A Tiered Approach for Risk‐Benefit Assessment of Foods

Risk‐benefit analyses are introduced as a new paradigm for old problems. However, in many cases it is not always necessary to perform a full comprehensive and expensive quantitative risk‐benefit assessment to solve the problem, nor is it always possible, given the lack of required date. The choice to continue from a more qualitative to a full quantitative risk‐benefit assessment can be made using a tiered approach. In this article, this tiered approach for risk‐benefit assessment will be addressed using a decision tree. The tiered approach described uses the same four steps as the risk assessment paradigm: hazard and benefit identification, hazard and benefit characterization, exposure assessment, and risk‐benefit characterization, albeit in a different order. For the purpose of this approach, the exposure assessment has been moved upward and the dose‐response modeling (part of hazard and benefit characterization) is moved to a later stage. The decision tree includes several stop moments, depending on the situation where the gathered information is sufficient to answer the initial risk‐benefit question. The approach has been tested for two food ingredients. The decision tree presented in this article is useful to assist on a case‐by‐case basis a risk‐benefit assessor and policymaker in making informed choices when to stop or continue with a risk‐benefit assessment.     

Risk‐Cost‐Benefit Analysis for Transportation Corridors with Interval Uncertainties of Heterogeneous Data

Access management, which systematically limits opportunities for egress and ingress of vehicles to highway lanes, is critical to protect trillions of dollars of current investment in transportation. This article addresses allocating resources for access management with incomplete and partially relevant data on crash rates, travel speeds, and other factors. While access management can be effective to avoid crashes, reduce travel times, and increase route capacities, the literature suggests a need for performance metrics to guide investments in resource allocation across large corridor networks and several time horizons. In this article, we describe a quantitative decision model to support an access management program via risk‐cost‐benefit analysis under data uncertainties from diverse sources of data and expertise. The approach quantifies potential benefits, including safety improvement and travel time savings, and costs of access management through functional relationships of input parameters including crash rates, corridor access point densities, and traffic volumes. Parameter uncertainties, which vary across locales and experts, are addressed via numerical interval analyses. This approach is demonstrated at several geographic scales across 7,000 kilometers of highways in a geographic region and several subregions. The demonstration prioritizes route segments that would benefit from risk management, including (i) additional data or elicitation, (ii) right‐of‐way purchases, (iii) restriction or closing of access points, (iv) new alignments, (v) developer proffers, and (vi) etc. The approach ought to be of wide interest to analysts, planners, policymakers, and stakeholders who rely on heterogeneous data and expertise for risk management.     

Decision Making for Animal Health and Welfare: Integrating Risk‐Benefit Analysis with Prospect Theory

This study integrated risk‐benefit analysis with prospect theory with the overall objective of identifying the type of management behavior represented by farmers’ choices of mastitis control options (MCOs). Two exploratory factor analyses, based on 163 and 175 Swedish farmers, respectively, highlighted attitudes to MCOs related to: (1) grouping cows and applying milking order to prevent spread of existing infection and (2) working in a precautionary way to prevent mastitis occurring. This was interpreted as being based on (1) reactive management behavior on detection of udder‐health problems in individual cows and (2) proactive management behavior to prevent mastitis developing. Farmers’ assessments of these MCOs were found to be based on asymmetrical evaluations of risks and benefits, suggesting that farmers’ management behavior depends on their individual reference point. In particular, attitudes to MCOs related to grouping cows and applying milking order to prevent the spread of mastitis once infected cows were detected were stronger in the risk domain than in the benefit domain, in accordance with loss aversion. In contrast, attitudes to MCOs related to working in a precautionary way to prevent cows from becoming infected in the first place were stronger in the benefit domain than in the risk domain, in accordance with reverse loss aversion. These findings are of practical importance for farmers and agribusiness and in public health protection work to reduce the current extensive use of antibiotics in dairy herds.     

Public Perceptions of the Potential Hazards Associated with Food Production and Food Consumption: An Empirical Study

Although public perceptions of food-related hazards receive much media comment and debate, the research literature on such perceptions is sparse and piecemeal. In the reported study, 216 people completed a questionnaire relating to their perceptions of the "risk characteristics" of potential hazards associated with various aspects of food production and food consumption. Responses were examined via principal-components analysis to obtain a structural representation of risk perception of the kind provided by Fischhoff, Slovic, and their colleagues in their seminal psychometric work.^(1,2) A three-component solution accounting for 87% of the variance was obtained, with the dimensions labeled as "severity,""unknown," and "number of people exposed." The findings also yielded information pointing to evidence of the phenomenon of unrealistic optimism. We conclude that our findings offer a useful base upon which further in-depth research integrating different perspectives on risk perception with respect to food-related hazards may be developed.     

Determinants of Seeking and Avoiding Risk‐Related Information in Times of Crisis

This research is designed to provide insight into the psychological (e.g., threat appraisal or coping appraisal) and other determinants (e.g., information quality judgments or demographics) of risk information seeking or avoidance in times of an acute risk, as part of the process of increasing public resilience through adherence to risk mitigating advice. Data were collected via telephone interviews. A specialized agency interviewed 1,000 Dutch citizens, randomly confronted with one of eight fictitious, but realistic, acute risk and emergency situations. Results indicate that information seeking in an acute situation is anticipated by a less elaborate set of predictors (age and risk perception) than information seeking in a nonacute situation (age and risk perception, as well as educational level and social norm). Although risk perception is a predictor for risk information seeking, its predictive value for acute‐risk‐related behavior, as one might have assumed based on theories such as protection motivation theory (PMT) or the extended parallel process model (EPPM), appears to be limited. Implications for risk communication are discussed.     

Risk‐Taking and the Media

In recent years, media formats with risk‐glorifying content, such as video games that simulate illegal street racing (“bang and crash” games), films about extreme sports, and risky stunts have emerged as top sellers of the media industry. A variety of recent studies conducted by several researchers revealed that exposure to risk‐glorifying media content (e.g., video games that simulate reckless driving, smoking and drinking in movies, or depictions that glorify extreme sports) increases the likelihood that recipients will show increased levels of risk‐taking inclinations and behaviors. The present article (1) reviews the latest research on the detrimental impact of risk‐glorifying media on risk‐taking inclinations (cognitions, emotions, behaviors), (2) puts these findings in the theoretical context of recent sociocognitive models on media effects, and (3) makes suggestions to science and policymakers on how to deal with these effects in the future.     

The Unintended Effects of Risk‐Refuting Information on Anxiety

Researchers in the field of risk perception have been asking why people are more worried about risk today than in years past. This article explores one possible answer to this question, associative anxiety. The affect heuristic and the mental network models suggest that anxiety triggered by information regarding a particular risk can spread to other risks of the same category. Research to date, however, has not examined how information refuting the particular risk can also be generalized across other risks. The article presents two experimental studies addressing this issue. Study 1 showed that when participants were presented with information based on a real train collision, they experienced increased anxiety not only about train collisions but also about public transportation in general. In contrast, those who were informed about the train collision case as well as the preventative measures implemented after the accident experienced decreased anxiety about train collisions but not about public transportation more generally. Study 2 measured the changes in participant anxiety about a genetically modified organism (GMO) and compared the influence of information about either the existence or nonexistence of its risk. Similar to Study 1, associative anxiety rippled through the risk category. The results also suggest that the follow‐up information refuting the GMO risk reduced the anxiety toward the hazard drastically, but did not fully alleviate the anxiety toward other hazards in the category. The implications and the limitations of these studies are also discussed.     

Channel Coordination with a Risk‐Neutral Supplier and a Downside‐Risk‐Averse Retailer

We investigate how a supply chain involving a risk‐neutral supplier and a downside‐risk‐averse retailer can be coordinated with a supply contract. We show that the standard buy‐back or revenue‐sharing contracts may not coordinate such a channel. Using a definition of coordination of supply chains proposed earlier by the authors, we design a risk‐sharing contract that offers the desired downside protection to the retailer, provides respective reservation profits to the agents, and accomplishes channel coordination.     

General Probability‐Time Tradeoff and Intertemporal Risk‐Value Model

This article proposes an intertemporal risk‐value (IRV) model that integrates probability‐time tradeoff, time‐value tradeoff, and risk‐value tradeoff into one unified framework. We obtain a general probability‐time tradeoff, which yields a formal representation form to reflect the psychological distance of a decisionmaker in evaluating a temporal lottery. This intuition of probability‐time tradeoff is supported by robust empirical findings as well as by psychological theory. Through an explicit formalization of probability‐time tradeoff, an IRV model taking into account three fundamental dimensions, namely, value, probability, and time, is established. The object of evaluation in our framework is a complex lottery. We also give some insights into the structure of the IRV model using a wildcatter problem.     

Coordination of Supply Chains with Risk‐Averse Agents

The extant supply chain management literature has not addressed the issue of coordination in supply chains involving risk‐averse agents. We take up this issue and begin with defining a coordinating contract as one that results in a Pareto‐optimal solution acceptable to each agent. Our definition generalizes the standard one in the risk‐neutral case. We then develop coordinating contracts in three specific cases: (i) the supplier is risk neutral and the retailer maximizes his expected profit subject to a downside risk constraint; (ii) the supplier and the retailer each maximizes his own mean‐variance trade‐off; and (iii) the supplier and the retailer each maximizes his own expected utility. Moreover, in case (iii), we show that our contract yields the Nash Bargaining solution. In each case, we show how we can find the set of Pareto‐optimal solutions, and then design a contract to achieve the solutions. We also exhibit a case in which we obtain Pareto‐optimal sharing rules explicitly, and outline a procedure to obtain Pareto‐optimal solutions.     

Terrorism Risks and Cost‐Benefit Analysis of Aviation Security

We evaluate, for the U.S. case, the costs and benefits of three security measures designed to reduce the likelihood of a direct replication of the 9/11 terrorist attacks. To do so, we assess risk reduction, losses, and security costs in the context of the full set of security layers. The three measures evaluated are installed physical secondary barriers (IPSB) to restrict access to the hardened cockpit door during door transitions, the Federal Air Marshal Service (FAMS), and the Federal Flight Deck Officer (FFDO) Program. In the process, we examine an alternate policy measure: doubling the budget of the FFDO program to $44 million per year, installing IPSBs in all U.S. aircraft at a cost of $13.5 million per year, and reducing funding for FAMS by 75% to $300 million per year. A break‐even cost‐benefit analysis then finds the minimum probability of an otherwise successful attack required for the benefit of each security measures to equal its cost. We find that the IPSB is costeffective if the annual attack probability of an otherwise successful attack exceeds 0.5% or one attack every 200 years. The FFDO program is costeffective if the annual attack probability exceeds 2%. On the other hand, more than two otherwise successful attacks per year are required for FAMS to be costeffective. A policy that includes IPSBs, an increased budget for FFDOs, and a reduced budget for FAMS may be a viable policy alternative, potentially saving hundreds of millions of dollars per year with consequences for security that are, at most, negligible.     

Risk‐Based Sampling: I Don't Want to Weight in Vain

Recently, there has been considerable interest in developing risk‐based sampling for food safety and animal and plant health for efficient allocation of inspection and surveillance resources. The problem of risk‐based sampling allocation presents a challenge similar to financial portfolio analysis. Markowitz (1952) laid the foundation for modern portfolio theory based on mean‐variance optimization. However, a persistent challenge in implementing portfolio optimization is the problem of estimation error, leading to false “optimal” portfolios and unstable asset weights. In some cases, portfolio diversification based on simple heuristics (e.g., equal allocation) has better out‐of‐sample performance than complex portfolio optimization methods due to estimation uncertainty. Even for portfolios with a modest number of assets, the estimation window required for true optimization may imply an implausibly long stationary period. The implications for risk‐based sampling are illustrated by a simple simulation model of lot inspection for a small, heterogeneous group of producers.     

Food Safety in the Domestic Environment: The Effect of Consumer Risk Information on Human Disease Risks

The improvement of food safety in the domestic environment requires a transdisciplinary approach, involving interaction between both the social and natural sciences. This approach is applied in a study on risks associated with Campylobacter on broiler meat. First, some web-based information interventions were designed and tested on participant motivation and intentions to cook more safely. Based on these self-reported measures, the intervention supported by the emotion "disgust" was selected as the most promising information intervention. Its effect on microbial cross-contamination was tested by recruiting a set of participants who prepared a salad with chicken breast fillet carrying a known amount of tracer bacteria. The amount of tracer that could be recovered from the salad revealed the transfer and survival of Campylobacter and was used as a measure of hygiene. This was introduced into an existing risk model on Campylobacter in the Netherlands to assess the effect of the information intervention both at the level of exposure and the level of human disease risk. We showed that the information intervention supported by the emotion "disgust" alone had no measurable effect on the health risk. However, when a behavioral cue was embedded within the instruction for the salad preparation, the risk decreased sharply. It is shown that a transdisciplinary approach, involving research on risk perception, microbiology, and risk assessment, is successful in evaluating the efficacy of an information intervention in terms of human health risks. The approach offers a novel tool for science-based risk management in the area of food safety.     

Assessing Risk‐Based Upper Limits of Melamine Migration from Food Containers

Melamine contamination of food has become a major food safety issue because of incidents of infant disease caused by exposure to this chemical. This study was aimed at establishing a safety limit in Taiwan for the degree of melamine migration from food containers. Health risk assessment was performed for three exposure groups (preschool children, individuals who dine out, and elderly residents of nursing homes). Selected values of tolerable daily intake (TDI) for melamine were used to calculate the reference migration concentration limit (RMCL) or reference specific migration limit (RSML) for melamine food containers. The only existing values of these limits for international standards today are 1.2 mg/L (0.2 mg/dm²) in China and 30 mg/L (5 mg/dm²) in the European Union. The factors used in the calculations included the specific surface area of food containers, daily food consumption rate, body weight, TDI, and the percentile of the population protected at a given migration concentration limit (MCL). The results indicate that children are indeed at higher risk of melamine exposure at toxic levels than are other groups and that the 95th percentile of MCL (specific surface area = 5) for children aged 1–6 years should be the RMCL (0.07 mg/dm²) for protecting the sensitive and general population.     

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.     

The Value of a Statistical Life for Risk‐Averse and Risk‐Seeking Individuals

This article estimates the value of a statistical life (VSL) for Chile under the hedonic wage method while accounting for individual risk preferences. Two alternative measures of risk aversion are used. First, risk aversion is directly measured using survey measures of preferences over hypothetical gambles, and second, over observed individual behaviors that may proxy for risk preferences, such as smoking status, are used. I reconcile the results with a theoretical model of economic behavior that predicts how the wage‐risk tradeoff changes as risk aversion differs across individuals. The VSL estimates range between 0.61 and 8.68 million dollars. The results using smoking behavior as a proxy for risk attitudes are consistent with previous findings. However, directly measuring risk aversion corrects the wage‐risk tradeoff estimation bias in the opposite direction. The results are robust to other observed measures of risk aversion such as drinking behavior and stock investments. Results suggest that, consistent with the literature that connects smoking behavior with labor market outcomes, smoking status could be capturing poor health productivity effect in addition to purely risk preferences.     

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.     

Development of Dose‐Response Models to Predict the Relationship for Human Toxoplasma gondii Infection Associated with Meat Consumption

Toxoplasma gondii is a protozoan parasite that is responsible for approximately 24% of deaths attributed to foodborne pathogens in the United States. It is thought that a substantial portion of human T. gondii infections is acquired through the consumption of meats. The dose‐response relationship for human exposures to T. gondii‐infected meat is unknown because no human data are available. The goal of this study was to develop and validate dose‐response models based on animal studies, and to compute scaling factors so that animal‐derived models can predict T. gondii infection in humans. Relevant studies in literature were collected and appropriate studies were selected based on animal species, stage, genotype of T. gondii, and route of infection. Data were pooled and fitted to four sigmoidal‐shaped mathematical models, and model parameters were estimated using maximum likelihood estimation. Data from a mouse study were selected to develop the dose‐response relationship. Exponential and beta‐Poisson models, which predicted similar responses, were selected as reasonable dose‐response models based on their simplicity, biological plausibility, and goodness fit. A confidence interval of the parameter was determined by constructing 10,000 bootstrap samples. Scaling factors were computed by matching the predicted infection cases with the epidemiological data. Mouse‐derived models were validated against data for the dose‐infection relationship in rats. A human dose‐response model was developed as P (d) = 1–exp (–0.0015 × 0.005 × d) or P (d) = 1–(1 + d × 0.003 / 582.414)^?1.479. Both models predict the human response after consuming T. gondii‐infected meats, and provide an enhanced risk characterization in a quantitative microbial risk assessment model for this pathogen.     

Cost‐Benefit Analysis of Passive Fire Protections in Road LPG Transportation

The cost‐benefit evaluation of passive fire protection adoption in the road transport of liquefied petroleum gas (LPG) was investigated. In a previous study, mathematical simulations of real scale fire scenarios proved the effectiveness of passive fire protections in preventing the “fired” boiling liquid expanding vapor explosion (BLEVE), thus providing a significant risk reduction. In the present study the economical aspects of the adoption of fire protections are analyzed and an approach to cost‐benefit analysis (CBA) is proposed. The CBA model is based on the comparison of the risk reduction due to fire protections (expressed in monetary terms by the value of a statistical life) and the cost of the application of fire protections to a fleet of tankers. Different types of fire protections were considered, as well as the possibility to apply protections to the entire fleet or only to a part of it. The application of the proposed model to a real‐life case study is presented and discussed. Results demonstrate that the adoption of passive fire protections on road tankers, though not compulsory in Europe, can be economically feasible, thus representing a concrete measure to achieve control of the “major hazard accidents” cited by the European legislation.     

Modeling Risk‐Related Knowledge in Tunneling Projects

Knowledge on failure events and their associated factors, gained from past construction projects, is regarded as potentially extremely useful in risk management. However, a number of circumstances are constraining its wider use. Such knowledge is usually scarce, seldom documented, and even unavailable when it is required. Further, there exists a lack of proven methods to integrate and analyze it in a cost‐effective way. This article addresses possible options to overcome these difficulties. Focusing on limited but critical potential failure events, the article demonstrates how knowledge on a number of important potential failure events in tunnel works can be integrated. The problem of unavailable or incomplete information was addressed by gathering judgments from a group of experts. The elicited expert knowledge consisted of failure scenarios and associated probabilistic information. This information was integrated using Bayesian belief‐networks‐based models that were first customized in order to deal with the expected divergence in judgments caused by epistemic uncertainty of risks. The work described in the article shows that the developed models that integrate risk‐related knowledge provide guidance as to the use of specific remedial measures.