Hasil untuk "Risk in industry. Risk management"

R. Hodrick

Dan Li, Li He, Zhengwei He et al.

Drought disasters severely constrain ecological security and agricultural sustainability in Xinjiang, and reliable monitoring across diverse vegetation types remains challenging because of the vegetation saturation and soil background effects in traditional indices. This study integrates the kernel-based NDVI (kNDVI), land surface temperature (LST), and precipitation into the TVDI framework to develop a three-dimensional temperature–vegetation–precipitation drought index (kTVPDI). The spatiotemporal evolution of drought from 2000 to 2024 was assessed using the Sen slope, Mann‒Kendall test, and Loess decomposition, and SHAP-based machine learning was applied to identify dominant drivers. The results show that kTVPDI has a significantly stronger correlation with soil moisture (r = −0.875) than TVDI, demonstrating improved monitoring accuracy. Drought severity increases from peripheral to the central regions and peaks at the beginning and end of the growing season. The mean annual drought intensity follows the order: desert > grassland > cropland > forest, and 66% of northern Xinjiang exhibits a slight upward trend. Driver analysis identifies potential evapotranspiration and wind speed as major contributors to drought intensification, whereas elevation and slope mitigate drought severity. Overall, the kTVPDI offers enhanced sensitivity and stability, providing a more robust tool for drought monitoring and supporting ecological management and risk mitigation in other arid and semi-arid regions globally.

Hasan Meral, Behlul Ersoy, Mesut Dogan

Sustainability has become a critical concern in finance, in particular for the insurance industry, which faces rising environmental and social risks. This paper examines the influence of environmental, social, and governance (ESG) factors on the performance of global insurance companies. Using a comprehensive dataset of 22 life and 59 non–life insurance firms from 2013 to 2022, we employ panel data analysis to explore the relationship between ESG scores and key performance metrics. Our findings reveal that higher ESG scores are significantly associated with a higher return on assets, more efficient management of expense and loss ratios, and increases in investment returns. These results show the importance of incorporating ESG factors into insurance decision-making to enhance sectoral resilience and corporate performance. The study concludes by emphasizing the need for insurers to leverage their technical expertise and strategic risk management capabilities in order to address sustainability challenges effectively.

Alireza Sanatkhah

Background and objective The role of public participation in managing natural crises, including floods, is evident, and the government will incur many costs without utilizing the potential of non-governmental organizations (NGOs). This study aims to explore the perceptions of NGOs in Iran regarding public participation in flood relief during the 2020 flood in Chabahar city, Sistan & Baluchistan Province, south of Iran. Method This is a qualitative study using the grounded theory. Participants were 25 members of NGOs who participated in relief operations during the 2020 flood in Chabahar city, who were selected using a purposive sampling method. A semi-structured interview was used to collect data. Member checking, analytical comparisons, and the auditing technique were used to determine the trustworthiness of the data. The data were analyzed using the grounded theory approach in three stages: open coding, selective coding, and axial coding. Results Causal factors included: Formation and support of NGOs, quality of flood management, operational transparency, and media culture-building. The intervening factors included: Quality and manner of information dissemination, quality of relief goods distribution and relief services, quality of institutional trust, and social-cultural conflicts. Contextual factors included: Regional public support for relief groups, cultural structure, and professional ethics of relief groups. Strategies included: Education and information on relief efforts, pragmatic/revolutionary approach to flood management, establishment of participatory platforms, and utilization of capacities. Consequences included: Lack of coordination in flood management, inapplicable policies, personal-psychological consequences, and institutional distrust. Conclusion Various causal, intervening, and contextual factors influence public participation in managing crises caused by floods in Iran.

Aodi Fu, Wenzheng Yu, Bashar Bashir et al.

This study investigates the spatiotemporal patterns and synergistic mechanisms of extreme heatwave–drought compound events in the Qaidam Basin from 1990 to 2020, integrating observational data and multivariate statistical analyses. The key findings include that all heatwave durations (1–7 days) exhibited significant increasing trends, with the fastest growth rate observed for 1-day events (2.3 events/decade). Spatially, the heatwave frequency intensified northward, peaking at Golmud Station (5.1 events/decade for 1-day events). The SPEI revealed contrasting trends—monthly moistening (+0.108/decade for SPEI1) versus seasonal to annual aridification (declines of 0.007–0.088/decade for SPEI3–12). Extreme droughts clustered in 2001 (SPEI1 = −2.03) and 2013 (SPEI6 = −1.87). The heatwave‒drought co-occurrence frequency generally declined (−0.86 events/year for 1-day events), yet an anomalous peak occurred in 2000, driven by Tibetan Plateau circulation anomalies. Local moisture conditions (precipitation and relative humidity, r = −0.41) dominated decoupling, while the North Atlantic Oscillation (NAO) and Western Pacific Index (WP) regulated interannual variability. The 2000 extreme episode was characterized by 500-hPa geopotential height anomalies (−10 gpm) and cyclonic 700-hPa wind patterns. This work provides the identification of teleconnections between compound extremes and western Pacific subtropical high dynamics in the northern Tibetan Plateau arid zone, offering dynamical foundations for extreme event risk assessment in warming–wetting transitional regions.

Vicky Zampeta, Gregory Chondrokoukis, Dimosthenis Kyriazis

Maritime safety is a critical concern for the transport sector and remains a key challenge for the international shipping industry. Recognizing that maritime accidents pose significant risks to both safety and operational efficiency, this study explores the application of big data analysis techniques to understand the factors influencing maritime transport accidents (MTA). Specifically, using extensive datasets derived from vessel performance measurements, environmental conditions, and accident reports, it seeks to identify the key intrinsic and extrinsic factors contributing to maritime accidents. The research examines more than 90 thousand incidents for the period 2014–2022. Leveraging big data analytics and advanced statistical techniques, the findings reveal significant correlations between vessel size, speed, and specific environmental factors. Furthermore, the study highlights the potential of big data analytics in enhancing predictive modeling, real-time risk assessment, and decision-making processes for maritime traffic management. The integration of big data with intelligent transportation systems (ITSs) can optimize safety strategies, improve accident prevention mechanisms, and enhance the resilience of ocean-going transportation systems. By bridging the gap between big data applications and maritime safety research, this work contributes to the literature by emphasizing the importance of examining both intrinsic and extrinsic factors in predicting maritime accident risks. Additionally, it underscores the transformative role of big data in shaping safer and more efficient waterway transportation systems.

Preeti Subba, Sudeshna Nandi, Malay Bhattacharya

Pesticide resistance has emerged as a critical challenge in modern agriculture, including tea plantations. Previous studies have highlighted the vital role of gut bacteria in developing resistance, offering potential opportunities for integrating novel bacterial strains into pest management strategies. Biston suppressaria poses a significant threat to the tea industry in India. The frequent application of flubendiamide for its control has resulted in increased resistance. Therefore, this study aims to investigate the gut bacteria of this pest that may confer resistance against pesticides and tea allelochemicals, while proving nutritional benefits to the host. Six flubendiamide-tolerant gut bacteria have been isolated through in vitro analysis. Among them, Priestia flexa (DM1a) and Bacillus safensis (DM2) showed high flubendiamide tolerance and cross-tolerance to deltamethrin, quinalphos, and emamectin benzoate. Additionally, a pesticide utilization assay conducted on MSF media revealed their ability to utilize pesticides for growth and development, indicating pesticide detoxification through the degradation process. The cellulose degradation and caffeine utilization tests confirmed their nutritional benefits and protection from tea allelochemicals. Furthermore, the strains exhibited tolerance to toxic metals such as Cd, Pb, As, and Cr up to 2500 ppm and resistance to certain antibiotics with an MDR index of ≥ 0.2. This result underscores the chances of spreading these resistance genes to the host pest and also the risk of disseminating to the surrounding environment, raising concerns. Moreover, GC-MS analysis of the gut extract reveals an abundance of fatty acids derivatives, indicating metabolic resistance in this pest. Overall, this study enhances the understanding of the potent gut bacteria associated with this major tea pest and suggests that these gut bacteria are not merely inhabitants but significant contributors to the host’s survivability and fitness, which must be considered when formulating pest management strategies.

Alessandro Ramponi, Sergio Scarlatti

We propose a credit risk model for portfolios composed of green and brown loans, extending the ASRF framework via a two-factor copula structure. Systematic risk is modeled using potentially skewed distributions, allowing for asymmetric creditworthiness effects, while idiosyncratic risk remains Gaussian. Under a non-uniform exposure setting, we establish convergence in quadratic mean of the portfolio loss to a limit reflecting the distinct characteristics of the two loan segments. Numerical results confirm the theoretical findings and illustrate how value-at-risk is affected by portfolio granularity, default probabilities, factor loadings, and skewness. Our model accommodates differential sensitivity to systematic shocks and offers a tractable basis for further developments in credit risk modeling, including granularity adjustments, CDO pricing, and empirical analysis of green loan portfolios.

Palani Jagan, Joseph Antony Visuvasam

Nonlinear dynamic properties of soil crucially influence structural responses during seismic events, highlighting the interdependence between soil and structural behavior. Incorporating soil–structure interaction (SSI) significantly increases structural vulnerability, especially in irregular conditions, compared to traditional fixed-base structures. Despite the emerging construction of reinforced concrete structures with floating columns in urban areas, their seismic performance, particularly when considering soil-structure interaction, remains largely unexplored. Therefore, this study aims to investigate the structural seismic response of mid-rise reinforcement concrete structures with and without floating columns situated on multilayered soil deposits, incorporating the effects of SSI. The nonlinearity of the soil materials was modeled using an isotropic hardening elastoplastic hysteretic constitutive model. A three-dimensional numerical investigation, employing finite element nonlinear time history analysis, was conducted to study seismic responses of structures under different configurations and base conditions. The results were presented as the ratio of structural responses with soil-structure interaction to fixed-base responses subjected to earthquake events. Structures with floating columns exhibited 1.43 times higher peak lateral storey displacement and 55% higher inter-storey drift ratio compared to those without, considering soil-structure interaction. The analysis results demonstrated a decrease in base shear values of up to 35% when accounting for SSI effects.

Suntichai Kotcharin, Kulaya Jantadej

This study examined the relationship between working capital management and the profitability of small and medium enterprises (SMEs) in the shipping industry, particularly during crises and geopolitical uncertainty, as well as the moderating effects of firm-specific characteristics and macroeconomic factors. We used firm-level data from Thailand’s shipping SMEs from 2001 to 2021 and a dynamic panel Generalized Method of Moments (GMM) approach. We found a nonlinear and negative relationship between working capital and profitability for all of the study’s samples. Shipping SMEs tended to adopt aggressive working capital policies during the global financial crisis, whereas they were likely to use conservative policies during the 2016–2017 shipping market turmoil, according to the separate analysis. The 2016–2017 shipping market turmoil negatively impacted firms’ profitability, albeit mitigated by sales growth. Our findings indicated that the impact of working capital management on profitability was more pronounced during the global financial crisis compared to the shipping industry turbulence observed in 2016–2017. We also discovered that, in the presence of China’s geopolitical risk, firms were likely to enhance their working capital efficiency and mitigate an adverse impact on firm performance with their financial leverage and firm size. Additionally, financially constrained firms exhibited an inverted U-shaped relationship between working capital and profitability. To maximize firms’ profitability, management should pay attention to their working capital management and attempt to maintain the optimum level of working capital. Moreover, management should consider working capital as an essential source of financing, especially for financially constrained firms. The findings shed light on the working capital management decisions made by shipping SMEs in the emerging market.

Roozbeh Roshanak, Alireza Rousta, Mahmoud Ahmadi Sharif et al.

Abstract The purpose of the current research is the mixed effect of marketing on blockchain technology with the mediating role of perceived usefulness in the customers of Bank Melli Iran in Tehran. The research method is applicable in terms of purpose, and descriptive-survey based on the method of data collection. The statistical population of this research is all the customers of the Bank Melli Iran in Tehran in 2023. For this purpose, according to Cochran's formula, 384 people were selected as the sample size, 420 questionnaires were distributed among the customers of the Bank Melli Iran in Tehran by a simple random method, and 393 questionnaires were collected. The data collection tool of this research is a questionnaire. The validity of the research tool has been confirmed by performing the confirmatory factor analysis technique. The reliability of the current research questionnaire was measured by calculating Cronbach's alpha coefficient, which was 0.815. Also, to analyze the data, structural equation modeling method using Smart-PLS3 software has been used. The research results indicate that senior management support, supply chain integration, and innovation capability have a significant impact on blockchain technology. Also, supply chain risk has not affected blockchain technology. Finally, the role of the marketing mix on perceived usefulness is demonstrated. Also, the perceived usefulness is affective on blockchain technology. Extended Abstract                                           Introduction Blockchain is used for various technology concepts related to databases of value exchange, security and identity among others. Blockchain technology is very important for business today. This technology is constantly evolving. Leading companies in the field of information and communication technology use blockchain technology because of its high security (Akbari Ganjeh et al., 2022). In today's era, experts have called blockchain technology the second internet, which is capable of transforming a large number of current patterns. One of the sectors that can use blockchain is the banking industry. Blockchain is a developing technology and is actually a place in the web world that records the data and information of a group of people in files, but this information is not available in a single place, and people from different parts of the world trade and communicate to each other without any records. Also, the information stored in the blockchain is a digital collection of decentralized records that is not maintained by any person or organization (Ekramifard et al., 2020). The banking industry is the most important industry in the world. Today, banks in advanced countries act as professional consultants, experts in increasing the financial resources of companies, and collecting and exchanging the necessary information for their customers, and they are considered one of the economic drivers of every country. In modern banking, there are various components that affect the process of mobilizing monetary resources of banks and financial institutions. Determining and identifying the degree of influence and the type of connection of these components with the success of banks in mobilizing monetary resources is a very important issue. Today, the position and conditions of financial institutions and banks are different from each other, and it is possible that the factors affecting the provision of monetary resources are different even for each branch of a banking group, which has caused a close competitive atmosphere between them. Therefore, in this research, we tried to answer this question: what role does the marketing mix have on blockchain technology with the mediating role of perceived usefulness? Theoretical Framework Ahmadi et al., (2022) carried out a research titled marketing future research in the banking industry with a focus on blockchain technology. The findings showed that the drivers of marketing researchers' interest in digital financial technologies and blockchain and the development of decentralized banking had the highest priority and were selected for scenario planning. Hosseingholipour & Einabadi (2022) in a research addressed the effects of international sanctions on the international banking interactions of Iranian companies on the blockchain platform. The results showed that international sanctions in the international banking interactions of Iranian companies can be presented as an opportunity in the context of blockchain, and by using blockchain, international banking interactions can be implemented and managed in a more effective way. Da Silva & Moro (2021) in a research addressed blockchain technology as a factor of consumer trust: literature analysis using the method of texts. Their findings indicate the relationship between some blockchain features such as tracking and privacy with customer trust. For this reason, marketing, social and economic researchers are advised to focus on the use of blockchain to improve consumer trust. Ali, Ally & Dwivedi (2020) performed a systematic and analytical review of articles related to blockchain technology in the financial services industry. The proposed classification framework of this research has three components: financial advantages, challenges, and functions enabled by blockchain. Methodology The current research is an applicable research which has been implemented by descriptive-survey method of causal type. The statistical population of the research is the customers of Bank Melli Iran in Tehran in 2023; and to determine the number of samples, since the size of the population is unknown, Cochran's formula will be used to determine the sample size. Therefore, according to Cochran's formula for the unknown population size, the number of samples was 384 people, in which data have been quantitatively analyzed. It has also been analyzed using SPSS and Smart-PLS3 software. In order to collect and measure data, a 43-item questionnaire with a five-point Likert scale (1-completely disagree, 2-disagree, 3-I have no opinion, 4-agree and 5-completely agree) was used. Also, its validity has been confirmed by professors and experts, and its reliability by Cronbach's alpha coefficient.   Discussion and Results The results of the analysis of demographic variables, Cronbach's alpha coefficient value and composite reliability for each construct, the values ​​of factor loadings between constructs and the average extracted variance of the research variables, the results of the coefficient of determination and the Stone-Geisser coefficient for the endogenous construct, the output of the software in the effectiveness coefficients, the software output in significant coefficients and the impact coefficients, the value of the test statistic and the results of the research hypotheses and anti-value values ​​and effect intensity of mediating variables were given. Conclusion The purpose of this study was to investigate the impact of marketing mix on blockchain technology with the mediating role of perceived usefulness, on the basis of which 7 hypotheses were investigated, and the effect of all factors on blockchain technology was confirmed except for the fourth hypothesis: the impact of supply chain risk on blockchain technology. Based on the first research hypothesis: marketing mix has a significant effect on perceived usefulness. This hypothesis has been confirmed based on statistical analysis. In other words, it can be predicted that if the marketing mix of Bank Melli Iran customers in Tehran is improved, their perceived usefulness will also increase. Therefore, since the marketing mix has an effect on perceived usefulness, they should pay special attention to indicators such as product marketing, price marketing, channel marketing, advertising activities, and individual image. In line with the result obtained in this hypothesis, Lin, Wang & Hwang (2010) showed that marketing mix affects perceived usefulness. Based on the second hypothesis of the research: the support of senior management has a significant impact on blockchain technology. This hypothesis has been confirmed based on statistical analysis. In other words, it can be predicted that if the support of the senior management of Bank Melli Iran customers in Tehran is improved, the use of blockchain technology will also increase. Therefore, since senior management's support has an impact on blockchain technology, they should pay special attention to indicators such as attention and active response, confirmation of access to resources, willingness to accept risks, and motivating employees. In line with the result obtained in this hypothesis, Wong et al., (2020) showed that top management support affects blockchain technology. Based on the third hypothesis of the research: supply chain integration has a significant impact on blockchain technology. This hypothesis has been confirmed based on statistical analysis. In other words, it can be predicted that if the integration of the supply chain of Bank Melli Iran customers in Tehran is improved, the use of blockchain technology will also increase. Therefore, since the integration of the supply chain affects blockchain technology, they should pay special attention to indicators such as understanding the needs of employees, information sharing, cooperation and coordination and strategic alliance, public and private partnerships, and sharing knowledge and innovation. In line with the result obtained in this hypothesis, Chiarini, Belvedere & Grando (2020) showed that supply chain integration affects blockchain technology. Based on the fourth research hypothesis: supply chain risk has a significant impact on blockchain technology. This hypothesis, based on statistical analysis, has not been confirmed. In other words, it can be predicted that if the supply chain risk of Bank Melli Iran customers in Tehran increases, the use of blockchain technology will not change. Therefore, since supply chain risk does not affect blockchain technology, it is necessary to pay attention to indicators such as delays in delivery and selection of products, storage capacity and inappropriate delivery, demand fluctuations, poor forecasting, labor shortages, closures, and price fluctuations. Contrary to the result obtained in this hypothesis, Wang et al., (2020) concluded in their research that supply chain risk has a positive and significant relationship with blockchain technology. Based on the fifth hypothesis of the research: innovation capability has a significant impact on blockchain technology. This hypothesis has been confirmed based on statistical analysis. In other words, it can be predicted that if the innovation ability of Bank Melli Iran customers in Tehran is improved, the use of blockchain technology will also increase. Therefore, since the ability to innovate affects blockchain technology, it is necessary to pay special attention to indicators such as using innovative techniques, regular improvement in operations, adopting innovative and technical solutions, using standard and simple operations, and protecting against risks. In line with the result obtained in this hypothesis, Wang et al., (2020) showed that innovation ability affects blockchain technology. Based on the sixth hypothesis of the research: perceived usefulness has a significant impact on blockchain technology. This hypothesis has been confirmed based on statistical analysis. In other words, it can be predicted that if the perceived usefulness of Bank Melli Iran customers in Tehran is improved, the use of blockchain technology will also increase. Therefore, since perceived usefulness affects blockchain technology, they should pay special attention to indicators such as obtaining information, saving money, being helpful, and being useful. In line with the result obtained in this hypothesis, Lin, Wang & Hwang (2010) showed that perceived usefulness affects blockchain technology. Based on the seventh hypothesis of the research: there is a significant relationship between the marketing mix of blockchain technology and the mediating role of perceived usefulness. This hypothesis has been confirmed based on statistical analysis. In other words, it can be predicted that if the marketing mix of Bank Melli Iran customers in Tehran is improved, the use of blockchain technology with the role of mediating perceived usefulness will also increase. Therefore, since the marketing mix has an effect on blockchain technology with the mediating role of perceived usefulness, they should pay special attention to indicators such as product marketing, price marketing, channel marketing, advertising measures, and the image of a person. In line with the result obtained in this hypothesis, Lin, Wang & Hwang (2010) showed that marketing mix affects blockchain technology with the mediating role of perceived usefulness.

Prince Nketiah, Herbert Ntuli

Destocking as a drought mitigation strategy exposes smallholder cattle farmers to adverse effects, including the distortion of farm planning and income loss, as cattle are sold off regardless of the market price. Factors influencing destocking as a drought mitigation strategy for smallholder cattle farmers have received less attention in the literature. The study assessed the relationship between drought and cattle destocking as well as factors that affect farmers’ destocking decision. The relationship between drought and cattle destocking was assessed using correlation analysis, while determinants of destocking were identified through the zero-inflated Poisson (ZIP) regression model, which controlled for structural zeros. The research covered the period 2008–2017 using secondary data from the National Income Dynamics Study (NIDS), the South Africa Weather Service and the Food and Agriculture Organisation (FAO). The study found that drought has direct correlation with the quantity of beef produced in South Africa at −0.67, with a 1% significance level. Farmers’ socioeconomic characteristics such as cattle herd size, income, secondary occupation, fodder purchase and ownership of land positively influenced cattle destocking decision while household size and cattle loss during drought influenced destocking decision negatively. Contribution: The study estimated the determinants of smallholder cattle farmers’ decision to destock during drought, using a count model and accounted for socioeconomic and farmer-specific factors.

Henok Shiferaw, Amanuel Zenebe, Eyasu Yazew et al.

Evaluating the flood and drought hazards provides vital information for sustainable water resources management, particularly in semi-arid, water-deficit environments. Most prior studies were limited in exploring the flood and drought hazards, which are important for early warning systems and preparedness. This study characterized the hydrological extreme hazards on the Gereb-Geba reservoir, namely the Suluh, Genfel, and Agula rivers. Flood frequency analysis was performed using the fitted flood frequency distribution in MATLAB. The 2D hydrodynamic model HEC-RAS was implemented to produce a flood-inundation map. Meteorological, agricultural, and hydrological droughts were analyzed using the Standardized Precipitation Index (SPI), Vegetation Condition Index (VCI), and Streamflow Drought Index (SDI), respectively. Using the Generalized Extreme Value (GEV), the estimated flood magnitude showed an increasing tendency in all the rivers across all the return periods (2-, 5-, 10-, 20-, 50-, and 100-years). The reservoir inundated an area of 12.8 km2 at an elevation of 1830 m.a.s.l. with a water depth of 80 m at the outlet. Suluh experienced more severe to extreme hydrological drought episodes than the Agula and Genfel rivers. Severe to extreme meteorological droughts were also observed in the respective catchments. Moreover, severe agricultural drought prevalence was also detected across all the river catchments. This study provides vital and comprehensive flood and drought information for water resources planning, management, and development.

Nandhini Swaminathan, David Danks

This study offers an in-depth analysis of the application and implications of the National Institute of Standards and Technology's AI Risk Management Framework (NIST AI RMF) within the domain of surveillance technologies, particularly facial recognition technology. Given the inherently high-risk and consequential nature of facial recognition systems, our research emphasizes the critical need for a structured approach to risk management in this sector. The paper presents a detailed case study demonstrating the utility of the NIST AI RMF in identifying and mitigating risks that might otherwise remain unnoticed in these technologies. Our primary objective is to develop a comprehensive risk management strategy that advances the practice of responsible AI utilization in feasible, scalable ways. We propose a six-step process tailored to the specific challenges of surveillance technology that aims to produce a more systematic and effective risk management practice. This process emphasizes continual assessment and improvement to facilitate companies in managing AI-related risks more robustly and ensuring ethical and responsible deployment of AI systems. Additionally, our analysis uncovers and discusses critical gaps in the current framework of the NIST AI RMF, particularly concerning its application to surveillance technologies. These insights contribute to the evolving discourse on AI governance and risk management, highlighting areas for future refinement and development in frameworks like the NIST AI RMF.

Selim Mankaï, Sébastien Marchand, Ngoc Ha Le

The demand for voluntary insurance against low-probability, high-impact risks is lower than expected. To assess the magnitude of the demand, we conduct a meta-analysis of contingent valuation studies using a dataset of experimentally elicited and survey-based estimates. We find that the average stated willingness to pay (WTP) for insurance is 87% of expected losses. We perform a meta-regression analysis to examine the heterogeneity in aggregate WTP across these studies. The meta-regression reveals that information about loss probability and probability levels positively influence relative willingness to pay, whereas respondents' average income and age have a negative effect. Moreover, we identify cultural sub-factors, such as power distance and uncertainty avoidance, that provided additional explanations for differences in WTP across international samples. Methodological factors related to the sampling and data collection process significantly influence the stated WTP. Our results, robust to model specification and publication bias, are relevant to current debates on stated preferences for low-probability risks management.

Wenqing Wu, Wenkai Liu, Jun Hu et al.

AbstractAs a landmark in China’s hydraulic engineering history, the Central Route of the South–North Water Diversion Project (SNWD-CR) plays a major role in alleviating severe water shortages in Northern China. Existing InSAR monitoring of the SNWD-CR based on one-dimensional viewing geometry and Sentinel-1 imaging is insufficient for a comprehensive assessment of deformation causes. Moreover, the poor geocoding accuracy hampers the previous interpretation of the estimated deformations. Here we carry out comprehensive two-dimensional deformation analyses over the head of the SNWD-CR by integrating the multitemporal PS/DS InSAR and the stress–strain model, where the well-designed topography and geocoded error correction can help to identify the causes of deformation. We apply our strategy to ascending and descending TerraSAR-X meter-resolution datasets acquired from June 2020 to February 2021. Geocoding errors in both ascending and descending orbits are corrected, and the relationship between topography error and horizontal positioning error is discussed. The multi-data fusion results reveal insignificant deformations in the east–west direction except for a makeshift rigid-frame bridge, whereas the vertical deformation field shows two uplifts and a subsidence area in the narrow canal with a maximum rate of 23 mm/y, which are likely to be related to rainfall and water diversion pressure. Furthermore, the combination of the external DEM and topographic residual offers the chance to reconstruct the high-accuracy DEM.

E. V. Altukhova, E. A. Asyaeva, M. A. Markov et al.

Current trends of economic development form the necessity to observe new requirements and restrictions. It shows a new turn of the progressive development in different spheres of human activity. Challenges of sustainable development call for concrete positions in the system of risk management. Dynamic emergence of innovation technologies and services speed up processes of decision-making, and urge on business-processes to more serious changes. Today the key lines in business transformation include building-up clean energy and shaping green economy and green society. At the same time, efficiency of business entities’ work is estimated not only in view of financial results, but also within the frames of total ecological effect with simultaneous submission of report data. The goal of the present research is to identify points of growth and development in the system of today’s contradictions and to define priorities of state policy in order to coordinate interests of industry and requirements of sustainable development. The article substantiates the importance of finance sector in the system of providing harmonization of decarbonization policy and economic development. It is also important to take into account the whole list of tools, methods and infrastructural elements promoting the effective interaction of all participants of the decarbonization process at the level of separate state and within the frames of global international space.

Yange Li, Jiaming Yang, Zheng Han et al.

AbstractThe improvement of the landslide susceptibility mapping (LSM) is a long-standing problem, as it provides basics for hazard mitigation. Recently, hybrid ensemble deep learning (DL) techniques have witnessed the potential for this purpose. In this paper, we proposed a novel ensemble DL model, namely GL-ResNet, which employs the conventional ResNet blocks for landslide feature extraction, long-short term memory (LSTM) structures for information storage, and a proposed GoogLeNet block (GBlk) to broaden model perception ability. To validate the model performance, a landslide inventory containing 1147 historical landslide polygons and the data of 12 landslide factors in the Wenchuan area in southwestern China, was presented and separated into training and validating dataset using a 7:3 randomly sampling ratio strategy. Based on AUC and Accuracy, GL-ResNet (0.96 and 0.909) outperformed logistic regression (0.92 and 0.851), support vector machines (0.94 and 0.884), deep belief networks (0.95 and 0.884), gated recurrent unit (0.94 and 0.884) and ResNet (0.95 and 0.894). We also explored the robustness of GL-ResNet for LSM. The results suggested that although GL-ResNet is sensitive to initial training conditions, it showed good robustness to model training method and sample ratios. In detail, GL-ResNet outperformed the conventional models in terms of fitting power and prediction performance by 0.03-0.04 and 0.02 respectively in most cases, with even greater differences in the limited training dataset.

Paweł Sakowski, Rafał Sieradzki, Robert Ślepaczuk

We propose a new measure of systemic risk to analyze the impact of the major financial market turmoils in the stock markets from 2000 to 2023 in the USA, Europe, Brazil, and Japan. Our Implied Volatility Realized Volatility Systemic Risk Indicator (IVRVSRI) shows that the reaction of stock markets varies across different geographical locations and the persistence of the shocks depends on the historical volatility and long-term average volatility level in a given market. The methodology applied is based on the logic that the simpler is always better than the more complex if it leads to the same results. Such an approach significantly limits model risk and substantially decreases computational burden. Robustness checks show that IVRVSRI is a precise and valid measure of the current systemic risk in the stock markets. Moreover, it can be used for other types of assets and high-frequency data. The forecasting ability of various SRIs (including CATFIN, CISS, IVRVSRI, SRISK, and Cleveland FED) with regard to weekly returns of S&P 500 index is evaluated based on the simple linear, quasi-quantile, and quantile regressions. We show that IVRVSRI has the strongest predicting power among them.

K. B. Gubbels, J. Y. Ypma, C. W. Oosterlee

We introduce a class of copulas that we call Principal Component Copulas (PCCs). This class combines the strong points of copula-based techniques with principal component analysis (PCA), which results in flexibility when modelling tail dependence along the most important directions in high-dimensional data. We obtain theoretical results for PCCs that are important for practical applications. In particular, we derive tractable expressions for the high-dimensional copula density, which can be represented in terms of characteristic functions. We also develop algorithms to perform Maximum Likelihood and Generalized Method of Moment estimation in high-dimensions and show very good performance in simulation experiments. Finally, we apply the copula to the international stock market to study systemic risk. We find that PCCs lead to excellent performance on measures of systemic risk due to their ability to distinguish between parallel and orthogonal movements in the global market, which have a different impact on systemic risk and diversification. As a result, we consider the PCC promising for capital models, which financial institutions use to protect themselves against systemic risk.