensitivity analysis shows that our method captures a resolution-reliability tradeoff for decisionmakers in choosing an appropriate rating scheme for a risk matrix. Finally, we compare the designs based on the SUA and Cox's axioms, highlighting the advantages of the SUA.