Risk Analysis

Publisher: Society for Risk Analysis, Wiley

Journal description

Current impact factor: 2.28

Impact Factor Rankings

2015 Impact Factor Available summer 2015
2011 Impact Factor 2.366

Additional details

5-year impact 2.47
Cited half-life 8.50
Immediacy index 0.78
Eigenfactor 0.01
Article influence 0.86
Other titles Risk analysis (Online), Risk analysis
ISSN 1539-6924
OCLC 45175725
Material type Document, Periodical, Internet resource
Document type Internet Resource, Computer File, Journal / Magazine / Newspaper

Publisher details

Wiley

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    • 2 years embargo
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    • On author's personal website, institutional repositories, arXiv, AgEcon, PhilPapers, PubMed Central, RePEc or Social Science Research Network
    • Author's pre-print may not be updated with Publisher's Version/PDF
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    • On a non-profit server
    • Publisher's version/PDF cannot be used
    • Publisher source must be acknowledged with citation
    • Must link to publisher version with set statement (see policy)
    • If OnlineOpen is available, BBSRC, EPSRC, MRC, NERC and STFC authors, may self-archive after 12 months
    • If OnlineOpen is available, AHRC and ESRC authors, may self-archive after 24 months
    • Publisher last contacted on 07/08/2014
    • This policy is an exception to the default policies of 'Wiley'
  • Classification
    ​ yellow

Publications in this journal

  • [Show abstract] [Hide abstract]
    ABSTRACT: Occupational risk rates per hour of exposure have been quantified for 63 occupational accident types for the Dutch working population. Data were obtained from the analysis of more than 9,000 accidents that occurred over a period of six years in the Netherlands and resulted in three types of reportable consequences under Dutch law: (a) fatal injury, (b) permanent injury, and (c) serious recoverable injury requiring at least one day of hospitalization. A Bayesian uncertainty assessment on the value of the risk rates has been performed. Annual risks for each of the 63 occupational accident types have been calculated, including the variability in the annual exposure of the working population to the corresponding hazards. The suitability of three risk measures-individual risk rates, individual annual risk, and number of accidents-is examined and discussed. © 2015 Society for Risk Analysis.
    Risk Analysis 02/2015; DOI:10.1111/risa.12354
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    ABSTRACT: The burden of Salmonella entering pig slaughterhouses across the European Union is considered a primary food safety concern. To assist E.U. member states with the development of national control plans, we have developed a farm transmission model applicable to all member states. It is an individual-based stochastic susceptible-infected model that takes into account four different sources of infection of pigs (sows, feed, external contaminants such as rodents, and new stock) and various management practices linked to Salmonella transmission/protection (housing, flooring, feed, all-in-all-out production). A novel development within the model is the assessment of dynamic shedding rates. The results of the model, parameterized for two case study member states (one high and one low prevalence) suggest that breeding herd prevalence is a strong indicator of slaughter pig prevalence. Until a member state's' breeding herd prevalence is brought below 10%, the sow will be the dominant source of infection to pigs raised for meat production; below this level of breeding herd prevalence, feed becomes the dominant force of infection. © 2015 Society for Risk Analysis.
    Risk Analysis 02/2015; DOI:10.1111/risa.12356
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    ABSTRACT: In three waves, this study investigates the impact of risk and benefit knowledge on attitude formation toward genetically modified (GM) foods as well as the moderating effect of knowledge level on attitude change caused by receiving information. The data in Wave 1 (N = 561) demonstrate that both benefit and risk knowledge either directly contribute to attitude formation or indirectly affect attitudes through the mediating roles of benefit and risk perceptions. Overall, benefit and risk knowledge affect consumer attitudes positively and negatively, respectively. In Wave 2, 486 participants from Wave 1 were provided with information about GM foods, and their attitudes were assessed. Three weeks later, 433 of these participants again reported their attitudes. The results indicate that compared with the benefit and mixed information, risk information has a greater and longer lasting impact on attitude change, which results in lower acceptance of GM foods. Furthermore, risk information more strongly influences participants with a higher knowledge level. The moderating effect of knowledge on attitude change may result from these participants' better understanding of and greater trust in the information. These findings highlight the important role of knowledge in attitude formation and attitude change toward GM foods as well as the necessity of considering the determinants of attitude formation in attitude change studies. © 2014 Society for Risk Analysis.
    Risk Analysis 02/2015; DOI:10.1111/risa.12319
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    ABSTRACT: Public companies in the United States are required to report standardized values of their proved reserves and asset retirement obligations on an annual basis. When compared, these two measures provide an aggregate indicator of corporate decommissioning risk but, because of their consolidated nature, cannot readily be decomposed at a more granular level. The purpose of this article is to introduce a decommissioning risk metric defined in terms of the ratio of the expected value of an asset's reserves to its expected cost of decommissioning. Asset decommissioning risk (ADR) is more difficult to compute than a consolidated corporate risk measure, but can be used to quantify the decommissioning risk of structures and to perform regional comparisons, and also provides market signals of future decommissioning activity. We formalize two risk metrics for decommissioning and apply the ADR metric to the deepwater Gulf of Mexico (GOM) floater inventory. Deepwater oil and gas structures are expensive to construct, and at the end of their useful life, will be expensive to decommission. The value of proved reserves for the 42 floating structures in the GOM circa January 2013 is estimated to range between $37 and $80 billion for future oil prices between 60 and 120 $/bbl, which is about 10 to 20 times greater than the estimated $4.3 billion to decommission the inventory. Eni's Allegheny and MC Offshore's Jolliet tension leg platforms have ADR metrics less than one and are approaching the end of their useful life. Application of the proposed metrics in the regulatory review of supplemental bonding requirements in the U.S. Outer Continental Shelf is suggested to complement the current suite of financial metrics employed. © 2015 Society for Risk Analysis.
    Risk Analysis 02/2015; DOI:10.1111/risa.12349
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    ABSTRACT: Unmanned aircraft, or drones, are a rapidly emerging sector of the aviation industry. There has been limited substantive research, however, into the public perception and acceptance of drones. This article presents the results from two surveys of the Australian public designed to investigate (1) whether the public perceive drones to be riskier than existing manned aviation, (2) whether the terminology used to describe the technology influences public perception, and (3) what the broader concerns are that may influence public acceptance of the technology. We find that the Australian public currently hold a relatively neutral attitude toward drones. Respondents did not consider the technology to be overly unsafe, risky, beneficial, or threatening. Drones are largely viewed as being of comparable risk to that of existing manned aviation. Furthermore, terminology had a minimal effect on the perception of the risks or acceptability of the technology. The neutral response is likely due to a lack of knowledge about the technology, which was also identified as the most prevalent public concern as opposed to the risks associated with its use. Privacy, military use, and misuse (e.g., terrorism) were also significant public concerns. The results suggest that society is yet to form an opinion of drones. As public knowledge increases, the current position is likely to change. Industry communication and media coverage will likely influence the ultimate position adopted by the public, which can be difficult to change once established. © 2014 Society for Risk Analysis.
    Risk Analysis 02/2015; DOI:10.1111/risa.12330
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    ABSTRACT: Wind power is becoming an increasingly important part of the global energy portfolio, and there is growing interest in developing offshore wind farms in the United States to better utilize this resource. Wind farms have certain environmental benefits, notably near-zero emissions of greenhouse gases, particulates, and other contaminants of concern. However, there are significant challenges ahead in achieving large-scale integration of wind power in the United States, particularly offshore wind. Environmental impacts from wind farms are a concern, and these are subject to a number of on-going studies focused on risks to the environment. However, once a wind farm is built, the farm itself will face a number of risks from a variety of hazards, and managing these risks is critical to the ultimate achievement of long-term reductions in pollutant emissions from clean energy sources such as wind. No integrated framework currently exists for assessing risks to offshore wind farms in the United States, which poses a challenge for wind farm risk management. In this "Perspective", we provide an overview of the risks faced by an offshore wind farm, argue that an integrated framework is needed, and give a preliminary starting point for such a framework to illustrate what it might look like. This is not a final framework; substantial work remains. Our intention here is to highlight the research need in this area in the hope of spurring additional research about the risks to wind farms to complement the substantial amount of on-going research on the risks from wind farms. © 2014 Society for Risk Analysis.
    Risk Analysis 02/2015; DOI:10.1111/risa.12324
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    ABSTRACT: 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. © 2015 Society for Risk Analysis.
    Risk Analysis 02/2015; DOI:10.1111/risa.12310
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    ABSTRACT: Inappropriate measures of exposure, including inadequate consideration of latency in the analysis of chronic effects of air pollution, may lead to overestimation of the impact of air pollution on health effects. A relatively simple way to check the plausibility of results on chronic effects of air pollution would be to report in parallel the smoking-associated risks. © 2015 Society for Risk Analysis.
    Risk Analysis 02/2015; DOI:10.1111/risa.12320
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    ABSTRACT: To develop a quantitative exposure-response relationship between concentrations and durations of inhaled diesel engine exhaust (DEE) and increases in lung cancer risks, we examined the role of temporal factors in modifying the estimated effects of exposure to DEE on lung cancer mortality and characterized risk by mine type in the Diesel Exhaust in Miners Study (DEMS) cohort, which followed 12,315 workers through December 1997. We analyzed the data using parametric functions based on concepts of multistage carcinogenesis to directly estimate the hazard functions associated with estimated exposure to a surrogate marker of DEE, respirable elemental carbon (REC). The REC-associated risk of lung cancer mortality in DEMS is driven by increased risk in only one of four mine types (limestone), with statistically significant heterogeneity by mine type and no significant exposure-response relationship after removal of the limestone mine workers. Temporal factors, such as duration of exposure, play an important role in determining the risk of lung cancer mortality following exposure to REC, and the relative risk declines after exposure to REC stops. There is evidence of effect modification of risk by attained age. The modifying impact of temporal factors and effect modification by age should be addressed in any quantitative risk assessment (QRA) of DEE. Until there is a better understanding of why the risk appears to be confined to a single mine type, data from DEMS cannot reliably be used for QRA. © 2015 Society for Risk Analysis.
    Risk Analysis 02/2015; DOI:10.1111/risa.12315
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    ABSTRACT: Although risk and benefits of risky activities are positively correlated in real world, empirical results indicate that people perceive them as negatively correlated. The common explanation is that confounding benefits and losses stems from affect. In this article, we address an issue that has not been clearly established in studies on the affect heuristic: to what extent boundary conditions, such as judgments’ generality and expertise influence the presence of the inverse relation in judgments of hazards. These conditions were examined in four studies in which respondents evaluated general or specific benefits and risks of “affect-rich” and “affect-poor” hazards (ranging from investments to applications of stem cell research). In line with previous research, affect is defined as good or bad feelings integral to a stimulus. In contrast to previous research, affect is considered as related both to personal feelings and to social controversies associated with a hazard. Expertise is related to personal knowledge (laypersons vs. experts) as well as to objective knowledge (targets well vs. poorly known to science). The direct comparison of the input from personal and objective ignorance into the inverse relation has not been investigated previously. It was found that affect invoked by a hazard guides general but not specific judgments of its benefits and risks. Technical expertise helps to avoid simplified evaluations of consequences as long as they are well known to science. For new, poorly understood hazards (e.g. stem cell research), expertise does not protect from the perception of the inverse relation between benefits and risks.
    Risk Analysis 02/2015; fprthcomming. DOI:10.2139/ssrn.2409306
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    ABSTRACT: This article presents ongoing research that focuses on efficient allocation of defense resources to minimize the damage inflicted on a spatially distributed physical network such as a pipeline, water system, or power distribution system from an attack by an active adversary, recognizing the fundamental difference between preparing for natural disasters such as hurricanes, earthquakes, or even accidental systems failures and the problem of allocating resources to defend against an opponent who is aware of, and anticipating, the defender's efforts to mitigate the threat. Our approach is to utilize a combination of integer programming and agent-based modeling to allocate the defensive resources. We conceptualize the problem as a Stackelberg “leader follower” game where the defender first places his assets to defend key areas of the network, and the attacker then seeks to inflict the maximum damage possible within the constraints of resources and network structure. The criticality of arcs in the network is estimated by a deterministic network interdiction formulation, which then informs an evolutionary agent-based simulation. The evolutionary agent-based simulation is used to determine the allocation of resources for attackers and defenders that results in evolutionary stable strategies, where actions by either side alone cannot increase its share of victories. We demonstrate these techniques on an example network, comparing the evolutionary agent-based results to a more traditional, probabilistic risk analysis (PRA) approach. Our results show that the agent-based approach results in a greater percentage of defender victories than does the PRA-based approach.
    Risk Analysis 02/2015; DOI:10.1111/risa.12325
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    ABSTRACT: This article considers all 87 attacks worldwide against air and rail transport systems that killed at least two passengers over the 30-year period of 1982-2011. The data offer strong and statistically significant evidence that successful acts of terror have "gone to ground" in recent years: attacks against aviation were concentrated early in the three decades studied whereas those against rail were concentrated later. Recent data are used to make estimates of absolute and comparative risk for frequent flyers and subway/rail commuters. Point estimates in the "status quo" case imply that mortality risk from successful acts of terror was very low on both modes of transportation and that, whereas risk per trip is higher for air travelers than subway/rail commuters, the rail commuters experience greater risk per year than the frequent flyers. © 2015 Society for Risk Analysis.
    Risk Analysis 02/2015; DOI:10.1111/risa.12352
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    ABSTRACT: This article presents a new methodology to implement the concept of equity in regional earthquake risk mitigation programs using an optimization framework. It presents a framework that could be used by decisionmakers (government and authorities) to structure budget allocation strategy toward different seismic risk mitigation measures, i.e., structural retrofitting for different building structural types in different locations and planning horizons. A two-stage stochastic model is developed here to seek optimal mitigation measures based on minimizing mitigation expenditures, reconstruction expenditures, and especially large losses in highly seismically active countries. To consider fairness in the distribution of financial resources among different groups of people, the equity concept is incorporated using constraints in model formulation. These constraints limit inequity to the user-defined level to achieve the equity-efficiency tradeoff in the decision-making process. To present practical application of the proposed model, it is applied to a pilot area in Tehran, the capital city of Iran. Building stocks, structural vulnerability functions, and regional seismic hazard characteristics are incorporated to compile a probabilistic seismic risk model for the pilot area. Results illustrate the variation of mitigation expenditures by location and structural type for buildings. These expenditures are sensitive to the amount of available budget and equity consideration for the constant risk aversion. Most significantly, equity is more easily achieved if the budget is unlimited. Conversely, increasing equity where the budget is limited decreases the efficiency. The risk-return tradeoff, equity-reconstruction expenditures tradeoff, and variation of per-capita expected earthquake loss in different income classes are also presented.
    Risk Analysis 02/2015; DOI:10.1111/risa.12321
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    ABSTRACT: In this article, Bayesian networks are used to model semiconductor lifetime data obtained from a cyclic stress test system. The data of interest are a mixture of log-normal distributions, representing two dominant physical failure mechanisms. Moreover, the data can be censored due to limited test resources. For a better understanding of the complex lifetime behavior, interactions between test settings, geometric designs, material properties, and physical parameters of the semiconductor device are modeled by a Bayesian network. Statistical toolboxes in MATLAB(®) have been extended and applied to find the best structure of the Bayesian network and to perform parameter learning. Due to censored observations Markov chain Monte Carlo (MCMC) simulations are employed to determine the posterior distributions. For model selection the automatic relevance determination (ARD) algorithm and goodness-of-fit criteria such as marginal likelihoods, Bayes factors, posterior predictive density distributions, and sum of squared errors of prediction (SSEP) are applied and evaluated. The results indicate that the application of Bayesian networks to semiconductor reliability provides useful information about the interactions between the significant covariates and serves as a reliable alternative to currently applied methods. © 2015 Society for Risk Analysis.
    Risk Analysis 02/2015; DOI:10.1111/risa.12342
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    ABSTRACT: Despite improvements in forecasting extreme weather events, noncompliance with weather warnings among the public remains a problem. Although there are likely many reasons for noncompliance with weather warnings, one important factor might be people's past experiences with false alarms. The research presented here explores the role of false alarms in weather-related decision making. Over a series of trials, participants used an overnight low temperature forecast and advice from a decision aid to decide whether to apply salt treatment to a town's roads to prevent icy conditions or take the risk of withholding treatment, which resulted in a large penalty when freezing temperatures occurred. The decision aid gave treatment recommendations, some of which were false alarms, i.e., treatment was recommended but observed temperatures were above freezing. The rate at which the advice resulted in false alarms was manipulated between groups. Results suggest that very high and very low false alarm rates led to inferior decision making, but that lowering the false alarm rate slightly did not significantly affect compliance or decision quality. However, adding a probabilistic uncertainty estimate in the forecasts improved both compliance and decision quality. These findings carry implications about how weather warnings should be communicated to the public.
    Risk Analysis 01/2015; DOI:10.1111/risa.12336
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    ABSTRACT: A persistent problem in health risk analysis where it is known that a disease may occur as a consequence of multiple risk factors with interactions is allocating the total risk of the disease among the individual risk factors. This problem, referred to here as risk apportionment, arises in various venues, including: (i) public health management, (ii) government programs for compensating injured individuals, and (iii) litigation. Two methods have been described in the risk analysis and epidemiology literature for allocating total risk among individual risk factors. One method uses weights to allocate interactions among the individual risk factors. The other method is based on risk accounting axioms and finding an optimal and unique allocation that satisfies the axioms using a procedure borrowed from game theory. Where relative risk or attributable risk is the risk measure, we find that the game-theory-determined allocation is the same as the allocation where risk factor interactions are apportioned to individual risk factors using equal weights. Therefore, the apportionment problem becomes one of selecting a meaningful set of weights for allocating interactions among the individual risk factors. Equal weights and weights proportional to the risks of the individual risk factors are discussed.
    Risk Analysis 01/2015; DOI:10.1111/risa.12309