Risk Analysis最新文献

{"title":"Shaping Trust Through Information Processing: How Social Media Risk Information Affects Government Trust During a Crisis.","authors":"Qixi Zhong, Zongchao Peng, Xiaojun Zhang","doi":"10.1111/risa.70108","DOIUrl":"https://doi.org/10.1111/risa.70108","url":null,"abstract":"<p><p>Trust-shaping is an important element of government risk management in the social media era. Studies to date have focused on the negative impact of exposure to social media risk information on government trust in a crisis, which mainly transpires by increasing the visibility of trust factors and stimulating negative perceptions. This study proposes another possible explanation from the perspective of information insufficiency and empirically tests it using 18,949 questionnaire data from China during a major emerging pandemic. The results show that social media risk information has a positive effect on central government trust, fully mediated by information insufficiency, and a negative effect on local government trust, fully mediated by negative affective risk response. This study also examined the paradoxical nature of the social media environment, in which truth and misinformation coexist. Misinformation was found to moderate the effect of risk facts on government trust by decreasing information insufficiency rather than increasing negative affective risk response. By distinguishing between levels of government, introducing a mediating role for information insufficiency, and examining the potential positive effects of ambivalent information environments, this study enhances our understanding of the dynamics of government trust during a crisis in the social media era.</p>","PeriodicalId":21472,"journal":{"name":"Risk Analysis","volume":" ","pages":""},"PeriodicalIF":3.3,"publicationDate":"2025-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145041399","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"How Will AI Shape the Future of Pandemic Response? Early Clues From Data Analytics.","authors":"Benjamin D Trump, Stephanie Galaitsi, Jeff Cegan, Igor Linkov","doi":"10.1111/risa.70103","DOIUrl":"https://doi.org/10.1111/risa.70103","url":null,"abstract":"<p><p>The COVID-19 pandemic has exposed critical gaps in our management of systemic risks within complex, interconnected systems. This review examines 10 key areas where artificial intelligence (AI) and data analytics can significantly enhance pandemic preparedness, response, and recovery. Inadequate early warning systems, insufficient real-time data on resource needs, and the limitations of traditional epidemiological models in capturing complex disease dynamics are among the challenges analyzed. To address these issues, we explore the potential of AI applications, including machine learning-based surveillance, deep learning for improved epidemiological modeling, and AI-driven optimization of non-pharmaceutical interventions. These technologies offer the promise of more timely, accurate, and granular analysis of pandemic risks, thereby supporting evidence-based decision-making in rapidly evolving crises. However, implementing AI in pandemic response raises significant ethical and governance challenges, particularly concerning privacy, fairness, and accountability. We parse the promise and challenges of AI in the evolving space of emergency response data analytics and highlight critical steps forward.</p>","PeriodicalId":21472,"journal":{"name":"Risk Analysis","volume":" ","pages":""},"PeriodicalIF":3.3,"publicationDate":"2025-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145030373","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Public Health Risks Under Temporally Compounding Climate Extremes.","authors":"Kuan Zhang, Xiaoming Wang, Tao Wang, Hongmei Zeng, Bingsheng Liu","doi":"10.1111/risa.70107","DOIUrl":"https://doi.org/10.1111/risa.70107","url":null,"abstract":"<p><p>Climate change is causing a significant increase in the number of compound extreme events that pose significantly greater threats to public safety. Chongqing is a megacity in southwestern China that took the brunt of temporally compounding events (TCEs) in the summer of 2022. We developed an approach based on the Intergovernmental Panel on Climate Change (IPCC) risk framework to assess the public health risks posed by TCEs. This approach was then applied to reveal temporal and spatial discrepancies in risks, which depend on natural endowments, socioeconomic conditions, and population demographics. High public health risks posed by heatwaves are caused by high exposure and vulnerability, which are primarily influenced by poor living conditions and living alone, together with underlying medical conditions such as mental disorders. The risks can be further magnified when TCEs emerge along with heatwaves, resulting from accumulated effects associated with noncommunicable diseases and vulnerable populations, including children and elderly individuals. Although a reduction in exposure to heatwaves can directly moderate these risks, prioritizing a reduction in exposure while simultaneously mitigating climate hazards and actively protecting people from TCEs, including alleviating vulnerability, is unequivocally necessary to minimize the risks to TCEs. Our findings indicate that highly vulnerable population groups are mostly exposed to TCEs and susceptible to impacts. These impacts exacerbate inequalities, engender environmental injustice, and hinder sustainable development. Efforts to reduce these risks by strengthening the health system and improving dwelling conditions are essential.</p>","PeriodicalId":21472,"journal":{"name":"Risk Analysis","volume":" ","pages":""},"PeriodicalIF":3.3,"publicationDate":"2025-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145030370","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Examining the Effect of Hazard Prevention and Control on Safety Outcomes in the Automotive Industry: The Mediating Role of Safety Behaviors and the Moderating Role of Safety Leadership.","authors":"Mohammadreza Bahrehbar, Saeed Givehchi","doi":"10.1111/risa.70095","DOIUrl":"https://doi.org/10.1111/risa.70095","url":null,"abstract":"<p><p>The high frequency of occupational accidents in manufacturing industries highlights deficiencies in controlling unsafe workplace conditions and behaviors. The automotive sector, as a cornerstone for related industries, has made a significant contribution to these statistics. This study examines the influence of hazard prevention and control on safety outcomes, focusing on the mediating role of safety behaviors and the moderating role of safety leadership within Iran's automotive industry. This quantitative research employed a stratified random sampling method to distribute survey questionnaires across 28 departments within the Iranian automotive manufacturing company, with 1149 employees participating. Structural equation modeling was conducted using the partial least squares approach to validate and analyze the hypothesized relationships. Additionally, expert assessments guided fuzzy cognitive mapping to identify causal relationships and prioritize variables within the occupational health and safety management system. The findings reveal significant associations between hazard prevention, control measures, and various dimensions of safety behaviors. While the evaluation and effectiveness of hazard prevention measures demonstrated the strongest impact, planning and implementation also influenced safety behaviors, albeit to a lesser extent. Safety outcomes were adversely affected by hazard prevention and control, mediated by safety behaviors and moderated by safety leadership. Safety leadership exhibited the most substantial effect in reducing lost time injuries, primarily by enhancing safety compliance. The proposed model enhances understanding of how organizations can develop effective strategies to improve workplace safety by identifying high-priority elements within the occupational health and safety management system. This allows them to allocate resources more efficiently and minimize incidents and waste.</p>","PeriodicalId":21472,"journal":{"name":"Risk Analysis","volume":" ","pages":""},"PeriodicalIF":3.3,"publicationDate":"2025-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145024123","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Living with risk, then and now: A dual review of Cam Grey's Living with Risk in the Late Roman World and of current AI-assisted book reviewing.","authors":"Louis Anthony Cox, Michael R Greenberg","doi":"10.1111/risa.70080","DOIUrl":"https://doi.org/10.1111/risa.70080","url":null,"abstract":"<p><p>This AI-assisted review article offers a dual review: a book review of Living with Risk in the Late Roman World by Cam Grey, and a critical review of the current potential of large language models (LLMs), specifically ChatGPT's DeepResearch mode, to assist in thoughtful and scholarly book reviewing within risk science. Grey's book presents an innovative reconstruction of how communities in the late Roman Empire perceived and adapted to chronic environmental and societal risks, emphasizing spatial variability, cultural interpretation, and the normalization of uncertainty. Drawing on commentary from a human reviewer and a parallel AI-assisted analysis, we compare the distinct strengths and limitations of each approach. The human review provides deep contextual judgment, skepticism, and sensitivity to narrative bias, while the AI-generated review offers thematic organization, broad literature synthesis, and analytical clarity. Our findings suggest that AI-assisted tools, when used alongside expert human insight, can significantly facilitate and enrich the scholarly review process. We argue that such hybrid methods hold promise for accelerating critical synthesis and expanding the scope of reflective inquiry in risk analysis, especially as the field increasingly engages with historical, cultural, and interdisciplinary perspectives.</p>","PeriodicalId":21472,"journal":{"name":"Risk Analysis","volume":" ","pages":""},"PeriodicalIF":3.3,"publicationDate":"2025-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145008492","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Ecological Risk Assessment and Management of Forest Fires in Tamil Nadu, India: A MaxEnt Model-Based Approach for Strategic Resource Allocation and Fire Mitigation.","authors":"Gowhar Meraj, Shizuka Hashimoto, Rajarshi Dasgupta, Bijon Kumer Mitra","doi":"10.1111/risa.70098","DOIUrl":"https://doi.org/10.1111/risa.70098","url":null,"abstract":"<p><p>Forest fires are integral to forest ecosystems as they influence nutrient cycling, plant regeneration, tree density, and biodiversity. However, human-induced climate change and activities have made forest fires more frequent, more intense, and more widespread, exacerbating their ecological and socioeconomic impact. Forest fires shape Tamil Nadu's diverse forest ecosystems, yet rising anthropogenic pressure and a warmer, drier climate have increased both their frequency and severity. We used a presence-only Maximum Entropy (MaxEnt) model to map the state-wide probability of fire occurrence and to guide the Tamil Nadu Forest Department (TNFD) in proactive suppression planning. Fire-occurrence points for 2020 (around 1900 ignitions) trained the model; independent ignitions from 2021 and 2022 (n = 2,906) validated it. Around nineteen topographic, climatic, and anthropogenic predictors, including Euclidean distance to cropland, rangeland, and roads, were resampled to 1 km resolution. The model showed excellent discrimination (AUC = 0.92) and achieved an overall test-set accuracy of 0.88 (Cohen's κ = 0.71). Distance to cropland (32.8 % permutation importance) and rangelands (25.8%) emerged as the strongest individual drivers, highlighting the combined influence of escaped agricultural burns and fuel condition on ignition risk. Jenks-optimized breaks split the landscape into Low (< 0.30), Medium (0.30-0.60), and High (≥ 0.60) classes, subsequently aggregated to the state's 2109 forest ranges. Although the High-risk zone comprises only 6.4 % of ranges (136/2109), it captured 54% of the 2021-22 ignitions, demonstrating substantial management leverage in the form of pre-season patrol planning and fuel-break maintenance. The resulting fire-probability map can help TNFD to prioritize patrol surges, pre-position water tankers, and refine early-warning bulletins for the 32 ranges exceeding the 0.80 \"critical\" threshold. Our approach provides a transferable template for data-poor tropical regions seeking to align limited suppression resources with the pockets of greatest ignition pressure. Future work should embed dynamic weather streams and near-real-time fuel-moisture indices to move from seasonal risk zoning toward operational early-warning.</p>","PeriodicalId":21472,"journal":{"name":"Risk Analysis","volume":" ","pages":""},"PeriodicalIF":3.3,"publicationDate":"2025-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145001467","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"An Integrative Analysis of Psychological Mechanisms Underlying the Effects of Online and Social Media Exposure on Drought Mitigation-Related Outcomes.","authors":"Hyunjung Hwang, Kwanho Kim, Chul-Joo Lee, Bee-Ah Kang, Hana Lee","doi":"10.1111/risa.70097","DOIUrl":"https://doi.org/10.1111/risa.70097","url":null,"abstract":"<p><p>Climate change is an urgent environmental risk. This study examines an integrative model suggesting psychological pathways from drought-related information exposure through online and social media to drought mitigation behavioral intentions and support for drought management policies. The model proposes links between these variables through perceived risks, fear, anger, and hope, with institutional trust acting as a moderator. A two-wave panel survey was conducted in the context of drought due to climate change in Korea (n = 694 at the baseline survey). The results show that online media exposure increased perceived risks and fear; perceived risks were positively associated with behavioral intentions and policy support, whereas fear was positively associated with behavioral intentions. Among people with low institutional trust, social media exposure was associated with risk perception and hope. These findings suggest that online and social media play distinct roles in shaping public responses to climate change, particularly depending on individuals' levels of institutional trust.</p>","PeriodicalId":21472,"journal":{"name":"Risk Analysis","volume":" ","pages":""},"PeriodicalIF":3.3,"publicationDate":"2025-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145001419","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Multiscale Risk Spillovers and External Driving Factors: Evidence From the Global Futures and Spot Markets of Staple Foods.","authors":"Yun-Shi Dai, Peng-Fei Dai, Stéphane Goutte, Duc Khuong Nguyen, Wei-Xing Zhou","doi":"10.1111/risa.70094","DOIUrl":"https://doi.org/10.1111/risa.70094","url":null,"abstract":"<p><p>Stable and efficient food markets are crucial for global food security. However, international staple food markets are increasingly exposed to complex risks, including intensified risk contagion and increasing external uncertainties. This paper systematically investigates risk spillovers in global staple food markets and explores the key determinants of these spillover effects, combining innovative decomposition-reconstruction techniques, risk connectedness analysis, and random forest models. The findings reveal that short-term components exhibit the highest volatility, with futures components generally more volatile than spot components. Further analysis identifies two main risk transmission patterns, namely, cross-grain and cross-timescale transmission, and clarifies the distinct roles of each component in various net risk spillover networks. Furthermore, price drivers, external uncertainties, and core supply-demand indicators significantly influence these spillover effects, with the heterogeneous importance of varying factors in explaining different risk spillovers. This study provides valuable information on the risk dynamics of staple food markets, offers evidence-based guidance to policymakers and market participants to improve risk warning and mitigation efforts, and supports the stabilization of international food markets and the protection of global food security.</p>","PeriodicalId":21472,"journal":{"name":"Risk Analysis","volume":" ","pages":""},"PeriodicalIF":3.3,"publicationDate":"2025-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145001421","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Evaluating Megacity Resilience to Pandemics: The Case of China.","authors":"Yaru Cheng, Hongyun Si, Zhikang Bao","doi":"10.1111/risa.70102","DOIUrl":"https://doi.org/10.1111/risa.70102","url":null,"abstract":"<p><p>Megacities' inherent complexity and dense populations heighten vulnerability to health crises, necessitating pandemic resilience research. This study pioneers a tailored resilience assessment framework for pandemic-facing megacities, building upon a refined Tyler and Moench urban resilience model. Applying grey correlation-technique for order preference by similarity to ideal solution (TOPSIS) methodology and barrier diagnosis modeling, we evaluated eight Chinese megacities. Key findings reveal: First, pandemic resilience scores exhibited fluctuating growth across all cities from 2014 to 2021. Shanghai demonstrated the most rapid improvement (23.13% increase), contrasting with Shenzhen's marginal gain (1.82%). Second, Shanghai achieved optimal coordination across systems, agents, and institutional dimensions in 2017, 2020, and 2021, whereas Shenzhen displayed the least dimension integration during 2016-2021. This dimensional equilibrium critically determines overall urban resilience. Finally, barrier analysis identified population scale, urban size, resource allocation efficiency, and mobility patterns as dominant resilience constraints. The findings and policy recommendations of this study can inform megacity development and pandemic response planning.</p>","PeriodicalId":21472,"journal":{"name":"Risk Analysis","volume":" ","pages":""},"PeriodicalIF":3.3,"publicationDate":"2025-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145001439","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Practical Method to Assess Bird Strike Risk in Air Operations Using a Count-Based Risk Mitigation Tool.","authors":"A Marijn Teunizen, Hans van Gasteren, Karen L Krijgsveld","doi":"10.1111/risa.70101","DOIUrl":"https://doi.org/10.1111/risa.70101","url":null,"abstract":"<p><p>Bird strikes pose a risk to aviation. Collisions between birds and airplanes result in a threat to human lives, economic losses, and material damage. The majority of these collisions occur on airfields during takeoff and landing. Knowing what bird species are present on airfields, in what numbers, and relating that to the extent to which these birds are involved in collisions can help to direct bird control activities to specific bird species and thus reduce bird strikes. In this article, we offer a method to quantify the risk of bird strikes at airfields based on counts of bird abundance on airfields. We analyzed bird abundance in relation to bird strike risks based on a dataset from six Dutch airfields covering three decades. We used the data to define two metrics: Species Strike Impact (SSI) and Bird Strike Risk Index (BSRI), which are both independent of aspects such as bird behavior, habitat, season, or weather. These two metrics, respectively, reflect the bird strike risk per individual of a bird species on an airfield based on hazard probability and severity (SSI), and they provide quick insight in the local status of overall bird strike risks by summing all species-related risks into one overall index (BSRI). Both metrics are calculated from counts on the airfield of birds, bird strikes, and air traffic movements. This method can be readily incorporated as a leading indicator in flight safety management at airfields, enabling bird control personnel to take risk-reducing actions targeted at specific bird species on airfields.</p>","PeriodicalId":21472,"journal":{"name":"Risk Analysis","volume":" ","pages":""},"PeriodicalIF":3.3,"publicationDate":"2025-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144966946","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}