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: Losses due to natural hazard events can be extraordinarily high and difficult to cope with. Therefore, there is considerable interest to estimate the potential impact of current and future extreme events at all scales in as much detail as possible. As hazards typically spread over wider areas, risk assessment must take into account interrelations between regions. Neglecting such interdependencies can lead to a severe underestimation of potential losses, especially for extreme events. This underestimation of extreme risk can lead to the failure of riskmanagement strategies when they are most needed, namely, in times of unprecedented events. In this article, we suggest a methodology to incorporate such interdependencies in risk via the use of copulas. We demonstrate that by coupling losses, dependencies can be incorporated in risk analysis, avoiding the underestimation of risk. Based on maximum discharge data of river basins and stream networks, we present and discuss different ways to couple loss distributions of basins while explicitly incorporating tail dependencies. We distinguish between coupling methods that require river structure data for the analysis and those that do not. For the later approach we propose a minimax algorithm to choose coupled basin pairs so that the underestimation of risk is avoided and the use of river structure data is not needed. The proposed methodology is especially useful for large-scale analysis and we motivate and apply our method using the case of Romania. The approach can be easily extended to other countries and natural hazards.
    Risk Analysis 05/2015; DOI:10.1111/risa.12382
  • [Show abstract] [Hide abstract]
    ABSTRACT: Many health-related decisions require choosing between two options, each with risks and benefits. When presented with such tradeoffs, people often make choices that fail to align with scientific evidence or with their own values. This study tested whether risk communication and values clarification methods could help parents and guardians make evidence-based, values-congruent decisions about children's influenza vaccinations. In 2013-2014 we conducted an online 2×2 factorial experiment in which a diverse sample of U.S. parents and guardians (n = 407) were randomly assigned to view either standard information about influenza vaccines or risk communication using absolute and incremental risk formats. Participants were then either presented or not presented with an interactive values clarification interface with constrained sliders and dynamic visual feedback. Participants randomized to the risk communication condition combined with the values clarification interface were more likely to indicate intentions to vaccinate (β = 2.10, t(399) = 2.63, p < 0.01). The effect was particularly notable among participants who had previously demonstrated less interest in having their children vaccinated against influenza (β = -2.14, t(399) = -2.06, p < 0.05). When assessing vaccination status reported by participants who agreed to participate in a follow-up study six months later (n = 116), vaccination intentions significantly predicted vaccination status (OR = 1.66, 95%CI (1.13, 2.44), p < 0.05) and rates of informed choice (OR = 1.51, 95%CI (1.07, 2.13), p < 0.012), although there were no direct effects of experimental factors on vaccination rates. Qualitative analysis suggested that logistical barriers impeded immunization rates. Risk communication and values clarification methods may contribute to increased vaccination intentions, which may, in turn, predict vaccination status if logistical barriers are also addressed. © 2015 Society for Risk Analysis.
    Risk Analysis 05/2015; DOI:10.1111/risa.12418
  • [Show abstract] [Hide abstract]
    ABSTRACT: Timely warning communication and decision making are critical for reducing harm from flash flooding. To help understand and improve extreme weather risk communication and management, this study uses a mental models research approach to investigate the flash flood warning system and its risk decision context. Data were collected in the Boulder, Colorado area from mental models interviews with forecasters, public officials, and media broadcasters, who each make important interacting decisions in the warning system, and from a group modeling session with forecasters. Analysis of the data informed development of a decision-focused model of the flash flood warning system that integrates the professionals' perspectives. Comparative analysis of individual and group data with this model characterizes how these professionals conceptualize flash flood risks and associated uncertainty; create and disseminate flash flood warning information; and perceive how warning information is (and should be) used in their own and others' decisions. The analysis indicates that warning system functioning would benefit from professionals developing a clearer, shared understanding of flash flood risks and the warning system, across their areas of expertise and job roles. Given the challenges in risk communication and decision making for complex, rapidly evolving hazards such as flash floods, another priority is development of improved warning content to help members of the public protect themselves when needed. Also important is professional communication with members of the public about allocation of responsibilities for managing flash flood risks, as well as improved system-wide management of uncertainty in decisions. © 2015 Society for Risk Analysis.
    Risk Analysis 05/2015; DOI:10.1111/risa.12403
  • [Show abstract] [Hide abstract]
    ABSTRACT: The U.S. federal government regulates the reliability of bulk power systems, while the reliability of power distribution systems is regulated at a state level. In this article, we review the history of regulating electric service reliability and study the existing reliability metrics, indices, and standards for power transmission and distribution networks. We assess the foundations of the reliability standards and metrics, discuss how they are applied to outages caused by large exogenous disturbances such as natural disasters, and investigate whether the standards adequately internalize the impacts of these events. Our reflections shed light on how existing standards conceptualize reliability, question the basis for treating large-scale hazard-induced outages differently from normal daily outages, and discuss whether this conceptualization maps well onto customer expectations. We show that the risk indices for transmission systems used in regulating power system reliability do not adequately capture the risks that transmission systems are prone to, particularly when it comes to low-probability high-impact events. We also point out several shortcomings associated with the way in which regulators require utilities to calculate and report distribution system reliability indices. We offer several recommendations for improving the conceptualization of reliability metrics and standards. We conclude that while the approaches taken in reliability standards have made considerable advances in enhancing the reliability of power systems and may be logical from a utility perspective during normal operation, existing standards do not provide a sufficient incentive structure for the utilities to adequately ensure high levels of reliability for end-users, particularly during large-scale events. © 2015 Society for Risk Analysis.
    Risk Analysis 05/2015; DOI:10.1111/risa.12401
  • [Show abstract] [Hide abstract]
    ABSTRACT: Over the last decade the health and environmental research communities have made significant progress in collecting and improving access to genomic, toxicology, exposure, health, and disease data useful to health risk assessment. One of the barriers to applying these growing volumes of information in fields such as risk assessment is the lack of informatics tools to organize, curate, and evaluate thousands of journal publications and hundreds of databases to provide new insights on relationships among exposure, hazard, and disease burden. Many fields are developing ontologies as a way of organizing and analyzing large amounts of complex information from multiple scientific disciplines. Ontologies include a vocabulary of terms and concepts with defined logical relationships to each other. Building from the recently published exposure ontology and other relevant health and environmental ontologies, this article proposes an ontology for health risk assessment (RsO) that provides a structural framework for organizing risk assessment information and methods. The RsO is anchored by eight major concepts that were either identified by exploratory curations of the risk literature or the exposure-ontology working group as key for describing the risk assessment domain. These concepts are: (1) stressor, (2) receptor, (3) outcome, (4) exposure event, (5) dose-response approach, (6) dose-response metric, (7) uncertainty, and (8) measure of risk. We illustrate the utility of these concepts for the RsO with example curations of published risk assessments for ionizing radiation, arsenic in drinking water, and persistent pollutants in salmon. © 2015 Society for Risk Analysis.
    Risk Analysis 05/2015; DOI:10.1111/risa.12414
  • [Show abstract] [Hide abstract]
    ABSTRACT: We describe recent advances in biophysical and social aspects of risk and their potential combined contribution to improve mitigation planning on fire-prone landscapes. The methods and tools provide an improved method for defining the spatial extent of wildfire risk to communities compared to current planning processes. They also propose an expanded role for social science to improve understanding of community-wide risk perceptions and to predict property owners' capacities and willingness to mitigate risk by treating hazardous fuels and reducing the susceptibility of dwellings. In particular, we identify spatial scale mismatches in wildfire mitigation planning and their potential adverse impact on risk mitigation goals. Studies in other fire-prone regions suggest that these scale mismatches are widespread and contribute to continued wildfire dwelling losses. We discuss how risk perceptions and behavior contribute to scale mismatches and how they can be minimized through integrated analyses of landscape wildfire transmission and social factors that describe the potential for collaboration among landowners and land management agencies. These concepts are then used to outline an integrated socioecological planning framework to identify optimal strategies for local community risk mitigation and improve landscape-scale prioritization of fuel management investments by government entities. © 2015 Society for Risk Analysis.
    Risk Analysis 05/2015; DOI:10.1111/risa.12373
  • [Show abstract] [Hide abstract]
    ABSTRACT: A model for the transmission of Salmonella between finisher pigs during transport to the abattoir and subsequent lairage has been developed, including novel factors such as environmental contamination and the effect of stress, and is designed to be adaptable for any EU Member State (MS). The model forms part of a generic farm-to-consumption model for Salmonella in pigs, designed to model potentially important risk factors and assess the effectiveness of interventions. In this article, we discuss the parameterization of the model for two case study MSs. For both MSs, the model predicted an increase in the average MS-level prevalence of Salmonella-positive pigs during both transport and lairage, accounting for a large amount of the variation between reported on-farm prevalence and reported lymph-node prevalence at the slaughterhouse. Sensitivity analysis suggested that stress is the most important factor during transport, while a number of factors, including environmental contamination and the dose-response parameters, are important during lairage. There was wide variation in the model-predicted change in prevalence in individual batches; while the majority of batches (80-90%) had no increase, in some batches the increase in prevalence was over 70% and in some cases infection was introduced into previously uninfected batches of pigs. Thus, the model suggests that while the transport and lairage stages of the farm-to-consumption exposure pathway are unlikely to be responsible for a large increase in average prevalence at the MS level, they can have a large effect on prevalence at an individual-batch level. © 2015 Society for Risk Analysis.
    Risk Analysis 05/2015; DOI:10.1111/risa.12390
  • [Show abstract] [Hide abstract]
    ABSTRACT: Recent studies indicate that absence of the consideration of risk attitudes of decisionmakers in the risk matrix establishment process has become a major limitation. In order to evaluate risk in a more comprehensive manner, an approach to establish risk matrices that integrates risk attitudes based on utility theory is proposed. There are three main steps within this approach: (1) describing risk attitudes of decisionmakers by utility functions, (2) bridging the gap between utility functions and the risk matrix by utility indifference curves, and (3) discretizing utility indifference curves. A complete risk matrix establishment process based on practical investigations is introduced. This process utilizes decisionmakers' answers to questionnaires to formulate required boundary values for risk matrix establishment and utility functions that effectively quantify their respective risk attitudes. © 2015 Society for Risk Analysis.
    Risk Analysis 05/2015; DOI:10.1111/risa.12400
  • [Show abstract] [Hide abstract]
    ABSTRACT: This study uses state-level panel data from a 33-year period to test the hypotheses of offsetting and enhancing behavior with regards to motorcycle helmet legislation. Results presented in this article find no evidence of offsetting behavior and are consistent with the presence of enhancing behavior. State motorcycle helmet laws are estimated to reduce motorcycle crashes by 18.4% to 31.9%. In the absence of any behavioral adaptations among motorcyclists mandatory helmet laws are not expected to have any significant impact on motorcycle crash rates. The estimated motorcycle crash reductions do not appear to be driven by omitted variable bias or nonclassical measurement error in reported crashes. Overall, the results strongly suggest that mandatory helmet laws yield significant changes in motorcycle mobility in the form of reduced risk taking and/or decreased utilization. © 2015 Society for Risk Analysis.
    Risk Analysis 05/2015; DOI:10.1111/risa.12376
  • Risk Analysis 05/2015; DOI:10.1111/risa.12411
  • [Show abstract] [Hide abstract]
    ABSTRACT: This article argues that "game-changing" approaches to risk analysis must focus on "democratizing" risk analysis in the same way that information technologies have democratized access to, and production of, knowledge. This argument is motivated by the author's reading of Goble and Bier's analysis, "Risk Assessment Can Be a Game-Changing Information Technology-But Too Often It Isn't" (Risk Analysis, 2013; 33: 1942-1951), in which living risk assessments are shown to be "game changing" in probabilistic risk analysis. In this author's opinion, Goble and Bier's article focuses on living risk assessment's potential for transforming risk analysis from the perspective of risk professionals-yet, the game-changing nature of information technologies has typically achieved a much broader reach. Specifically, information technologies change who has access to, and who can produce, information. From this perspective, the author argues that risk assessment is not a game-changing technology in the same way as the printing press or the Internet because transformative information technologies reduce the cost of production of, and access to, privileged knowledge bases. The author argues that risk analysis does not reduce these costs. The author applies Goble and Bier's metaphor to the chemical risk analysis context, and in doing so proposes key features that transformative risk analysis technology should possess. The author also discusses the challenges and opportunities facing risk analysis in this context. These key features include: clarity in information structure and problem representation, economical information dissemination, increased transparency to nonspecialists, democratized manufacture and transmission of knowledge, and democratic ownership, control, and interpretation of knowledge. The chemical safety decision-making context illustrates the impact of changing the way information is produced and accessed in the risk context. Ultimately, the author concludes that although new chemical safety regulations do transform access to risk information, they do not transform the costs of producing this information-rather, they change the bearer of these costs. The need for further risk assessment transformation continues to motivate new practical and theoretical developments in risk analysis and management. © 2015 Society for Risk Analysis.
    Risk Analysis 05/2015; DOI:10.1111/risa.12391
  • [Show abstract] [Hide abstract]
    ABSTRACT: Meta-analyses offer a rigorous and transparent systematic framework for synthesizing data that can be used for a wide range of research areas, study designs, and data types. Both the outcome of meta-analyses and the meta-analysis process itself can yield useful insights for answering scientific questions and making policy decisions. Development of the National Ambient Air Quality Standards illustrates many potential applications of meta-analysis. These applications demonstrate the strengths and limitations of meta-analysis, issues that arise in various data realms, how meta-analysis design choices can influence interpretation of results, and how meta-analysis can be used to address bias and heterogeneity. Reviewing available data from a meta-analysis perspective can provide a useful framework and impetus for identifying and refining strategies for future research. Moreover, increased pervasiveness of a meta-analysis mindset-focusing on how the pieces of the research puzzle fit together-would benefit scientific research and data syntheses regardless of whether or not a quantitative meta-analysis is undertaken. While an individual meta-analysis can only synthesize studies addressing the same research question, the results of separate meta-analyses can be combined to address a question encompassing multiple data types. This observation applies to any scientific or policy area where information from a variety of disciplines must be considered to address a broader research question. © 2015 Society for Risk Analysis.
    Risk Analysis 05/2015; DOI:10.1111/risa.12405
  • [Show abstract] [Hide abstract]
    ABSTRACT: Fish consumption advisories are issued by states, tribes, and federal agencies to provide guidance to consumers about eating sport-caught fish potentially affected by chemical contaminants. Previous work has found that while anglers report being aware that advisories are available, awareness and use of specific advisory recommendations is low. This study uses the Integrative Model of Behavioral Prediction (IMBP) to identify beliefs with potential to increase intentions to follow fish consumption advisories in Great Lakes states. We conducted a mail survey of 1,712 licensed anglers in seven of eight Great Lakes states (excluding Ohio) to gauge advisory awareness, cognitive factors influencing fish consumption behaviors (informed by the IMBP), and sociodemographic characteristics. Results show that most anglers reported being generally or vaguely aware of fish consumption advisories and try to follow them, but far fewer report being aware of specific advice needed to decide whether or not to consume different types of sport-caught fish. Informed by the IMBP, we also identify several behavioral, normative, and control beliefs that have sufficient room to change, strong associations with intentions to follow the advisories, and potential to be modified if targeted with strategic risk messages. Targeting these beliefs with strategic communication holds potential to increase the proportion of anglers intending to follow fish consumption advisory recommendations in choosing which fish to eat. © 2015 Society for Risk Analysis.
    Risk Analysis 05/2015; DOI:10.1111/risa.12408
  • [Show abstract] [Hide abstract]
    ABSTRACT: This article addresses the issue of how performance and risk management can complement each other in order to enhance the management of an enterprise. Often, we see that risk management focuses on goal achievements and not the enterprise risk related to its activities in the value chain. The statement "no goal, no risk" is a common misconception. The main aim of the article is to present a normative model for describing the links between performance and risk, and to use this model to give recommendations on how to best structure and plan the management of an enterprise in situations involving risk and uncertainties. The model, which has several novel features, is based on the interaction between different types of risk management (enterprise risk management, task risk management, and personal risk management) and a structure where the enterprise risk management overrules both the task and personal risk management. To illustrate the model we use the metaphor of a ship, where the ship is loaded with cash-generating activities and has a direction over time determined by the overall strategic objectives. Compared to the current enterprise risk management practice, the model and related analysis are founded on a new perspective on risk, highlighting knowledge and uncertainties beyond probabilities. © 2015 Society for Risk Analysis.
    Risk Analysis 05/2015; DOI:10.1111/risa.12375
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    ABSTRACT: Many real-world planning and decision problems are far too uncertain, too variable, and too complicated to support realistic mathematical models. Nonetheless, we explain the usefulness, in these situations, of qualitative insights from mathematical decision theory. We demonstrate the integration of info-gap robustness in decision problems in which surprise and ignorance are predominant and where personal and collective psychological factors are critical. We present practical guidelines for employing adaptable-choice strategies as a proxy for robustness against uncertainty. These guidelines include being prepared for more surprises than we intuitively expect, retaining sufficiently many options to avoid premature closure and conflicts among preferences, and prioritizing outcomes that are steerable, whose consequences are observable, and that do not entail sunk costs, resource depletion, or high transition costs. We illustrate these concepts and guidelines with the example of the medical management of the 2003 SARS outbreak in Vietnam. © 2015 Society for Risk Analysis.
    Risk Analysis 05/2015; DOI:10.1111/risa.12397
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    ABSTRACT: In Britain, it is recommended that, to stay healthy, adults should do 150 minutes of moderate-intensity physical activity every week. The recommendations provided by the U.K. government, however, remain silent in regard to the type of activity that should be done. Using the annual Health Survey for England we compare how different types of physical activities predict a person's weight. In particular, we consider clinically measured body mass index and waist circumference. We document mean slopes emanating from ordinary least squares regressions with these measures as the dependent variables. We show that individuals who walk at a brisk or fast pace are more likely to have a lower weight when compared to individuals doing other activities. Additionally, we highlight that the association between physical activity and weight is stronger for females and individuals over the age of 50. Our overall conclusions are robust to a number of specifications. © 2015 Society for Risk Analysis.
    Risk Analysis 05/2015; DOI:10.1111/risa.12417
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    ABSTRACT: In this article, we introduce a framework for analyzing the risk of systems failure based on estimating the failure probability. The latter is defined as the probability that a certain risk process, characterizing the operations of a system, reaches a possibly time-dependent critical risk level within a finite-time interval. Under general assumptions, we define two dually connected models for the risk process and derive explicit expressions for the failure probability and also the joint probability of the time of the occurrence of failure and the excess of the risk process over the risk level. We illustrate how these probabilistic models and results can be successfully applied in several important areas of risk analysis, among which are systems reliability, inventory management, flood control via dam management, infectious disease spread, and financial insolvency. Numerical illustrations are also presented.
    Risk Analysis 05/2015; DOI:10.1111/risa.12384