Risk Analysis

Publisher: Society for Risk Analysis, Wiley

Journal description

Current impact factor: 2.50

Impact Factor Rankings

2015 Impact Factor Available summer 2016
2014 Impact Factor 2.502
2013 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 2.54
Cited half-life 9.40
Immediacy index 0.27
Eigenfactor 0.01
Article influence 1.00
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
    • Non-Commercial
    • 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: Worldwide, more than 50 million cases of dengue fever are reported every year in at least 124 countries, and it is estimated that approximately 2.5 billion people are at risk for dengue infection. In Bangladesh, the recurrence of dengue has become a growing public health threat. Notably, knowledge and perceptions of dengue disease risk, particularly among the public, are not well understood. Recognizing the importance of assessing risk perception, we adopted a comparative approach to examine a generic methodology to assess diverse sets of beliefs related to dengue disease risk. Our study mapped existing knowledge structures regarding the risk associated with dengue virus, its vector (Aedes mosquitoes), water container use, and human activities in the city of Dhaka, Bangladesh. "Public mental models" were developed from interviews and focus group discussions with diverse community groups; "expert mental models" were formulated based on open-ended discussions with experts in the pertinent fields. A comparative assessment of the public's and experts' knowledge and perception of dengue disease risk has revealed significant gaps in the perception of: (a) disease risk indicators and measurements; (b) disease severity; (c) control of disease spread; and (d) the institutions responsible for intervention. This assessment further identifies misconceptions in public perception regarding: (a) causes of dengue disease; (b) dengue disease symptoms; (c) dengue disease severity; (d) dengue vector ecology; and (e) dengue disease transmission. Based on these results, recommendations are put forward for improving communication of dengue risk and practicing local community engagement and knowledge enhancement in Bangladesh.
    Risk Analysis 09/2015; DOI:10.1111/risa.12501
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    ABSTRACT: Understanding how people view flash flood risks can help improve risk communication, ultimately improving outcomes. This article analyzes data from 26 mental models interviews about flash floods with members of the public in Boulder, Colorado, to understand their perspectives on flash flood risks and mitigation. The analysis includes a comparison between public and professional perspectives by referencing a companion mental models study of Boulder-area professionals. A mental models approach can help to diagnose what people already know about flash flood risks and responses, as well as any critical gaps in their knowledge that might be addressed through improved risk communication. A few public interviewees mentioned most of the key concepts discussed by professionals as important for flash flood warning decision making. However, most interviewees exhibited some incomplete understandings and misconceptions about aspects of flash flood development and exposure, effects, or mitigation that may lead to ineffective warning decisions when a flash flood threatens. These include important misunderstandings about the rapid evolution of flash floods, the speed of water in flash floods, the locations and times that pose the greatest flash flood risk in Boulder, the value of situational awareness and environmental cues, and the most appropriate responses when a flash flood threatens. The findings point to recommendations for ways to improve risk communication, over the long term and when an event threatens, to help people quickly recognize and understand threats, obtain needed information, and make informed decisions in complex, rapidly evolving extreme weather events such as flash floods.
    Risk Analysis 09/2015; DOI:10.1111/risa.12480
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    ABSTRACT: This study investigates how people change their risk perception, trust, and behavior as a consequence of being informed about the occurrence of micropollutants in drinking water. Micropollutants are substances present in extremely low concentrations that might be dangerous in higher concentrations. Data were gathered in the city of Zurich, Switzerland in 2013 using a questionnaire in which the information on micropollutants was presented differently to 12 experimental groups. Data of the key constructs were gathered before and after this information, so that causal effects could be quantified by regression analyses. Affective reactions to the information turned out to be the critical mediator of changes in risk perception (operationalized as the perceived change of quality due to pollution), which is an important determinant of changes in behavior and trust. Also, direct effects of affective reactions on behavior and trust were observed. Trust before appraising risks reduces negative affective reactions; however, it also reduces perceived quality (i.e., increases risk perception) and trust after risks are appraised. The different forms of information mainly influenced the participants' affective reactions, but they also influenced perceived quality. The presentation with the least negative effects was a comparison of the intake of the substance by water with intake by food. The experimental design with repeated measurement that considers trust as a determinant and consequence of risk perception uncovered positive and negative effects of trust before appraising risks on changes of risk perception and trust due to appraising risks.
    Risk Analysis 09/2015; DOI:10.1111/risa.12485
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    ABSTRACT: Polycyclic aromatic hydrocarbons (PAHs) have been labeled contaminants of concern due to their carcinogenic potential, insufficient toxicological data, environmental ubiquity, and inconsistencies in the composition of environmental mixtures. The Environmental Protection Agency is reevaluating current methods for assessing the toxicity of PAHs, including the assumption of toxic additivity in mixtures. This study was aimed at testing mixture interactions through in vitro cell culture experimentation, and modeling the toxicity using quantitative structure-activity relationships (QSAR). Clone-9 rat liver cells were used to analyze cellular proliferation, viability, and genotoxicity of 15 PAHs in single doses and binary mixtures. Tests revealed that many mixtures have nonadditive toxicity, but display varying mixture effects depending on the mixture composition. Many mixtures displayed antagonism, similar to other published studies. QSARs were then developed using the genetic function approximation algorithm to predict toxic activity both in single PAH congeners and in binary mixtures. Effective concentrations inhibiting 50% of the cell populations were modeled, with R(2) = 0.90, 0.99, and 0.84, respectively. The QSAR mixture algorithms were then adjusted to account for the observed mixture interactions as well as the mixture composition (ratios) to assess the feasibility of QSARs for mixtures. Based on these results, toxic addition is improbable and therefore environmental PAH mixtures are likely to see nonadditive responses when complex interactions occur between components. Furthermore, QSAR may be a useful tool to help bridge these data gaps surrounding the assessment of human health risks that are associated with PAH exposures.
    Risk Analysis 09/2015; DOI:10.1111/risa.12475
  • [Show abstract] [Hide abstract]
    ABSTRACT: This article presents research aimed at developing and testing an online, multistakeholder decision-aiding framework for informing multiattribute risk management choices associated with energy development and climate change. The framework was designed to provide necessary background information and facilitate internally consistent choices, or choices that are in line with users’ prioritized objectives. In order to test different components of the decision-aiding framework, a six-part, 2 × 2 × 2 factorial experiment was conducted, yielding eight treatment scenarios. The three factors included: (1) whether or not users could construct their own alternatives; (2) the level of detail regarding the composition of alternatives users would evaluate; and (3) the way in which a final choice between users’ own constructed (or highest-ranked) portfolio and an internally consistent portfolio was presented. Participants’ self-reports revealed the framework was easy to use and providing an opportunity to develop one's own risk-management alternatives (Factor 1) led to the highest knowledge gains. Empirical measures showed the internal consistency of users’ decisions across all treatments to be lower than expected and confirmed that providing information about alternatives’ composition (Factor 2) resulted in the least internally consistent choices. At the same time, those users who did not develop their own alternatives and were not shown detailed information about the composition of alternatives believed their choices to be the most internally consistent. These results raise concerns about how the amount of information provided and the ability to construct alternatives may inversely affect users’ real and perceived internal consistency.
    Risk Analysis 09/2015; DOI:10.1111/risa.12481
  • [Show abstract] [Hide abstract]
    ABSTRACT: This article constructs a framework to help a decisionmaker allocate resources to increase his or her organization's resilience to a system disruption, where resilience is measured as a function of the average loss per unit time and the time needed to recover full functionality. Enhancing resilience prior to a disruption involves allocating resources from a fixed budget to reduce the value of one or both of these characteristics. We first look at characterizing the optimal resource allocations associated with several standard allocation functions. Because the resources are being allocated before the disruption, however, the initial loss and recovery time may not be known with certainty. We thus also apply the optimal resource allocation model for resilience to three models of uncertain disruptions: (1) independent probabilities, (2) dependent probabilities, and (3) unknown probabilities. The optimization model is applied to an example of increasing the resilience of an electric power network following Superstorm Sandy. © 2015 Society for Risk Analysis.
    Risk Analysis 09/2015; DOI:10.1111/risa.12479
  • [Show abstract] [Hide abstract]
    ABSTRACT: Reducing the risk of introduction to North America of the invasive Asian gypsy moth (Lymantria dispar asiatica Vnukovskij and L. d. japonica [Motschulsky]) on international maritime vessels involves two tactics: (1) vessels that wish to arrive in Canada or the United States and have visited any Asian port that is subject to regulation during designated times must obtain a predeparture inspection certificate from an approved entity; and (2) vessels with a certificate may be subjected to an additional inspection upon arrival. A decision support tool is described here with which the allocation of inspection resources at North American ports can be partitioned among multiple vessels according to estimates of the potential onboard Asian gypsy moth population and estimates of the onboard larval emergence pattern. The decision support tool assumes that port inspection is uniformly imperfect at the Asian ports and that each visit to a regulated port has potential for the vessel to be contaminated with gypsy moth egg masses. The decision support tool uses a multigenerational phenology model to estimate the potential onboard population of egg masses by calculating the temporal intersection between the dates of port visits to regulated ports and the simulated oviposition pattern in each port. The phenological development of the onboard population is simulated each day of the vessel log until the vessel arrives at the port being protected from introduction. Multiple independent simulations are used to create a probability distribution of the size and timing of larval emergence. © 2015 Society for Risk Analysis.
    Risk Analysis 08/2015; DOI:10.1111/risa.12474
  • [Show abstract] [Hide abstract]
    ABSTRACT: Wildfires present a complex applied risk management environment, but relatively little attention has been paid to behavioral and cognitive responses to risk among public agency wildfire managers. This study investigates responses to risk, including probability weighting and risk aversion, in a wildfire management context using a survey-based experiment administered to federal wildfire managers. Respondents were presented with a multiattribute lottery-choice experiment where each lottery is defined by three outcome attributes: expenditures for fire suppression, damage to private property, and exposure of firefighters to the risk of aviation-related fatalities. Respondents choose one of two strategies, each of which includes "good" (low cost/low damage) and "bad" (high cost/high damage) outcomes that occur with varying probabilities. The choice task also incorporates an information framing experiment to test whether information about fatality risk to firefighters alters managers' responses to risk. Results suggest that managers exhibit risk aversion and nonlinear probability weighting, which can result in choices that do not minimize expected expenditures, property damage, or firefighter exposure. Information framing tends to result in choices that reduce the risk of aviation fatalities, but exacerbates nonlinear probability weighting. © 2015 Society for Risk Analysis.
    Risk Analysis 08/2015; DOI:10.1111/risa.12457
  • [Show abstract] [Hide abstract]
    ABSTRACT: Ongoing challenges to understanding how hazard exposure and disaster experiences influence perceived risk lead us to ask: Is seeing believing? We approach risk perception by attending to two components of overall risk perception: perceived probability of an event occurring and perceived consequences if an event occurs. Using a two-period longitudinal data set collected from a survey of homeowners living in a fire-prone area of Colorado, we find that study participants' initial high levels of perceived probability and consequences of a wildfire did not change substantially after extreme wildfire events in the intervening years. More specifically, perceived probability of a wildfire changed very little, whereas the perceived consequences of a wildfire went up a bit. In addition, models of risk perceptions show that the two components of overall risk perception are correlated with somewhat different factors, and experience is not found to be one of the strongest correlates with perceived risk. These results reflect the importance of distinguishing the components of overall risk and modeling them separately to facilitate additional insights into the complexities of risk perceptions, factors related to perceived risk, and change in risk perceptions over time. © 2015 Society for Risk Analysis.
    Risk Analysis 08/2015; DOI:10.1111/risa.12465
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    ABSTRACT: Research indicates that uncertainty in science news stories affects public assessment of risk and uncertainty. However, the form in which uncertainty is presented may also affect people's risk and uncertainty assessments. For example, a news story that features an expert discussing both what is known and what is unknown about a topic may convey a different form of scientific uncertainty than a story that features two experts who hold conflicting opinions about the status of scientific knowledge of the topic, even when both stories contain the same information about knowledge and its boundaries. This study focuses on audience uncertainty and risk perceptions regarding the emerging science of nanotechnology by manipulating whether uncertainty in a news story about potential risks is attributed to expert sources in the form of caveats (individual uncertainty) or conflicting viewpoints (collective uncertainty). Results suggest that the type of uncertainty portrayed does not impact audience feelings of uncertainty or risk perceptions directly. Rather, the presentation of the story influences risk perceptions only among those who are highly deferent to scientific authority. Implications for risk communication theory and practice are discussed. © 2015 Society for Risk Analysis.
    Risk Analysis 08/2015; DOI:10.1111/risa.12462
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    ABSTRACT: Our reconstructed historical work scenarios incorporating a vintage 1950s locomotive can assist in better understanding the historical asbestos exposures associated with past maintenance and repairs and fill a literature data gap. Air sampling data collected during the exposure scenarios and analyzed by NIOSH 7400 (PCM) and 7402 (PCME) methodologies show personal breathing zone asbestiform fiber exposures were below the current OSHA exposure limits for the eight-hour TWA permissible exposure limit (PEL) of 0.1 f/cc (range <0.007-0.064 PCME f/cc) and the 30-minute short-term excursion limit (EL) of 1.0 f/cc (range <0.045-0.32 PCME f/cc) and orders of magnitude below historic OSHA PEL and ACGIH TLVs. Bayesian decision analysis (BDA) results demonstrate that the 95th percentile point estimate falls into an AIHA exposure category 3 or 4 as compared to the current PEL and category 1 when compared to the historic PEL. BDA results demonstrate that bystander exposures would be classified as category 0. Our findings were also significantly below the published calcium magnesium insulations exposure range of 2.5 to 7.5 f/cc reported for historic work activities of pipefitters, mechanics, and boilermakers. Diesel-electric locomotive pipe systems were typically insulated with a woven tape lagging that may have been chrysotile asbestos and handled, removed, and reinstalled during repair and maintenance activities. We reconstructed historical work scenarios containing asbestos woven tape pipe lagging that have not been characterized in the published literature. The historical work scenarios were conducted by a retired railroad pipefitter with 37 years of experience working with materials and locomotives. © 2015 The Authors. Risk Analysis published by Wiley Periodicals, Inc. on behalf of Society for Risk Analysis.
    Risk Analysis 08/2015; DOI:10.1111/risa.12458
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    ABSTRACT: In this article, we develop statistical models to predict the number and geographic distribution of fires caused by earthquake ground motion and tsunami inundation in Japan. Using new, uniquely large, and consistent data sets from the 2011 Tōhoku earthquake and tsunami, we fitted three types of models-generalized linear models (GLMs), generalized additive models (GAMs), and boosted regression trees (BRTs). This is the first time the latter two have been used in this application. A simple conceptual framework guided identification of candidate covariates. Models were then compared based on their out-of-sample predictive power, goodness of fit to the data, ease of implementation, and relative importance of the framework concepts. For the ground motion data set, we recommend a Poisson GAM; for the tsunami data set, a negative binomial (NB) GLM or NB GAM. The best models generate out-of-sample predictions of the total number of ignitions in the region within one or two. Prefecture-level prediction errors average approximately three. All models demonstrate predictive power far superior to four from the literature that were also tested. A nonlinear relationship is apparent between ignitions and ground motion, so for GLMs, which assume a linear response-covariate relationship, instrumental intensity was the preferred ground motion covariate because it captures part of that nonlinearity. Measures of commercial exposure were preferred over measures of residential exposure for both ground motion and tsunami ignition models. This may vary in other regions, but nevertheless highlights the value of testing alternative measures for each concept. Models with the best predictive power included two or three covariates. © 2015 Society for Risk Analysis.
    Risk Analysis 08/2015; DOI:10.1111/risa.12455
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    ABSTRACT: To improve U.S. Environmental Protection Agency (EPA) dose-response (DR) assessments for noncarcinogens and for nonlinear mode of action (MOA) carcinogens, the 2009 NRC Science and Decisions Panel recommended that the adjustment-factor approach traditionally applied to these endpoints should be replaced by a new default assumption that both endpoints have linear-no-threshold (LNT) population-wide DR relationships. The panel claimed this new approach is warranted because population DR is LNT when any new dose adds to a background dose that explains background levels of risk, and/or when there is substantial interindividual heterogeneity in susceptibility in the exposed human population. Mathematically, however, the first claim is either false or effectively meaningless and the second claim is false. Any dose-and population-response relationship that is statistically consistent with an LNT relationship may instead be an additive mixture of just two quasi-threshold DR relationships, which jointly exhibit low-dose S-shaped, quasi-threshold nonlinearity just below the lower end of the observed "linear" dose range. In this case, LNT extrapolation would necessarily overestimate increased risk by increasingly large relative magnitudes at diminishing values of above-background dose. The fact that chemically-induced apoptotic cell death occurs by unambiguously nonlinear, quasi-threshold DR mechanisms is apparent from recent data concerning this quintessential toxicity endpoint. The 2009 NRC Science and Decisions Panel claims and recommendations that default LNT assumptions be applied to DR assessment for noncarcinogens and nonlinear MOA carcinogens are therefore not justified either mathematically or biologically. © 2015 Society for Risk Analysis.
    Risk Analysis 08/2015; DOI:10.1111/risa.12460
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    ABSTRACT: Disruptive events such as natural disasters, loss or reduction of resources, work stoppages, and emergent conditions have potential to propagate economic losses across trade networks. In particular, disruptions to the operation of container port activity can be detrimental for international trade and commerce. Risk assessment should anticipate the impact of port operation disruptions with consideration of how priorities change due to uncertain scenarios and guide investments that are effective and feasible for implementation. Priorities for protective measures and continuity of operations planning must consider the economic impact of such disruptions across a variety of scenarios. This article introduces new performance metrics to characterize resiliency in interdependency modeling and also integrates scenario-based methods to measure economic sensitivity to sudden-onset disruptions. The methods will be demonstrated on a U.S. port responsible for handling $36.1 billion of cargo annually. The methods will be useful to port management, private industry supply chain planning, and transportation infrastructure management. © 2015 Society for Conservation Biology.
    Risk Analysis 08/2015; DOI:10.1111/risa.12473