Mountainous regions face heightened flood and landslide hazards, necessitating efficient population relocation strategies. This study develops an integrated optimization framework for shelter site selection and population allocation in multi-hazard environments. Flood susceptibility was evaluated using six indicators through GIS spatial analysis, while landslide susceptibility was assessed using nine environmental factors with a Random Forest model, validated through 5-fold cross-validation (mean [Formula: see text] = 0.9282). The two susceptibility maps were integrated through fuzzy overlay to delineate multi-hazard zones and identify safe candidate shelters. Shelter capacities were estimated from available area data and standardized per-capita requirements. A dual-objective optimization model was then formulated to minimize the number of activated shelters and the maximum evacuation distance. Applied to Luchuan County, China, the model produced two contrasting solutions: prioritizing shelter minimization activated 22 shelters with a maximum evacuation distance of 13.19 km, whereas prioritizing evacuation distance activated 24 shelters and reduced the maximum distance to 12.16 km. These findings demonstrate the framework’s effectiveness in generating balanced and practical relocation strategies. Future improvements for the study area include integrating heterogeneous evacuee characteristics, refining shelter capacity estimates with detailed facility data, and incorporating temporal weighting to better capture evolving climate-driven hazard patterns.
Abstract
Purpose: This paper draws on a sociological analysis of the 2024 Azerbaijan Airlines flight J2-8243 incident to critique the Conflict Zone Information Bulletin (CZIB) normative-bureaucratic safety protocol. Sociological theories referenced include: passive and active learning; latent and active error; systems-thinking; organisational accident and the Swiss cheese model of accident trajectory. The Azerbaijan Airlines Flight J2-8243 incident followed earlier shoot-downs. For example: Iran Air Flight 655; Malaysia Airlines Flight MH17; Ukraine International Airlines Flight PS752. Earlier shoot-downs confirmed the importance of risk-free routing.
Design/methodology: The paper draws on authoritative secondary data, for example, the 2025 Preliminary Report published by Kazakhstan’s Commission for Aviation Investigation, to mount a critique of the Conflict Zone Information Bulletin (CZIB) normative-bureaucratic safety protocol. The paper: Describes the factors that contributed to the shoot-down; Tests the efficacy of normative-bureaucratic defences against shoot-downs, such as the sharing of information via International Civil Aviation Organisation (ICAO) Annex 13-compliant investigations and the issuing of CZIBs; Asks whether accident investigators pay sufficient attention to the social, economic and political context of a near-miss, incident, accident or shoot-down when establishing causation; Assesses the workload implications of considering the social, economic and political context of a near-miss, incident, accident or shoot-down.
Findings: It is concluded that Azerbaijan Airlines failed to act on the relevant CZIB for two reasons. First, Azerbaijan’s government expected the airline to maintain an air bridge with its influential neighbour. While a private concern, Azerbaijan Airlines is the country’s de facto flag carrier, and is expected to act as such by the government. Secondly, the authoritarian character of Azerbaijan’s government discouraged the airline from questioning its government. It is concluded that the European Union’s CZIB normative-bureaucratic safety protocol is compromised by realpolitik without and within the aviation industry. Normative-bureaucratic safety protocols such as CZIBs may create a false sense of security, given this reality.
Originality/value: To the best of the author’s knowledge, at the time this paper was written the 2024 Azerbaijan Airlines flight J2-8243 accident trajectory had not been subjected to a holistic, sociological analysis. The paper’s value lies in that fact that it examines the immediate and proximate causes of the flight J2-8243 incident through a powerful sociological lens that draws on the work of risk-management luminaries such as Professor James Reason, whose Swiss Cheese model of system failure is used by many aviation accident investigators.
• This dissertation integrates three papers on risk management in complex new product development projects (NPD) with an integrated perspective on the automotive industry. It seeks to provide a comprehensive access to the topic by highlighting the most relevant risk management aspects in NPD – processes and methods (chapter 2), organization and coordination (chapter 3) as well as culture and strategy (chapter 4). The focus of chapter 2 lies on the identification and assessment of risks as the initial and most critical risk management steps. It illustrates the application of the analytic hierarchy process (AHP) method as an established multi-criteria decision analysis method to create transparency on the overall risk position of a selected highly complex NPD in the automotive industry. Chapter 2 confirms the AHP method as a suitable approach for stronger preventive risk management in complex NPD with stakeholders with conflicting functional perspectives. This sets the stage for chapter 3 and a subsequent consideration of organization and coordination. Chapter 3 considers an issue of organization and coordination in complex NPD that is mainly based on the fact that the involved stakeholders have individual targets and rely on concurrent processes. The selected automotive industry example illustrates the resulting managerial challenge of balancing the overall NPD requirements such as product characteristics and development lead time (system perspective) and the targets of single stakeholders in NPD (individual perspective). The NK model as an important setting for search builds the methodical basis to solve this issue and results in optimized organizational and coordination setups. The implications on risk management in complex NPD as a result of newly emerging NPD types in the automotive industry are subject to chapter 4. These implications are in line with profound industry changes that include changes in the requirements of customers and markets. Chapter 4 uses complexity theory and deploys the lens of complex adaptive systems (CAS) to NPD to outline the emerging NPD types and their implications on risk framing activities. An extended risk framework is derived as basis that addresses the cultural and strategic shift in the automotive industry with regard to managing risk in emerging NPD types.
The increasing development in the consumer credit card market brings substantial regulatory and risk management challenges. The advanced machine learning models applications bring concerns about model transparency and fairness for both financial institutions and regulatory departments. In this study, we evaluate the consistency of one commonly used Explainable AI (XAI) technology, SHAP, for variable explanation in credit card probability of default models via a case study about credit card default prediction. The study shows the consistency is related to the variable importance level and hence provides practical recommendation for credit risk management
Blockchain-based decentralised lending is a rapidly growing and evolving alternative to traditional lending, but it poses new risks. To mitigate these risks, lending protocols have integrated automated risk management tools into their smart contracts. However, the effectiveness of the latest risk management features introduced in the most recent versions of these lending protocols is understudied. To close this gap, we use a panel regression fixed effects model to empirically analyse the cross-version (v2 and v3) and cross-chain (L1 and L2) effectiveness of liquidation mechanisms, measured through TVL and total revenue as proxies for performance of the two most popular lending protocols, Aave and Compound, during the period Jan 2021 to Dec 2024. Our analysis reveals that liquidation events in v3 of both protocols lead to an increase in total value locked and total revenue, with stronger impact on the L2 blockchain compared to L1. In contrast, liquidations in v2 have an insignificant impact, which indicates that the most recent v3 protocols have better risk management than the earlier v2 protocols. We also show that L1 blockchains are the preferred choice among large investors for their robust liquidity and ecosystem depth, while L2 blockchains are more popular among retail investors for their lower fees and faster execution.
Groundwater in karst regions is a vital drinking water source, but it is highly susceptible to contamination from industrial activities, which exacerbate pollution and pose health risks. This study investigated the concentration, spatial distribution, quality, health risks and sources of trace elements (TEs) in groundwater within a newly established industrial park in Guiyang, a representative city with a karst landscape. The results indicated that the trace element concentrations followed the order: Ti > Fe > Al > Ni > Cr > Mn > V > Cu > As > Co. Correlation Analysis (CA) and Hierarchical Cluster Analysis (HCA) suggested that the sources of TEs are multifaceted, with industrial activities identified as the primary influencing factor. Monte Carlo simulations revealed that the non-carcinogenic risk (NCR) associated with each element was negligible. However, due to industrial activities, Cr, Ni and As exhibited significant carcinogenic risks. As one of the characteristic pollutants of the electroplating industry, Cr presented the highest potential risk. The total carcinogenic risks (TCR) for adults and children were 3.24E-05 and 3.78E-05, respectively, both exceeding the acceptable risk threshold of 1E-06. These results make a meaningful contribution to the management of vulnerable aquifers in karst industrial areas, with an emphasis on protection against TEs contamination, which is critical for ensuring groundwater safeguard and protecting public health.
This study explores the impact of the selected GNSS reference station numbers on determining horizontal and vertical coseismic deformations resulting from the October 23, 2011, Mw 7.1 Van Earthquake in Eastern Anatolia, near Van city center. Leveraging high-precision Global Navigation Satellite System (GNSS) measurements from 14 CORS-TR (Continuously Operating Reference Stations of Türkiye) stations and utilizing Bernese v5.2 software for data analysis, the research evaluates the effect of datum selection through various reference station configurations on the accuracy of coseismic displacement measurements. Our findings indicate significant variations in RMS values and coseismic displacements across different datum models. The analysis shows that models incorporating eight or more International GNSS Service (IGS) stations in the datum definition yield more stable and consistent results, with variations in displacement measurements not statistically significant when compared to a model using all available (19 station) IGS stations. This underscores the critical importance of datum definition in geodetic measurements for the assessment of natural disasters and emphasizes the need for a comprehensive and precise selection of reference stations number in the geodetic field. The study contributes to the broader geodetic efforts to develop fault slip models and improve the understanding of seismic events’ impact on Earth’s surface.
The petrochemical industry faces significant safety challenges, necessitating stringent protocols and advanced monitoring systems. Traditional methods rely on manual inspections and fixed sensors, often reacting to hazards only after they occur. Multimodal AI, integrating visual, sensor, and textual data, offers a transformative solution for real-time, proactive safety management. This paper evaluates AI models—Gemini 1.5 Pro, OPENAI GPT-4, and Copilot—in detecting workplace hazards, ensuring compliance with Process Safety Management (PSM) and DuPont safety frameworks. The study highlights the models’ potential in improving safety outcomes, reducing human error, and supporting continuous, data-driven risk management in petrochemical plants. This paper is the first of its kind to use the latest multimodal tech to identify the safety hazard; a similar model could be deployed in other manufacturing industries, especially the oil and gas (both upstream and downstream) industry, fertilizer industries, and production facilities.
Background and objective In scientific texts on crisis management in Iran, crisis mostly refers to natural disasters and less attention has been made to man-made disasters. In this article, by emphasizing three prediction, prevention, and preparation phase of crisis management, we aim to identify the driving factors and the consequences of mainstream media’s effective activism in managing socio-political crises in Iran.
Method This is a qualitative study. The participants were 15 media policymakers, experts in the field of crisis management, and politicians in the field of socio-political affairs in Iran, who were selected by purposive and snowball sampling methods and semi-structured interviews continued until reaching until reaching theoretical saturation. The data analysis method was the thematic content analysis.
Results From a total of 250 initial codes, 159 basic themes, 26 organizing themes, and 8 global themes were obtained. Based on the findings, the role of the media in socio-political crisis management before, during, and after the crisis included supporting public opinion, raising awareness, holding responsible institutions accountable, informing, and having strategic function. The factors driving effective media activism in predicting socio-political crises included infrastructure drivers, functional capability, human resources, professional standards, and social capital. The consequences of effective media activism in predicting socio-political crises were: Social, political, and media’s social responsibility-related consequences. The factors driving effective media activism in preventing socio-political crises were divided into the drivers related to the public and the drivers related to the government/crisis managers. The consequences of effective media activism in preventing socio-political crises were divided into macro and micro consequences. The factors driving effective media activism in preparing for socio-political crises included process-related, content-related, and contextual drivers. The consequences of effective media activism in preparing for socio-political crises were categorized into three areas: Educational, psychological, and functional outcomes.
Conclusion The mainstream media in Iran can have effective activism in predicting, preventing, and preparing for social-political crises.
Risk in industry. Risk management, Industrial safety. Industrial accident prevention
In this paper, we discuss aspects of model risk management in financial institutions which could be adopted by academic institutions to improve the process of conducting academic research, identify and mitigate existing limitations, decrease the possibility of erroneous results, and prevent fraudulent activities.
Abstract Background Coccidiosis is one of the most frequently reported diseases in chickens, causing a significant economic impact on the poultry industry. However, there have been no previous studies evaluating the prevalence of this disease in broiler farms in Guangdong province. Therefore, this study aims to conduct an epidemiological investigation into the occurrence of Eimeria species and associated risk factors in intensive management conditions across four regions in Guangdong province, China. A total of 394 fecal samples were collected from 89 broiler farms in Guangdong province. The prevalence of Eimeria species infection was determined using PCR, and the occurrence of Clostridium perfringens type A was assessed using quantitative real-time PCR. Results The results showed an overall prevalence of 98.88% (88/89) at the farm level and 87.06% (343/394) at the flock level. All seven Eimeria species were identified, with E. acervulina (72.53%; 64/89), E. tenella (68.54%; 61/89), and E. mitis (66.29%; 59/89) at the farm level, and E. acervulina (36.55%; 144/394), E. mitis (35.28%; 139/394), and E. tenella (34.01%; 134/394) at the flock level. The predominant species combination observed was a co-infection of all seven Eimeria species (6.74%; 6/89), followed by a combination of E. acervulina, E. tenella, E. mitis, E. necatrix, E. brunetti, and E. maxima (5.62%, 5/89). A combination of E. acervulina, E. tenella, E. mitis, E. necatrix, E. brunetti, and E. praecox (4.49%; 4/89) was also observed at the farm level. Furthermore, the study identified several potential risk factors associated with the prevalence of Eimeria species, including farm location, chicken age, drinking water source, control strategy, and the presence of C. perfringens type A were identified as potential risk factors associated with prevalence of Eimeria species. Univariate and multivariate analyses revealed a significant association between E. necatrix infection and both grower chickens (OR = 10.86; 95% CI: 1.92–61.36; p < 0.05) and adult chickens (OR = 24.97; 95% CI: 4.29–145.15; p < 0.001) compared to starter chickens at the farm level. Additionally, farms that used groundwater (OR = 0.27; 95% CI: 0.08–0.94; p < 0.05) were less likely to have E. maxima compared to those that used running water. At the flock level, the prevalence of E. tenella was significantly higher in the Pearl River Delta (OR = 2.48; 95% CI: 1.0–6.15; p = 0.05) compared to eastern Guangdong. Interestingly, flocks with indigenous birds were less likely to have E. brunetti (OR = 0.48; 95% CI: 0.26–0.89; p < 0.05) compared to flocks with indigenous crossbred birds. Furthermore, flocks that used anticoccidial drugs (OR = 0.09; 95% CI: 0.03–0.31; p < 0.001) or a combination of vaccines and anticoccidial drugs (OR = 0.06; 95% CI: 0.01–0.25; p < 0.001) were less likely to be positive for E. tenella compared to flocks that only used vaccines. Finally, flocks with C. perfringens type A infection were significantly more likely to have E. necatrix (OR = 3.26; 95% CI: 1.96–5.43; p < 0.001), E. tenella (OR = 2.14; 95% CI: 1.36–3.36; p < 0.001), E. brunetti (OR = 2.48; 95% CI: 1.45–4.23; p < 0.001), and E. acervulina (OR = 2.62; 95% CI: 1.69–4.06; p < 0.001) compared to flocks without C. perfringens type A. Conclusions This study conducted an investigation on the prevalence, distribution, and risk factors associated with Eimeria species infection in broiler chickens in Guangdong. The farm-level prevalence of Eimeria species was higher than the previous prevalence figures for other areas and countries. E. brunetti was identified at higher prevalence in Guangdong than previously survived prevalence in different regions in China. Farm location, chicken age, drinking water source, control strategy, and the presence of C. perfringens type A were considered as potential risk factors associated with prevalence of Eimeria species. It is imperative to underscore the necessity for further surveys to delve deeper into the occurrence of Eimeria species under intensive management conditions for different flock purposes.
Charlie Sire, Didier Rullière, Rodolphe Le Riche
et al.
A central question in risk analysis is to identify the factors that drive the system toward a specific hazardous outcome, such as the exceedance of a given threshold. When relying on numerical simulators, we propose to study the distribution of the inputs, transformed into uniform variables via their cumulative distributions, conditionally on the occurrence of the hazardous event. To represent this multivariate conditional distribution for sensitivity analysis, we introduce an original quantization approach based on estimating a mixture of Dirac and local uniform distributions. For each marginal of this mixture, a Dirac component indicates a strong influence of the corresponding variable, whereas a uniform component with wide support reflects weak influence. A notable advantage of this method is its ability to identify the regions of the input space that most strongly influence the occurrence of the risk event, while also capturing the joint effects of multiple variables. However, learning mixture models typically relies on likelihood-based methods, which are not well suited to mixtures involving singular or Dirac components. To address this, we propose an \emph{Augmented Quantization} method, a reformulation of the classical quantization problem based on the p-Wasserstein distance, which can be computed in very general distribution spaces. The performance of Augmented Quantization in estimating such mixture models is first demonstrated on analytical toy problems, and then applied to sensitivity analysis of both an analytical function and a practical flooding case study on a section of the Loire River.
A fatality is the most detrimental incident that can occur in mountaineering. It is important to study previous cases and learn from circumstances surrounding fatal incidences in programmes sharing some common elements. This paper is set to investigate the occurrences of fatal incidences in mountaineering, the case of Mt. Kenya. It captures the qualitative findings on fatality occurrences. Respondents consisted of porters, guides, instructors, facilitators and key stakeholders involved in outdoor adventure activities on Mt. Kenya. The study used snowballing approach to identify the participants. Focus group discussions involving 52 respondents were conducted, in-depth interviews took place with four key informants and additional records were sought through desk reviews. The study found out that occurrence of fatalities was not well documented in a structured database. Deep grieving and regrets were noted. Predisposing factors leading to fatalities during mountaineering included; The “I MUST summit mentality”, lack of proper acclimatization, lack of visitor education, and lack of early diagnosis of altitude sicknesses. With the inherent risks and dangers that lead to fatalities in the mountaineering industry, the study recommends the need for providers to be keen on risk assessment and management as well as develop response strategies for various eventualities.
Abstract: To further promote the theoretical research on digital finance's effective support for high-quality development of the real economy, this paper reviews the current status of domestic and foreign research on the impact mechanism of digital finance on the real economy and the impact mechanism of digital finance on economic growth. At present, domestic and foreign research on the impact mechanism of digital finance on the real economy mainly includes the basic transmission mechanism featuring the improvement of financing availability and guiding the flow of funds in the real economy, and the indirect transmission mechanism using innovation and R&D as a channel. Domestic and foreign research on the impact mechanism of digital finance on economic growth mainly includes: the direct impact mechanism featuring the improvement of financial services universality and efficiency, and the indirect impact mechanism with resident consumption, innovation and entrepreneurship, industrial structure transformation, and business environment as the channels. Future research directions include: deepening the research on the indirect transmission mechanism of digital finance to the real economy; expanding the research on the indirect impact mechanism of digital finance on economic growth.
Engineering (General). Civil engineering (General), Risk in industry. Risk management
Based on the analysis of domestic and foreign experience of digital transformation and the conducted expert survey, the authors conclude that Russia, in comparison with other countries, does not have a leading position in the implementation of digital technologies. At the same time, the electric power industry being the basic sector of the economy which is responsible for its safe and sustainable development, in terms of digitalization is on the sidelines, yielding to retail, the banking industry, telecommunications and the manufacturing industry. At the same time, digitalisation is a promising direction and can have a significant positive impact on the electric power industry. The purpose of the study is to assess the current level of digital maturity of the electric power industry in Russia, identify the main barriers to digital transformation and develop proposals in order to overcome them.The article uses generalisation, comparative analysis, analyses empirical data of digitalisation in Russia and abroad, conducts a survey of experts in the electric power industry about its digital maturity.
In this paper, the author analyzes the effects of an emergency situation, primarily the COVID-19 pandemic, on investments in construction industry. In Serbia, the expansion of construction industry continued in the conditions of the COVID-19 pandemic. Based on the risk assessment that accompanies construction projects and the actions of the state to reduce pandemic disturbances, we can conclude that the short-term effects of state measures in construction industry have supported the implementation of construction projects. The first pandemic wave affected a change in the project management strategy aimed at adapting to the changed circumstances. However, the long-term economic consequences of the pandemic are still difficult to observe. Long-term pandemic effects emerge as a consequence of structural disorders, the so-called "multiplied" negative effects, which are the result of the connection between economic flows and activities. The more economic segments are affected, the more multipliers there will be; moreover, there are compensatory effects (e.g. the expansion of the pharmaceutical industry, production of computer equipment, etc.). The complex interaction of related economic activities determines the initial result of individual economic entities, which will affect the profitability of future construction projects. The biggest incentive for construction industry in our country is the introduction of the Central Register of Unified Procedures (CRUP). By using this system, complete documentation required for construction and use of facilities may be submitted and issued online in e-form.
Tristan Campbell, S. Don Bradshaw, Kingsley W. Dixon
et al.
Wildfire risk-management needs to consider interrelated factors that influence fire regimes, including changing climate and sometimes conflicting stakeholder priorities. With wildfires increasing in size and intensity over recent decades, wildfire risk management is becoming more important and more complex. For southwest Australia, wildfire risk-management is predicated on a longitudinal study of the relationship between prescribed burns and wildfires from 1953–2004 over a subset of this biodiverse region. Our study replicates the methodology of the longitudinal study, applying it to the wider region and extending the analysis to 2021. We found the extrapolation of the longitudinal study’s findings to the wider region invalid, as was extrapolation beyond 2004. In particular, the area of prescribed burns generally had negligible influence on wildfire area. However, more spatially complex fire history was strongly correlated with lower probability of large wildfires (independent of area burned). This highlights the limitation of extrapolating wildfire risk-management policies to areas of differing vegetation and/or climate, including changing climate over time. The potential of indigenous-led practices for wildfire risk and biodiversity conservation, particularly for areas with high spatial variability, is apparent as is the need for alternative strategies to prescribed burning as the primary tool in wildfire-risk mitigation.