Risk Analysis

Publisher: Society for Risk Analysis, Wiley

Journal description

Current impact factor: 1.97

Impact Factor Rankings

2015 Impact Factor Available summer 2015
2013 / 2014 Impact Factor 1.974
2012 Impact Factor 2.278
2011 Impact Factor 2.366
2010 Impact Factor 2.096
2009 Impact Factor 1.953
2008 Impact Factor 1.831
2007 Impact Factor 1.784
2006 Impact Factor 1.938
2005 Impact Factor 1.51
2004 Impact Factor 1.321
2003 Impact Factor 1.064

Impact factor over time

Impact factor

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


  • Pre-print
    • Author can archive a pre-print version
  • Post-print
    • Author cannot archive a post-print version
  • Restrictions
    • 2 years embargo
  • Conditions
    • Some journals have separate policies, please check with each journal directly
    • 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
    • Author's pre-print must acknowledge acceptance for publication
    • 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: Public support for nuclear power generation has decreased in Japan since the Fukushima Daiichi nuclear accident in March 2011. This study examines how the factors influencing public acceptance of nuclear power changed after this event. The influence factors examined are perceived benefit, perceived risk, trust in the managing bodies, and pro-environmental orientation (i.e., new ecological paradigm). This study is based on cross-sectional data collected from two online nationwide surveys: one conducted in November 2009, before the nuclear accident, and the other in October 2011, after the accident. This study's target respondents were residents of Aomori, Miyagi, and Fukushima prefectures in the Tohoku region of Japan, as these areas were the epicenters of the Great East Japan Earthquake and the locations of nuclear power stations. After the accident, trust in the managing bodies was found to have a stronger influence on perceived risk, and pro-environmental orientation was found to have a stronger influence on trust in the managing bodies; however, perceived benefit had a weaker positive influence on public acceptance. We also discuss the theoretical and practical implications of these findings. © 2015 Society for Risk Analysis.
    Risk Analysis 07/2015; DOI:10.1111/risa.12447
  • [Show abstract] [Hide abstract]
    ABSTRACT: The Department of Homeland Security (DHS) characterized and prioritized the physical cross-border threats and hazards to the nation stemming from terrorism, market-driven illicit flows of people and goods (illegal immigration, narcotics, funds, counterfeits, and weaponry), and other nonmarket concerns (movement of diseases, pests, and invasive species). These threats and hazards pose a wide diversity of consequences with very different combinations of magnitudes and likelihoods, making it very challenging to prioritize them. This article presents the approach that was used at DHS to arrive at a consensus regarding the threats and hazards that stand out from the rest based on the overall risk they pose. Due to time constraints for the decision analysis, it was not feasible to apply multiattribute methodologies like multiattribute utility theory or the analytic hierarchy process. Using a holistic approach was considered, such as the deliberative method for ranking risks first published in this journal. However, an ordinal ranking alone does not indicate relative or absolute magnitude differences among the risks. Therefore, the use of the deliberative method for ranking risks is not sufficient for deciding whether there is a material difference between the top-ranked and bottom-ranked risks, let alone deciding what the stand-out risks are. To address this limitation of ordinal rankings, the deliberative method for ranking risks was augmented by adding an additional step to transform the ordinal ranking into a ratio scale ranking. This additional step enabled the selection of stand-out risks to help prioritize further analysis. © 2015 Society for Risk Analysis.
    Risk Analysis 07/2015; DOI:10.1111/risa.12456
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    ABSTRACT: Tunneling excavation is bound to produce significant disturbances to surrounding environments, and the tunnel-induced damage to adjacent underground buried pipelines is of considerable importance for geotechnical practice. A fuzzy Bayesian networks (FBNs) based approach for safety risk analysis is developed in this article with detailed step-by-step procedures, consisting of risk mechanism analysis, the FBN model establishment, fuzzification, FBN-based inference, defuzzification, and decision making. In accordance with the failure mechanism analysis, a tunnel-induced pipeline damage model is proposed to reveal the cause-effect relationships between the pipeline damage and its influential variables. In terms of the fuzzification process, an expert confidence indicator is proposed to reveal the reliability of the data when determining the fuzzy probability of occurrence of basic events, with both the judgment ability level and the subjectivity reliability level taken into account. By means of the fuzzy Bayesian inference, the approach proposed in this article is capable of calculating the probability distribution of potential safety risks and identifying the most likely potential causes of accidents under both prior knowledge and given evidence circumstances. A case concerning the safety analysis of underground buried pipelines adjacent to the construction of the Wuhan Yangtze River Tunnel is presented. The results demonstrate the feasibility of the proposed FBN approach and its application potential. The proposed approach can be used as a decision tool to provide support for safety assurance and management in tunnel construction, and thus increase the likelihood of a successful project in a complex project environment. © 2015 Society for Risk Analysis.
    Risk Analysis 07/2015; DOI:10.1111/risa.12448
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    ABSTRACT: Following the 2013 Chelyabinsk event, the risks posed by asteroids attracted renewed interest, from both the scientific and policy-making communities. It reminded the world that impacts from near-Earth objects (NEOs), while rare, have the potential to cause great damage to cities and populations. Point estimates of the risk (such as mean numbers of casualties) have been proposed, but because of the low-probability, high-consequence nature of asteroid impacts, these averages provide limited actionable information. While more work is needed to further refine its input distributions (e.g., NEO diameters), the probabilistic model presented in this article allows a more complete evaluation of the risk of NEO impacts because the results are distributions that cover the range of potential casualties. This model is based on a modularized simulation that uses probabilistic inputs to estimate probabilistic risk metrics, including those of rare asteroid impacts. Illustrative results of this analysis are presented for a period of 100 years. As part of this demonstration, we assess the effectiveness of civil defense measures in mitigating the risk of human casualties. We find that they are likely to be beneficial but not a panacea. We also compute the probability-but not the consequences-of an impact with global effects ("cataclysm"). We conclude that there is a continued need for NEO observation, and for analyses of the feasibility and risk-reduction effectiveness of space missions designed to deflect or destroy asteroids that threaten the Earth. © 2015 Society for Risk Analysis.
    Risk Analysis 07/2015; DOI:10.1111/risa.12453
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    ABSTRACT: This article gives a measure of life jacket (LJ) effectiveness in U.S. recreational boating. Using the U.S. Coast Guard's Boating Accident Report Database from 2008 to 2011, we find that LJ wear is one of the most important determinants influencing the number of recreational boating fatalities, together with the number of vessels involved, and the type and engine of the vessel(s). We estimate a decrease in the number of deceased per vessel of about 80% when the operator wears their LJs compared to when they do not. The odds of dying are 86% higher than average if the accident involves a canoe or kayak, but 80% lower than average when more than one vessel is involved in the accident and 34% lower than average when the operator involved in the accident has more than 100 hours of boating experience. Interestingly, we find that LJ effectiveness decreases significantly as the length of the boat increases and decreases slightly as water temperature increases. However, it increases slightly as the operator's age increases. We find that between 2008 and 2011, an LJ regulation that requires all operators to wear their LJs-representing a 20% increase in wear rate-would have saved 1,721 (out of 3,047) boaters or 1,234 out of 2,185 drowning victims. The same policy restricted to boats 16-30 feet in length would have saved approximately 778 victims. Finally, we find that such a policy would reduce the percentage of drowning victims compared to other causes of death. © 2015 Society for Risk Analysis.
    Risk Analysis 07/2015; DOI:10.1111/risa.12449
  • [Show abstract] [Hide abstract]
    ABSTRACT: This article addresses the problem of validating models in the absence of observed events, in the area of weapons of mass destruction terrorism risk assessment. We address that problem with a broadened definition of "validation," based on stepping "up" a level to considering the reason why decisionmakers seek validation, and from that basis redefine validation as testing how well the model can advise decisionmakers in terrorism risk management decisions. We develop that into two conditions: validation must be based on cues available in the observable world; and it must focus on what can be done to affect that observable world, i.e., risk management. That leads to two foci: (1) the real-world risk generating process, and (2) best use of available data. Based on our experience with nine WMD terrorism risk assessment models, we then describe three best use of available data pitfalls: SME confidence bias, lack of SME cross-referencing, and problematic initiation rates. Those two foci and three pitfalls provide a basis from which we define validation in this context in terms of four tests-Does the model: … capture initiation? … capture the sequence of events by which attack scenarios unfold? … consider unanticipated scenarios? … consider alternative causal chains? Finally, we corroborate our approach against three validation tests from the DOD literature: Is the model a correct representation of the process to be simulated? To what degree are the model results comparable to the real world? Over what range of inputs are the model results useful? © 2015 Society for Risk Analysis.
    Risk Analysis 07/2015; DOI:10.1111/risa.12442
  • [Show abstract] [Hide abstract]
    ABSTRACT: Job exposure matrices (JEMs) are used to measure exposures based on information about particular jobs and tasks. JEMs are especially useful when individual exposure data cannot be obtained. Nonetheless, there may be other workplace exposures associated with the study disease that are not measured in available JEMs. When these exposures are also associated with the exposures measured in the JEM, biases due to uncontrolled confounding will be introduced. Furthermore, individual exposures differ from JEM measurements due to differences in job conditions and worker practices. Uncertainty may also be present at the assessor level since exposure information for each job may be imprecise or incomplete. Assigning individuals a fixed exposure determined by the JEM ignores these uncertainty sources. We examine the uncertainty displayed by bias analyses in a study of occupational electric shocks, occupational magnetic fields, and amyotrophic lateral sclerosis. © 2015 Society for Risk Analysis.
    Risk Analysis 07/2015; DOI:10.1111/risa.12438
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    ABSTRACT: Product-harm crises usually lead to product recalls, which may cause consumers concern about the product quality and safety. This study systematically examines customers' immediate responses to the Volkswagen product recall crisis in China. Particular attention was given to customers' responses to the risk information influencing their behavioral intentions. By combining the protective action decision model and the heuristic-systematic model, we constructed a hypothetical model to explore this issue. A questionnaire survey was conducted to collect data involving 467 participants drawn from the customers of Volkswagen. We used structural equation modeling to explore the model. The results show that customers' product knowledge plays an important role in their responses to the crisis. Having more knowledge would make them perceive a lower risk, but they might need even more information, making them more likely to seek and process information, and subsequently increasing their positive behavioral intentions toward the firm (that is pro-firm behavioral intentions). Risk perception increased customers' information needs, information seeking, and information processing but decreased their pro-firm behavioral intentions. In addition to promoting information seeking, information needed to also facilitate customers' systematic processing and thus increase their behavioral intentions to take corrective action. Customers' behavioral intentions were also spurred by systematic processing, but failed to be predicted by information seeking. In summary, theoretical and practical implications and suggestions for further research are also discussed. © 2015 Society for Risk Analysis.
    Risk Analysis 07/2015; DOI:10.1111/risa.12446
  • [Show abstract] [Hide abstract]
    ABSTRACT: The aim of this study was to develop a modified quantitative microbial risk assessment (QMRA) framework that could be applied as a decision support tool to choose between alternative drinking water interventions in the developing context. The impact of different household water treatment (HWT) interventions on the overall incidence of diarrheal disease and disability adjusted life years (DALYs) was estimated, without relying on source water pathogen concentration as the starting point for the analysis. A framework was developed and a software tool constructed and then implemented for an illustrative case study for Nepal based on published scientific data. Coagulation combined with free chlorine disinfection provided the greatest estimated health gains in the short term; however, when long-term compliance was incorporated into the calculations, the preferred intervention was porous ceramic filtration. The model demonstrates how the QMRA framework can be used to integrate evidence from different studies to inform management decisions, and in particular to prioritize the next best intervention with respect to estimated reduction in diarrheal incidence. This study only considered HWT interventions; it is recognized that a systematic consideration of sanitation, recreation, and drinking water pathways is important for effective management of waterborne transmission of pathogens, and the approach could be expanded to consider the broader water-related context. © 2015 Society for Risk Analysis.
    Risk Analysis 07/2015; DOI:10.1111/risa.12452
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    ABSTRACT: Adversarial risk analysis has been introduced as a framework to deal with risks derived from intentional actions of adversaries. The analysis supports one of the decisionmakers, who must forecast the actions of the other agents. Typically, this forecast must take account of random consequences resulting from the set of selected actions. The solution requires one to model the behavior of the opponents, which entails strategic thinking. The supported agent may face different kinds of opponents, who may use different rationality paradigms, for example, the opponent may behave randomly, or seek a Nash equilibrium, or perform level-k thinking, or use mirroring, or employ prospect theory, among many other possibilities. We describe the appropriate analysis for these situations, and also show how to model the uncertainty about the rationality paradigm used by the opponent through a Bayesian model averaging approach, enabling a fully decision-theoretic solution. We also show how as we observe an opponent's decision behavior, this approach allows learning about the validity of each of the rationality models used to predict his decision by computing the models' (posterior) probabilities, which can be understood as a measure of their validity. We focus on simultaneous decision making by two agents. © 2015 Society for Risk Analysis.
    Risk Analysis 07/2015; DOI:10.1111/risa.12439
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    ABSTRACT: Measles outbreaks in the United States continue to occur in subpopulations with sufficient numbers of undervaccinated individuals, with a 2014 outbreak in Amish communities in Ohio pushing the annual cases to the highest national number reported in the last 20 years. We adapted an individual-based model developed to explore potential poliovirus transmission in the North American Amish to characterize a 1988 measles outbreak in the Pennsylvania Amish and the 2014 outbreak in the Ohio Amish. We explored the impact of the 2014 outbreak response compared to no or partial response. Measles can spread very rapidly in an underimmunized subpopulation like the North American Amish, with the potential for national spread within a year or so in the absence of outbreak response. Vaccination efforts significantly reduced the transmission of measles and the expected number of cases. Until global eradication, measles importations will continue to pose a threat to clusters of underimmunized individuals in the United States. Aggressive outbreak response efforts in Ohio probably prevented widespread transmission of measles within the entire North American Amish. © 2015 Society for Risk Analysis.
    Risk Analysis 06/2015; DOI:10.1111/risa.12440
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    ABSTRACT: To estimate the effects of a policy change, analysts must often rely on available data as time and resource constraints limit their ability to commission new primary research. Research synthesis methods-including systematic review, meta-analysis, and expert elicitation-play an important role in ensuring that this evidence is appropriately weighed and considered. We present the conclusions of a multidisciplinary Harvard Center for Risk Analysis project that evaluated and applied these methods, and introduce the resulting series of articles. The first step in any analysis is to clearly define the problem to be addressed; the second is a systematic review of the literature. Whether additional analysis is needed depends on the quality and relevance of the available data to the policy question, and the likely effect of uncertainty on the policy decision. Meta-analysis promotes understanding the variation between studies and may be used to combine the estimates to develop values for application in policy analysis. Formal, structured expert elicitation promotes careful consideration of the evidence when data are limited or inconsistent, and aids in extrapolating to the policy context. Regardless of the methods used, clear communication of the approach, assumptions, and uncertainty is essential. © 2015 Society for Risk Analysis.
    Risk Analysis 06/2015; 35(6). DOI:10.1111/risa.12437
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    ABSTRACT: This article focuses on the fluid nature of risk problems and the challenges it presents to establishing acceptability in risk governance. It introduces an actor-network theory (ANT) perspective as a way to deal with the mutable nature of risk controversies and the configuration of stakeholders. To translate this into a practicable framework, the article proposes a hybrid risk governance framework that combines ANT with integrative risk governance, deliberative democracy, and responsive regulation. This addresses a number of the limitations in existing risk governance models, including: (1) the lack of more substantive public participation throughout the lifecycle of a project; (2) hijacking of deliberative forums by particular groups; and (3) the treatment of risk problems and their associated stakeholders as immutable entities. The framework constitutes a five-stage process of co-selection, co-design, co-planning, and co-regulation to facilitate the co-production of collective interests and knowledge, build capacities, and strengthen accountability in the process. The aims of this article are twofold: conceptually, it introduces a framework of risk governance that accounts for the mutable nature of risk problems and configuration of stakeholders. In practice, this article offers risk managers and practitioners of risk governance a set of procedures with which to operationalize this conceptual approach to risk and stakeholder engagement. © 2015 Society for Risk Analysis.
    Risk Analysis 06/2015; DOI:10.1111/risa.12429
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    ABSTRACT: The World Health Organization (WHO) African Region set a goal for regional measles elimination by 2020; however, regional measles incidence was 125/1,000,000 in 2012. To support elimination efforts, the WHO and U.S. Centers for Disease Control and Prevention developed a tool to assess performance of measles control activities and identify high-risk areas at the subnational level. The tool uses routinely collected data to generate district-level risk scores across four categories: population immunity, surveillance quality, program performance, and threat assessment. To pilot test this tool, we used retrospective data from 2006 to 2008 to identify high-risk districts in Senegal; results were compared with measles case-based surveillance data from 2009 when Senegal experienced a large measles outbreak. Seventeen (25%) of 69 districts in Senegal were classified as high or very high risk. The tool highlighted how each of the four categories contributed to the total risk scores for high or very high risk districts. Measles case-based surveillance reported 986 cases during 2009, including 368 laboratory-confirmed, 540 epidemiologically linked, and 78 clinically compatible cases. The seven districts with the highest numbers of laboratory-confirmed or epidemiologically linked cases were within the capital region of Dakar. All except one of these seven districts were estimated to be high or very high risk, suggesting that districts identified as high risk by the tool have the potential for measles outbreaks. Prospective use of this tool is recommended to help immunization and surveillance program managers identify high-risk areas in which to strengthen specific programmatic weaknesses and mitigate risk for potential measles outbreaks. © 2015 Society for Risk Analysis.
    Risk Analysis 06/2015; DOI:10.1111/risa.12431
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    ABSTRACT: Current risk assessment guidance calls for an individual chemical-by-chemical approach that fails to capture potential interactive effects of exposure to environmental mixtures and genetic variability. We conducted a review of the literature on relationships between prenatal and early life exposure to mixtures of lead (Pb), arsenic (As), cadmium (Cd), and manganese (Mn) with neurodevelopmental outcomes. We then used an adverse outcome pathway (AOP) framework to integrate lines of evidence from multiple disciplines based on evolving guidance developed by the Organization for Economic Cooperation and Development (OECD). Toxicological evidence suggests a greater than additive effect of combined exposures to As-Pb-Cd and to Mn with any other metal, and several epidemiologic studies also suggest synergistic effects from binary combinations of Pb-As, Pb-Cd, and Pb-Mn. The exposure levels reported in these epidemiologic studies largely fall at the high-end (e.g., 95th percentile) of biomonitoring data from the National Health and Nutrition Examination Survey (NHANES), suggesting a small but significant potential for high-end exposures. This review integrates multiple data sources using an AOP framework and provides an initial application of the OECD guidance in the context of potential neurodevelopmental toxicity of several metals, recognizing the evolving nature of regulatory interpretation and acceptance. © 2015 Society for Risk Analysis.
    Risk Analysis 06/2015; 35(6). DOI:10.1111/risa.12425
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    ABSTRACT: We present a risk analysis undertaken to mitigate problems in relation to the unintended deployment of slides under normal operations within a commercial airline. This type of incident entails relevant costs for the airline industry. After assessing the likelihood and severity of its consequences, we conclude that such risks need to be managed. We then evaluate the effectiveness of various countermeasures, describing and justifying the chosen ones. We also discuss several issues faced when implementing and communicating the proposed measures, thus fully illustrating the risk analysis process. © 2015 Society for Risk Analysis.
    Risk Analysis 06/2015; DOI:10.1111/risa.12428