Deciding with Thresholds: Importance Measures and Value of Information

Risk‐informed decision making is often accompanied by the specification of an acceptable level of risk. Such target level is compared against the value of a risk metric, usually computed through a probabilistic safety assessment model, to decide about the acceptability of a given design, the launch of a space mission, etc. Importance measures complement the decision process with information about the risk/safety significance of events. However, importance measures do not tell us whether the occurrence of an event can change the overarching decision. By linking value of information and importance measures for probabilistic risk assessment models, this work obtains a value‐of‐information‐based importance measure that brings together the risk metric, risk importance measures, and the risk threshold in one expression. The new importance measure does not impose additional computational burden because it can be calculated from our knowledge of the risk achievement and risk reduction worth, and complements the insights delivered by these importance measures. Several properties are discussed, including the joint decision worth of basic event groups. The application to the large loss of coolant accident sequence of the Advanced Test Reactor helps us in illustrating the risk analysis insights.     

Learning from the Piper Alpha Accident: A Postmortem Analysis of Technical and Organizational Factors

The accident that occurred on board the offshore platform Piper Alpha in July 1988 killed 167 people and cost billions of dollars in property damage. It was caused by a massive fire, which was not the result of an unpredictable "act of God" but of an accumulation of errors and questionable decisions. Most of them were rooted in the organization, its structure, procedures, and culture. This paper analyzes the accident scenario using the risk analysis framework, determines which human decision and actions influenced the occurrence of the basic events, and then identifies the organizational roots of these decisions and actions. These organizational factors are generalizable to other industries and engineering systems. They include flaws in the design guidelines and design practices (e.g., tight physical couplings or insufficient redundancies), misguided priorities in the management of the tradeoff between productivity and safety, mistakes in the management of the personnel on board, and errors of judgment in the process by which financial pressures are applied on the production sector (i.e., the oil companies' definition of profit centers) resulting in deficiencies in inspection and maintenance operations. This analytical approach allows identification of risk management measures that go beyond the purely technical (e.g., add redundancies to a safety system) and also include improvements of management practices.     

Domain Effects and Financial Risk Attitudes

We investigated whether financial risk preferences are dependent on the financial domain (i.e., the context) in which the risky choice options are presented. Previous studies have demonstrated that risk attitudes change when gambles are framed as gains, losses, or as insurance. Our study explores this directly by offering choices between identical gambles, framed in terms of seven financial domains. Three factors were extracted, explaining 68.6% of the variance: Factor 1 (Positive)—opportunity to win, pension provision, and job salary change; Factor 2 (Positive‐Complex)—investments and mortgage buying; Factor 3 (Negative)—possibility of loss and insurance. Inspection of the solution revealed context effects on risk perceptions across the seven scenarios. We also found that the commonly accepted assumption that women are more risk averse cannot be confirmed with the context structure suggested in this research; however, it is acknowledged that in the students’ population the variance across genders might be considerably less. These results suggest that our financial risk attitude measures may be tapping into a stable aspect of “context dependence” of relevance to real‐world decision making.     

The Risk Management of Third Parties During Construction in Multifunctional Urban Locations

Buildings above roads, railways, and existing buildings themselves are examples of multifunctional urban locations. The construction stage of those buildings is in general extremely complicated. Safety is one of the critical issues during the construction stage. Because the traffic on the infrastructure must continue during the construction of the building above the infrastructure, falling objects due to construction activities form a major hazard for third parties, i.e., people present on the infrastructure or beneath it, such as car drivers and passengers. This article outlines a systematic approach to conduct quantitative risk assessment (QRA) and risk management of falling elements for third parties during the construction stage of the building above the infrastructure in multifunctional urban locations. In order to set up a QRA model, quantifiable aspects influencing the risk for third parties were determined. Subsequently, the conditional probabilities of these aspects were estimated by historical data or engineering judgment. This was followed by integrating those conditional probabilities, now used as input parameters for the QRA, into a Bayesian network representing the relation and the conditional dependence between the quantified aspects. The outcome of the Bayesian network—the calculation of both the human and financial risk in quantitative terms—is compared with the risk acceptance criteria as far as possible. Furthermore, the effect of some safety measures were analyzed and optimized in relation with decision making. Finally, the possibility of integration of safety measures in the functional and structural building design above the infrastructure are explored.     

Risk Perception and the Value of Safety

This paper examines the relationship between perceived risk and willingness-to-pay (WTP) for increased safety from technological hazards in both conceptual and empirical terms. A conceptual model is developed in which a given household's WTP for risk reductions is a function of traditional socioeconomic variables (i.e., income and base level of risk) and perceived characteristics of the hazards (i.e., dread, knowledge, and exposure). Data to estimate the model are obtained through a combined contingent valuation and risk perception survey that considers 10 technological hazards, five of which are well-defined (e.g., death rates are known and the risks are relatively common) and five are less well-defined. Econometric results, using TOBIT estimation procedures, support the importance of both types of variables in explaining WTP across all 10 hazards. When the risks are split into two groups, the results show that WTP for well-defined hazards is most influenced by perceived personal exposure, while WTP for less well-defined risks is most influenced by levels of dread and severity.     

Risk-Based Ranking of Dominant Contributors to Maritime Pollution Events

This report describes a conceptual approach for identifying dominant contributors to risk from maritime shipping of hazardous materials. Maritime transportation accidents are relatively common occurrences compared to more frequently analyzed contributors to public risk. Yet research on maritime safety and pollution incidents has not been guided by a systematic, risk-based approach. Maritime shipping accidents can be analyzed using event trees to group the accidents into "bins," or groups, of similar characteristics such as type of cargo, location of accident (e.g., harbor, inland waterway), type of accident (e.g., fire, collision, grounding), and size of release. The importance of specific types of events to each accident bin can be quantified. Then the overall importance of accident events to risk can be estimated by weighting the events' individual bin importance measures by the risk associated with each accident bin.     

An Integrated Framework for Environmental Multi‐Impact Spatial Risk Analysis

Quantitative risk analysis is being extensively employed to support policymakers and provides a strong conceptual framework for evaluating decision alternatives under uncertainty. Many problems involving environmental risks are, however, of a spatial nature, i.e., containing spatial impacts, spatial vulnerabilities, and spatial risk‐mitigation alternatives. Recent developments in multicriteria spatial analysis have enabled the assessment and aggregation of multiple impacts, supporting policymakers in spatial evaluation problems. However, recent attempts to conduct spatial multicriteria risk analysis have generally been weakly conceptualized, without adequate roots in quantitative risk analysis. Moreover, assessments of spatial risk often neglect the multidimensional nature of spatial impacts (e.g., social, economic, human) that are typically occurring in such decision problems. The aim of this article is therefore to suggest a conceptual quantitative framework for environmental multicriteria spatial risk analysis based on expected multi‐attribute utility theory. The framework proposes: (i) the formal assessment of multiple spatial impacts; (ii) the aggregation of these multiple spatial impacts; (iii) the assessment of spatial vulnerabilities and probabilities of occurrence of adverse events; (iv) the computation of spatial risks; (v) the assessment of spatial risk mitigation alternatives; and (vi) the design and comparison of spatial risk mitigation alternatives (e.g., reductions of vulnerabilities and/or impacts). We illustrate the use of the framework in practice with a case study based on a flood‐prone area in northern Italy.     

Offenders’ Risk‐Taking Attitude Inside and Outside the Prison Walls

It has long been assumed that risk taking is closely associated with criminal behavior. One reason for placing criminals behind bars—aside from punishment and protecting the public—is to prevent them from engaging in further risky criminal activities. Limited attention has been paid to whether being inside or outside prison affects offenders’ risk‐taking behaviors and attitudes. We compared risk‐taking behaviors and attitudes in five risk domains (ethical, financial, health/safety, recreational, social) among 75 incarcerated offenders (i.e., offenders who are currently in prison) and 45 ex‐offenders (i.e., offenders who have just been released from prison). Ex‐offenders reported higher likelihood of engaging in risky behavior, driven largely by a willingness to take more risks in the recreational and ethical domains. Benefits attributed to risk taking as well as risk perception did not differ between incarcerated and ex‐offenders, indicating that the opportunity to take risks might underlie behavioral risk intentions. Our results also indicate that risk‐taking activities are better predicted by the expected benefits rather than by risk perception, aside from the health/safety domain. These results highlight the importance of studying the person and the environment and examining risk taking in a number of content domains.     

Ensuring the Quality of Occupational Safety Risk Assessment

In work environments, the main aim of occupational safety risk assessment (OSRA) is to improve the safety level of an installation or site by either preventing accidents and injuries or minimizing their consequences. To this end, it is of paramount importance to identify all sources of hazards and assess their potential to cause problems in the respective context. If the OSRA process is inadequate and/or not applied effectively, it results in an ineffective safety prevention program and inefficient use of resources. An appropriate OSRA is an essential component of the occupational safety risk management process in industries. In this article, we performed a survey to elicit the relative importance for identified OSRA tasks to enable an in‐depth evaluation of the quality of risk assessments related to occupational safety aspects on industrial sites. The survey involved defining a questionnaire with the most important elements (tasks) for OSRA quality assessment, which was then presented to safety experts in the mining, electrical power production, transportation, and petrochemical industries. With this work, we expect to contribute to the main question of OSRA in industries: “What constitutes a good occupational safety risk assessment?” The results obtained from the questionnaire showed that experts agree with the proposed OSRA process decomposition in steps and tasks (taxonomy) and also with the importance of assigning weights to obtain knowledge about OSRA task relevance. The knowledge gained will enable us, in the near future, to build a framework to evaluate OSRA quality for industrial sites.     

Cost‐Benefit Analysis for Optimization of Risk Protection Under Budget Constraints

Cost‐benefit analysis (CBA) is commonly applied as a tool for deciding on risk protection. With CBA, one can identify risk mitigation strategies that lead to an optimal tradeoff between the costs of the mitigation measures and the achieved risk reduction. In practical applications of CBA, the strategies are typically evaluated through efficiency indicators such as the benefit‐cost ratio (BCR) and the marginal cost (MC) criterion. In many of these applications, the BCR is not consistently defined, which, as we demonstrate in this article, can lead to the identification of suboptimal solutions. This is of particular relevance when the overall budget for risk reduction measures is limited and an optimal allocation of resources among different subsystems is necessary. We show that this problem can be formulated as a hierarchical decision problem, where the general rules and decisions on the available budget are made at a central level (e.g., central government agency, top management), whereas the decisions on the specific measures are made at the subsystem level (e.g., local communities, company division). It is shown that the MC criterion provides optimal solutions in such hierarchical optimization. Since most practical applications only include a discrete set of possible risk protection measures, the MC criterion is extended to this situation. The findings are illustrated through a hypothetical numerical example. This study was prepared as part of our work on the optimal management of natural hazard risks, but its conclusions also apply to other fields of risk management.     

Growing Pains: How Risk Perception and Risk Communication Research Can Help to Manage the Challenges of Global Population Growth

In 2011, the global human population reached 7 billion and medium variant projections indicate that it will exceed 9 billion before 2045. Theoretical and empirical perspectives suggest that this growth could lead to an increase in the likelihood of adverse events (e.g., food shortages, climate change, etc.) and/or the severity of adverse events (e.g., famines, natural disasters, etc.). Several scholars have posited that the size to which the global population grows and the extent to which this growth increases the likelihood of adverse outcomes will largely be shaped by individuals’ decisions (in households, organizations, governments, etc.). In light of the strong relationship between perceived risk and decision behaviors, it is surprising that there remains a dearth of empirical research that specifically examines the perceived risks of population growth and how these perceptions might influence related decisions. In an attempt to motivate this important strand of research, this article examines the major risks that may be exacerbated by global population growth and draws upon empirical work concerning the perception and communication of risk to identify potential directions for future research. The article also considers how individuals might perceive both the risks and benefits of population growth and be helped to better understand and address the related issues. The answers to these questions could help humanity better manage the emerging consequences of its continuing success in increasing infant survival and adult longevity.     

Tree‐Based Logistic Regression Approach for Work Zone Casualty Risk Assessment

This study presents a tree‐based logistic regression approach to assessing work zone casualty risk, which is defined as the probability of a vehicle occupant being killed or injured in a work zone crash. First, a decision tree approach is employed to determine the tree structure and interacting factors. Based on the Michigan M‐94\I‐94\I‐94BL\I‐94BR highway work zone crash data, an optimal tree comprising four leaf nodes is first determined and the interacting factors are found to be airbag, occupant identity (i.e., driver, passenger), and gender. The data are then split into four groups according to the tree structure. Finally, the logistic regression analysis is separately conducted for each group. The results show that the proposed approach outperforms the pure decision tree model because the former has the capability of examining the marginal effects of risk factors. Compared with the pure logistic regression method, the proposed approach avoids the variable interaction effects so that it significantly improves the prediction accuracy.     

Designing Graphs that Promote Both Risk Understanding and Behavior Change

Graphs show promise for improving communications about different types of risks, including health risks, financial risks, and climate risks. However, graph designs that are effective at meeting one important risk communication goal (promoting risk‐avoidant behaviors) can at the same time compromise another key goal (improving risk understanding). We developed and tested simple bar graphs aimed at accomplishing these two goals simultaneously. We manipulated two design features in graphs, namely, whether graphs depicted the number of people affected by a risk and those at risk of harm (“foreground+background”) versus only those affected (“foreground‐only”), and the presence versus absence of simple numerical labels above bars. Foreground‐only displays were associated with larger risk perceptions and risk‐avoidant behavior (i.e., willingness to take a drug for heart attack prevention) than foreground+background displays, regardless of the presence of labels. Foreground‐only graphs also hindered risk understanding when labels were not present. However, the presence of labels significantly improved understanding, eliminating the detrimental effect of foreground‐only displays. Labels also led to more positive user evaluations of the graphs, but did not affect risk‐avoidant behavior. Using process modeling we identified mediators (risk perceptions, understanding, user evaluations) that explained the effect of display type on risk‐avoidant behavior. Our findings contribute new evidence to the graph design literature: unlike what was previously feared, we demonstrate that it is possible to design foreground‐only graphs that promote intentions for behavior change without a detrimental effect on risk understanding. Implications for the design of graphical risk communications and decision support are discussed.     

考虑风险规避的资金约束供应链最优信用契约设计

本文针对零售商的资金约束问题,研究了风险规避的供应商如何通过设计信用契约影响零售商的融资结构。构建了包含供应商、零售商以及银行在内的供应链融资模型,给出了供应商的最优信用契约决策、零售商的最优库存决策以及银行的最优利率决策。进一步分析了供应商的风险规避程度对最优信用契约决策的影响。研究表明：当供应商的风险规避程度低于某个临界值时,供应商偏好提供全额信用,从而零售商的融资结构为单一的交易信用融资;而当供应商的风险规避程度高于该临界值时,供应商偏好提供部分信用,从而零售商的融资结构为组合融资。最后,通过数值算例验证了本文的结论。本研究一定程度上丰富了现有供应链金融的理论研究,为供应链核心企业与银行的决策提供了依据与参考。     

“The Dose Makes the Poison”: Informing Consumers About the Scientific Risk Assessment of Food Additives

Intensive risk assessment is required before the approval of food additives. During this process, based on the toxicological principle of “the dose makes the poison,? maximum usage doses are assessed. However, most consumers are not aware of these efforts to ensure the safety of food additives and are therefore sceptical, even though food additives bring certain benefits to consumers. This study investigated the effect of a short video, which explains the scientific risk assessment and regulation of food additives, on consumers’ perceptions and acceptance of food additives. The primary goal of this study was to inform consumers and enable them to construct their own risk‐benefit assessment and make informed decisions about food additives. The secondary goal was to investigate whether people have different perceptions of food additives of artificial (i.e., aspartame) or natural origin (i.e., steviolglycoside). To attain these research goals, an online experiment was conducted on 185 Swiss consumers. Participants were randomly assigned to either the experimental group, which was shown a video about the scientific risk assessment of food additives, or the control group, which was shown a video about a topic irrelevant to the study. After watching the video, the respondents knew significantly more, expressed more positive thoughts and feelings, had less risk perception, and more acceptance than prior to watching the video. Thus, it appears that informing consumers about complex food safety topics, such as the scientific risk assessment of food additives, is possible, and using a carefully developed information video is a successful strategy for informing consumers.     

Understanding the Positive Effects of Graphical Risk Information on Comprehension: Measuring Attention Directed to Written,Tabular, and Graphical Risk Information

Risk communications are an integral aspect of health education and promotion. However, the commonly used textual risk information is relatively difficult to understand for the average recipient. Consequently, researchers and health promoters have started to focus on so‐called decision aids, such as tables and graphs. Although tabular and graphical risk information more effectively communicate risks than textual risk information, the cognitive mechanisms responsible for this enhancement are unclear. This study aimed to examine two possible mechanisms (i.e., cognitive workload and attention). Cognitive workload (mean pupil size and peak pupil dilation) and attention directed to the risk information (viewing time, number of eye fixations, and eye fixation durations) were both measured in a between‐subjects experimental design. The results suggest that graphical risk information facilitates comprehension of that information because it attracts and holds attention for a longer period of time than textual risk information. Graphs are thus a valuable asset to risk communication practice for two reasons: first, they tend to attract attention and, second, when attended to, they elicit information extraction with relatively little cognitive effort, and finally result in better comprehension.     

Risk Prevention and Policy-Making in Automatic Systems

Accidents with automatic production systems are reported to be on the order of one in a hundred or thousand robot-years, while fatal accidents are found to occur one or two orders of magnitude less frequently. Traditions in occupational safety tend to seek for safety targets in terms of zero severe accidents for automatic systems. Decision-making requires a risk assessment balancing potential risk reduction measures and costs within the cultural environment of a production company. This paper presents a simplified procedure which acts as a decision tool. The procedure is based on a risk concept approaching prevention both in a deterministic and in a probabilistic manner. Eight accident scenarios are shown to represent the potential accident processes involving robot interactions with people. Seven prevention policies are shown to cover the accident scenarios in principle. An additional probabilistic approach may indicate which extra safety measures can be taken against what risk reduction and additional costs. The risk evaluation process aims at achieving a quantitative acceptable risk level. For that purpose, three risk evaluation methods are discussed with respect to reaching broad consensus on the safety targets.     

Deliberation: Integrating Analytical Results into Environmental Decisions Involving Multiple Stakeholders

The National Research Council has recommended the use of an analytic/deliberative decision making process in environmental restoration decisions that involve multiple stakeholders. This work investigates the use of the results of risk assessment and multiattribute utility analysis (the "analysis") in guiding the deliberation. These results include the ranking of proposed remedial action alternatives according to each stakeholder's preferences, as well as the identification of the major reasons for these rankings. The stakeholder preferences are over a number of performance measures that include the traditional risk assessment metrics, e.g., individual worker risk, as well as programmatic, cultural, and cost-related impacts. Based on these results, a number of proposals are prepared for consideration by the stakeholders during the deliberation. These proposals are the starting point for the formulation of actual recommendations by the group. In our case study, these recommendations included new remedial action alternatives that were created by the stakeholders after an extensive discussion of the detailed analytical results.     

Use of Advances in Technology for Maritime Risk Assessment

The maritime industry is moving toward a "goal-setting" risk-based regime. This opens the way to safety engineers to explore and exploit flexible and advanced risk modeling and decision-making approaches in the design and operation processes. In this article, following a brief review of the current status of maritime risk assessment, a design/operation selection framework and a design/operation optimization framework are outlined. A general discussion of control engineering techniques and their application to risk modeling and decision making is given. Four novel risk modeling and decision-making approaches are then outlined with illustrative examples to demonstrate their use. Such approaches may be used as alternatives to facilitate risk modeling and decision making in situations where conventional techniques cannot be appropriately applied. Finally, recommendations on further exploitation of advances in general engineering and technology are suggested with respect to risk modeling and decision making.     

Marginal Trust in Risk Managers: Building and Losing Trust Following Decisions Under Uncertainty

Although a considerable amount of research has examined correlates of baseline public trust in risk managers, much less research has looked at marginal changes in public trust following specific events. Such research is important for identifying what kinds of events will lead to increases and decreases in public trust and thus for understanding how trust is built and lost. Using a taxonomy based upon signal detection theory (SDT), the current article presents two experimental studies examining marginal trust change following eight different types of events. Supporting predictions, cautious decisionmakers who accepted signs of danger (Hits and False Alarms) were more likely to be trusted than those who rejected them (All Clears and Misses). Moreover, transparency about an event was associated with higher levels of marginal trust than a lack of transparency in line with earlier findings. Contrary to predictions, however, trust was less affected by whether the decisions were correct (i.e., Hits and All Clears) or incorrect (i.e., False Alarms and Misses). This finding was primarily due to a "False Alarm Effect" whereby Open False Alarms led to positive increases in trust despite being incorrect assessments of risk. Results are explained in terms of a cue diagnosticity account of impression formation and suggest that a taxonomy of event types based on SDT may be useful in furthering our understanding of how public trust in risk managers is gained and lost.