Risk Analysis最新文献

Understanding what factors influence an attacker's decision to attack a soft target is important for allocating resources effectively to defend valuable targets. In this study, we aim to validate a game-theoretic model that explores the relationship between the reward and probability of successfully attacking through multiple layers of defense. We created multiple scenarios corresponding to each of four game-theoretic cases, resulting in a 2 × 2 factorial design (defended vs. undefended targets X low vs. high expected values [EVs] for attackers). We recruited 454 US adults from Prolific.com to decide whether to attack for a series of 24 scenarios, which varied the probability of success, the magnitude of reward, and whether Layer 1 was signaled to be defended or not. Results were generally consistent with the game model predictions, including a greater tendency to attack undefended targets with a higher EV. Targets with a low probability of success and greater reward were less likely to be attacked than targets with a higher probability of success and smaller reward. Additionally, participants with a higher self-reported risk-taking were significantly more likely to attack for a given trial compared to participants with lower self-reported risk-taking. This validated game model can be used as a tool to help stakeholders identify where threats are the most likely to occur based on inherent defenses and appeal to attackers.

Risk perception and communication research has to a large extent discussed risk issues on the basis of an understanding of risk as probabilities and expected values. The present article aims at providing some reflections on this research when adopting an uncertainty-based risk perspective, in line with contemporary conceptualizations of risk. This type of perspective sees uncertainty, rather than probability, as a main component of risk, in addition to the consequences and the severity of these consequences. The article shows that this perspective provides opportunities for new research in the field, which can have important impacts on how risk is understood, communicated, and handled in society. Some main challenges for the research are identified and discussed.

The objective of this study is to replicate the original study by Fischhoff et al. (1978) and its replication by Fox-Glassman and Weber (2016) and to examine whether risk perceptions for the previously studied activities and technologies have changed over the past 40 years, especially when activities/technologies related to contemporary concerns are included. To achieve this goal, the list of activities/technologies has been modified. To facilitate the analysis of individual data, all participants were asked to rate the benefits and risks of 24 activities. The within-participant approach was also used to achieve the second objective of our study: to analyze the relationship between perceived benefits and risks. In summary, the design of this study differed from previous studies in the following ways: (1) Nine activities/technologies were added related to contemporary concerns such as global warming and fake news on the Internet; (2) all participants rated both benefits and risks; (3) data were collected online (as in the 2016 study); (4) the study was conducted by Prolific with a sample size large enough to detect medium-size effects (n = 382). The two-factor structure proposed by Fischhoff et al.-unknown risk and dread risk-was confirmed on aggregated data for the new set of hazards, which included novel hazards. At the level of individual data, modest support for this structure was observed, and a very strong inverse relationship between perceived benefits and risks was observed.

The Chinese public is increasingly experiencing the local impacts of climate change, whereas the government downplays its domestic effects and critical opinions on environmental governance. As climate change perceptions are crucial for individual risk management, adaptation, and collective climate actions, it is vital to explore how these perceptions are shaped. Given the increasing significance of social media in climate change discourse, this study employs survey data from the 2021 Environmental Risk Perceptions and Environmental Behaviors of Urban Residents Project to investigate how social media exposure influences risk perceptions of climate change among the Chinese public. Drawing on the social amplification of risk framework, this study examines the effect of exposure to environmental information, exposure to opinion diversity, individuals' social media network ties to environmental opinion leaders, and the interaction between social media exposure and cultural values. The results indicate that in the contexts where climate change is neither politically divisive nor openly debated, social media exposure to diverse opinions and social media network ties to environmental scholars positively predict risk perceptions. Additionally, egalitarianism and fatalism are found to moderate the effect of these connections with environmental scholars. This study extends previous research, which focuses largely on the association between the frequency of social media exposure and risk perceptions of climate change, by revealing a more comprehensive and nuanced process that links social media exposure to climate change perceptions.

Communities exposed to Cascadia Subduction Zone earthquakes have diverse information needs. However, information about earthquake risk is often developed for general audiences and is rarely tested for its effectiveness at improving risk understanding or preparedness intentions for those general audiences, let alone ethnic minorities. Best practices in risk communication suggest that providing information that is personalized, clear, and culturally appropriate will improve people's willingness to engage with the material and improve learning outcomes. This study reports the test of a 2-h earthquake preparedness workshop that was based on active learning principles, addressed earthquake impacts, preparedness actions, and included goal setting activities to motivate participants' preparedness. We engaged local facilitators to deliver a culturally appropriate workshop in Spanish to 52 participants online and in-person. A pretest/posttest evaluation revealed significant increases in expected earthquake consequences, risk area accuracy for shaking zone and liquefaction zone, positive affect, self-efficacy, and, most important, preparedness intentions. These results indicate that an active learning strategy is an effective method of risk communication. However, further research is needed to identify ways to change the variables that had weak or nonsignificant impacts and to determine if the preparedness intentions ultimately produce preparedness actions.

Recent artificial intelligence (AI) risk management frameworks and regulations place stringent quality constraints on AI systems to be deployed in an increasingly competitive environment. Thus, from a software engineering point of view, a major issue is deciding when to release an AI system to the market. This problem is complex due to, among other features, the uncertainty surrounding the AI system's reliability and safety as reflected through its faults, the various cost items involved, and the presence of competitors. A novel general adversarial risk analysis framework with multiple agents of two types (producers and buyers) is proposed to support an AI system developer in deciding when to release a product. The implementation of the proposed framework is illustrated with an example and extensions to cases with multiple producers and multiple buyers are discussed.

Risk communicators frequently engage members of the public through social media; therefore, it is important to understand how to effectively communicate risks about environmental and health issues. This experiment with U.S. adults (N = 737) explored how message features in risk-focused social media posts-namely, message modality (text-only posts or text with the inclusion of photographs or data presentations) and risk representation (numerical risk details or nonnumerical summaries of risk information)-influence risk perceptions, perceived message informativeness, and intentions to share the content. To do so, we drew from research on visual communication and research on numerical and nonnumerical representations of risk. We assessed the robustness of these effects across three environmental risk domains (asthma, heat waves, and vector-borne diseases). We found that compared to text-only messages, text with a data presentation (i.e., graph or table) led to enhanced risk perceptions, perceptions of informativeness, and sharing intentions. Relative to nonnumerical messages, numerical messages generated greater perceived risk, were rated as more informative, and elicited greater sharing intentions. Additionally, the effects of risk representation depended on participants' numeracy level, such that numerical messages (vs. nonnumerical) elicited greater sharing intentions and perceived informativeness among high-numeracy individuals but had no such effects for low-numeracy individuals. We also found some evidence that message effects on perceived informativeness differed based on risk topic. Our results suggest that communicators can consider designing social media risk messages with numerical details and data visualizations.

Microbial-based cleaning products (MBCPs) are an emerging class of cleaning products that contain viable microorganisms, often bacteria or bacterial endospores, as intentionally added formulation ingredients for cleaning and/or odor control. Although several well-established methodologies exist to support risk analysis for conventional chemical-based cleaning products, at present there are no widely recognized methods or commonly utilized frameworks to support risk analysis for use of microbial ingredients present in MBCPs, specifically. The purpose of this work is to provide information to MBCP manufacturers and regulators that can be used to assist in developing their own approaches to MBCP risk assessment. As part of this assessment, potential hazards associated with use of bacterial or bacterial endospore ingredients of MBCPs can be adequately characterized, assessed, and managed as part of both product development and ongoing product stewardship. Accordingly, this document summarizes potential approaches to support strain-level identification of microbial ingredient(s), evaluate their hazards and potential for human exposure, and assess their potential effects following such exposures to different human populations. Recommendations for both hazard and risk characterization are discussed. Additionally, guidance is provided to support decision-making by risk managers, including guidance for the development of risk communication strategies, where appropriate, to mitigate the identified risks. Properly applied, the conceptual approaches described herein may facilitate the standardization and more consistent application of appropriate risk analysis procedures tailored to suit microbial ingredients present in MBCPs. Beyond their utility in assessing microbial ingredients commonly used in MBCPs today, these same approaches may help companies and regulators consider and manage risks for new microbial ingredients that may be utilized in future MBCP formulations.

This paper addresses the question of identifying and distinguishing risk amplification incidents and patterns in the news media. To meet this objective, our study incorporates a novel "floodlight" approach utilizing the Society for Risk Analysis Glossary in conjunction with topic modeling and time-series analysis, to investigate risk-focused stories within a corpus of 271,854 US news articles over the past two decades. We find that risk amplification in the US news media is concentrated around seven core risk news categories-business, domestic affairs, entertainment, environment, geopolitics, health, and technology-which also vary in the risk-related terms that they predominantly employ. We also identify 14 signal events that can be distinguished relative to general risk news within their categories. Across these events, the "War on Terror" and COVID-19 are seen to display uniquely dynamic media reporting patterns, including a systemic influence between risk news categories and the attenuation of other risk news. We discuss possible explanations for these findings along with their wider research and policy implications.

The renewable energy market in the United States of America (USA) has experienced several crests and troughs owing to the changes in the climate policies. These changes in the climate policies have impacted the climate risk management scenario in the USA. This impact has changed the behavioral pattern of the renewable energy drivers, and a supply-side analysis of this aspect is largely ignored in the literature. In this pursuit, the present study aims at analyzing the moderating role of climate policy uncertainty in shaping the behavior of renewable energy drivers in the USA. Given the risk analysis perspective, a novel multivariate quantile-on-quantile causality test is introduced in the present study to address five aspects of risk analysis, i.e., tail dependence, co-movement, predictability, multivariate, and asymmetric impact. Moreover, this test also addresses the omitted variable bias and absence of ortho-partiality distribution, which were inherent to Granger causality test. Along with the analysis at the national level, a firm-level analysis is also done by taking the top-5 renewable energy generation firms of the USA. The results show that the climate policy uncertainty has a dampening effect on the renewable energy drivers, and this effect differs at the firm level. These impacts show a significant policy dimension for addressing the climatic risk management concerns in the USA, while achieving the Sustainable Development Goal (SDG) 7 objectives.