Factors affecting farmers'choice to adopt risk management strategies:The application of multivariate and multinomial probit models

This study investigates the factors that impact farmers'adoption of risk management strategies(RMS)in Pakistan during times of uncertainty.The study examines farmers'adoption of RMS using both multinomial probit(MNP)and multivariate probit(MVP).Data were collected from 382 farmers sampled from four districts in KhyberPakhtunkhwa(KP)province of Pakistan via a multistage sampling technique.This study utilizes the MNP model,considering the assumption of Independence of Irrelevant Alternatives(IIA)and incorporating correlated error terms.The objective is to understand farmers'behavior in risky situations and determine if there is heterogeneity.Results are compared with the MVP model to assess robustness and gain deeper understanding of farmers'decisionmaking processes.The research findings reveal that our results are robust,and farmers behave homogeneously in various RMS scenarios.Farmers adopt RMS individually or in combination to mitigate the adverse effects of natural calamities on their livelihood.The risk-averse farmers,who perceive weather-related risks as a threat,access credits and information,and have farms close to a river are more likely to adopt RMS,irrespective of the format of the strategies available.Moreover,the predicted probabilities and correlation of the RMS and RM categories have strengthened our model estimation.These findings provide insights into the behavior of farmers in adopting RMS which are helpful for policymakers and stakeholders in developing strategies to mitigate the impacts of natural calamities on farmers.

Survey and Prospect for Applying Knowledge Graph in Enterprise Risk Management

Enterprise risk management holds significant importance in fostering sustainable growth of businesses and in serving as a critical element for regulatory bodies to uphold market order.Amidst the challenges posed by intricate and unpredictable risk factors,knowledge graph technology is effectively driving risk management,leveraging its ability to associate and infer knowledge from diverse sources.This review aims to comprehensively summarize the construction techniques of enterprise risk knowledge graphs and their prominent applications across various business scenarios.Firstly,employing bibliometric methods,the aim is to uncover the developmental trends and current research hotspots within the domain of enterprise risk knowledge graphs.In the succeeding section,systematically delineate the technical methods for knowledge extraction and fusion in the standardized construction process of enterprise risk knowledge graphs.Objectively comparing and summarizing the strengths and weaknesses of each method,we provide recommendations for addressing the existing challenges in the construction process.Subsequently,categorizing the applied research of enterprise risk knowledge graphs based on research hotspots and risk category standards,and furnishing a detailed exposition on the applicability of technical routes and methods.Finally,the future research directions that still need to be explored in enterprise risk knowledge graphs were discussed,and relevant improvement suggestions were proposed.Practitioners and researchers can gain insights into the construction of technical theories and practical guidance of enterprise risk knowledge graphs based on this foundation.

Mapping Climate Services for Disaster Risk Management: A Systematic Review and Research Gaps from a Policy Process Perspective

Climate services (CS) are crucial for mitigating and managing the impacts and risks associated with climate-induced disasters. While evidence over the past decade underscores their effectiveness across various domains, particularly agriculture, to maximize their potential, it is crucial to identify emerging priority areas and existing research gaps for future research agendas. As a contribution to this effort, this paper employs the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) methodology to review the state-of-the-art in the field of climate services for disaster risk management. A comprehensive search across five literature databases combined with a snowball search method using ResearchRabbit was conducted and yielded 242 peer-reviewed articles, book sections, and reports over 2013-2023 after the screening process. The analysis revealed flood, drought, and food insecurity as major climate-related disasters addressed in the reviewed literature. Major climate services addressed included early warning systems, (sub)seasonal forecasts and impact-based warnings. Grounded in the policy processes’ theoretical perspective, the main focus identified and discussed three prevailing policy-oriented priority areas: 1) development of climate services, 2) use-adoption-uptake, and 3) evaluation of climate services. In response to the limitations of the prevalent supply-driven and top-down approach to climate services promotion, co-production emerges as a cross-cutting critical aspect of the identified priority areas. Despite the extensive research in the field, more attention is needed, particularly pronounced in the science-policy interface perspective, which in practice bridges scientific knowledge and policy decisions for effective policy processes. This perspective offers a valuable analytical lens as an entry point for further investigation. Hence, future research agendas would generate insightful evidence by scrutinizing this critical aspect given its importance to institutions and climate services capacity, to better understand intricate facets of the development and the integration of climate services into disaster risk management.

Nursing Risk Management in the Prevention of Post-ERCP Pancreatitis

Objective:To study the role of nursing risk management in the prevention of post-ERCP pancreatitis.Methods:80 patients who underwent ERCP in our hospital from December 2023 to April 2024 were selected and randomly divided into an observation group and a control group using the random number table method,with 40 cases in each group.The observation group was given nursing risk management interventions and patients in the control group were given routine nursing interventions,and the patients in the two groups were compared in the incidence rate of pancreatitis and the satisfaction of nursing care.Results:The incidence of postoperative pancreatitis in the observation group was significantly lower than in the control group(P<0.05).The patient satisfaction of the observation group was significantly higher than that of the control group(P<0.05).Conclusion:Nursing risk management after ERCP can reduce the incidence of postoperative pancreatitis and improve patient satisfaction.

Electronic Commerce Security and Risk Management: An Important Part of College Curriculum

With the rapid expansion of e-commerce,its security and risk management problems become increasingly prominent.In the current business environment,the ability to understand and apply e-commerce security and risk management has become an important criterion to measure a good person.Therefore,the importance of e-commerce security and risk management courses in college education is self-evident.This course can not only help students master the basic knowledge of e-commerce,but also enable them to understand how to deal with various risks in practical work and ensure the safe operation of e-commerce.At the same time,through the study of e-commerce security and risk management,students can better understand the operation mode and law of e-commerce,and lay a solid foundation for their future career.In general,e-commerce security and risk management occupy an important position in the curriculum of colleges and universities,and play a crucial role in cultivating e-commerce professionals with practical operation ability and innovative thinking.

The indispensable role of resilience in rational landslide risk management for social sustainability

Landslide disasters reflect the conflict between human society and the natural environment,posing challenges to the sustainable development of mountain regions.Identification of potential landslides,estimation of the degree of damage and potential losses of elements at risk,and control of the loss are the major tasks of landslide risk management.Resilience is defined as a social system’s comprehensive abilities to cope with disasters,including the abilities to prepare,anticipate,preserve,absorb,respond,resist,recover,mitigate,learn,and adapt.As an indispensable role,resilience enables more rational landslide risk management for social sustainability.However,quantitative landslide risk management does not pay sufficient attention to the role of resilience.Hence,in this paper,the role of resilience in a landslide risk management framework is systematically discussed.A quantita-tive landslide risk management framework consists of hazard analysis,exposure analysis,risk estimation,risk evaluation,and risk control.In hazard analysis,resilience assessment could help identify potential landslides that could cause significant damage due to the poor resilience of the elements at risk.Resilience assessment in exposure analysis might aid in identifying the most vulnerable elements or regions to certain landslides.Consid-eration of resilience in risk estimation aids in the calculation of indirect losses and improves the results of direct losses analysis.In risk evaluation,resilience as a disaster-coping ability will impact the social system’s landslide risk tolerance threshold.Enhancing resilience is an essential strategy to reduce the vulnerability of social sys-tems.We also proposed that the efficient use of risk information will increase the accuracy of landslide resilience assessments.

Enterprise Internal Control Based on Risk Management with Moutai Group as an Example

Focusing on the two themes of"internal control"and"risk management",this paper makes an in-depth analysis of the current situation of risk management and internal control of Moutai Group.It analyzes the current situation of risk management and internal control of Moutai Group.It is found that the risk management of Moutai Group is not perfect,the information exchange is not smooth,and the internal control assessment is not perfect.Finally,it puts forward some corresponding countermeasures,including establishing an effective information communication mechanism,perfecting the risk assessment system,and strengthening the construction of the professional talent team.

Online payment fraud:from anomaly detection to risk management

Online banking fraud occurs whenever a criminal can seize accounts and transfer funds from an individual’s online bank account.Successfully preventing this requires the detection of as many fraudsters as possible,without producing too many false alarms.This is a challenge for machine learning owing to the extremely imbalanced data and complexity of fraud.In addition,classical machine learning methods must be extended,minimizing expected financial losses.Finally,fraud can only be combated systematically and economically if the risks and costs in payment channels are known.We define three models that overcome these challenges:machine learning-based fraud detection,economic optimization of machine learning results,and a risk model to predict the risk of fraud while considering countermeasures.The models were tested utilizing real data.Our machine learning model alone reduces the expected and unexpected losses in the three aggregated payment channels by 15%compared to a benchmark consisting of static if-then rules.Optimizing the machine-learning model further reduces the expected losses by 52%.These results hold with a low false positive rate of 0.4%.Thus,the risk framework of the three models is viable from a business and risk perspective.

Safety risk management of underground engineering in China：Progress, challenges and strategies

Underground construction in China is featured by large scale, high speed, long construction period,complex operation and frustrating situations regarding project safety. Various accidents have been reported from time to time, resulting in serious social impact and huge economic loss. This paper presents the main progress in the safety risk management of underground engineering in China over the last decade, i.e.（1） establishment of laws and regulations for safety risk management of underground engineering,（2） implementation of the safety risk management plan,（3） establishment of decision support system for risk management and early-warning based on information technology, and（4） strengthening the study on safety risk management, prediction and prevention. Based on the analysis of the typical accidents in China in the last decade, the new challenges in the safety risk management for underground engineering are identified as follows：（1） control of unsafe human behaviors;（2） technological innovation in safety risk management; and（3） design of safety risk management regulations. Finally, the strategies for safety risk management of underground engineering in China are proposed in six aspects, i.e. the safety risk management system and policy, law, administration, economy, education and technology.

Landslide susceptibility zonation method based on C5.0 decision tree and K-means cluster algorithms to improve the efficiency of risk management

Machine learning algorithms are an important measure with which to perform landslide susceptibility assessments, but most studies use GIS-based classification methods to conduct susceptibility zonation.This study presents a machine learning approach based on the C5.0 decision tree(DT) model and the K-means cluster algorithm to produce a regional landslide susceptibility map. Yanchang County, a typical landslide-prone area located in northwestern China, was taken as the area of interest to introduce the proposed application procedure. A landslide inventory containing 82 landslides was prepared and subsequently randomly partitioned into two subsets: training data(70% landslide pixels) and validation data(30% landslide pixels). Fourteen landslide influencing factors were considered in the input dataset and were used to calculate the landslide occurrence probability based on the C5.0 decision tree model.Susceptibility zonation was implemented according to the cut-off values calculated by the K-means cluster algorithm. The validation results of the model performance analysis showed that the AUC(area under the receiver operating characteristic(ROC) curve) of the proposed model was the highest, reaching 0.88,compared with traditional models(support vector machine(SVM) = 0.85, Bayesian network(BN) = 0.81,frequency ratio(FR) = 0.75, weight of evidence(WOE) = 0.76). The landslide frequency ratio and frequency density of the high susceptibility zones were 6.76/km^(2) and 0.88/km^(2), respectively, which were much higher than those of the low susceptibility zones. The top 20% interval of landslide occurrence probability contained 89% of the historical landslides but only accounted for 10.3% of the total area.Our results indicate that the distribution of high susceptibility zones was more focused without containing more " stable" pixels. Therefore, the obtained susceptibility map is suitable for application to landslide risk management practices.

Engineering complex systems applied to risk management in the mining industry

Related to complexity, there is a wide diversity of concepts, ranging from ‘‘systemic" to ‘‘complex", implying a need for a unified terminology. Per different authors, the main drivers of complexity can be found in human behaviour and uncertainty. This complexity, structural or dynamic can be organizational, technological, or nested in their relationship. ISO international standard 31000:2009 definition of risk management ‘‘coordinated activities to direct and control an organization with regard to risk", when applied to economic sectors, industry, services, project, or activity, it requires the use of models or theories as guidelines. Therefore, as its basic elements comprehend human behaviour and/or uncertainty, risk management to be effective and adapted as much as possible to reality, must be operational within complex systems, as already demonstrated in different R&D environments. Risk management faces demanding challenges when approaching specific and endogenous needs, such as the mining sector. This paper presents a multivariable function analysis methodology approach based on complex system modelling and through real data corresponding to a risk management tool in the mining sector.

The use of UAVs for landslide disaster risk research and disaster risk management: a literature review

On a global scale,from 2005 to 2019,there were 275 high-magnitude,low-frequency disasters that involved 14,172 fatalities and four million affected people.Similar patterns have taken place during longer periods of time in recent decades.This paper aims to analyse the contribution of the international landslide research community to disaster risk reduction and disaster risk management in reference to the use of Unmanned Aerial Vehicles(UAVs)in a literature review.The first section notes the relevance of disaster risk research contributions for the implementation of initiatives and strategies concerning disaster risk management.The second section highlights background information and current applications of drones in the field of hazards and risk.The methodology,which included a systematic peer review of journals in the ISI Web of Science and SCOPUS,was presented in the third section,where the results include analyses of the considered data.This study concludes that most current scholarly efforts remain rooted in hazards and post-disaster evaluation and response.Future landslide disaster risk research should be transdisciplinary in order to strengthen participation of the various relevant stakeholders in contributing to integrated disaster risk management at local,subnational,national,regional and global levels.

Managing Climate Change Risk in China's Agricultural Sector: The Potential for an Integrated Risk Management Framework

Climate change poses a serious threat to the future food security of China, which is among the most disaster-prone countries in the world. This paper discusses the implications of climate change for China＇s agricultural sector. Its main objectives are to identify the agricultural risks associated with climate change, to introduce a conceptual framework for agricultural climate risk management and to enumerate key adaptation strategies, challenges, and recommendations.

Risk Management of Key Issues of FPSO

Risk analysis of key systems have become a growing topic late of because of the development of offshore structures. Equipment failures of offioading system and fire accidents were analyzed based on the floating production, storage and offioading （FPSO） features. Fault tree analysis （FTA）, and failure modes and effects analysis （FMEA） methods were examined based on information already researched on modules of relex reliability studio （RRS）. Equipment failures were also analyzed qualitatively by establishing a fault tree and Boolean structure function based on the shortage of failure cases, statistical data, and risk control measures examined. Failure modes of fire accident were classified according to the different areas of fire occurrences during the FMEA process, using risk priority number （RPN） methods to evaluate their severity rank. The qualitative analysis of FTA gave the basic insight of forming the failure modes of FPSO offioading, and the fire FMEA gave the priorities and suggested processes. The research has practical importance for the security analysis problems of FPSO.

Systemic risk management and investment analysis with financial network analytics:research opportunities and challenges

Recent economic crises like the 2008 financial tsunami has demonstrated a critical need for better understanding of the topologies and various economic,social,and technical mechanisms of the increasingly interconnected global financial system.Such a system largely relies on the interconnectedness of various financial entities such as banks,firms,and investors through complex financial relationships such as interbank payment networks,investment relations,or supply chains.A network-based perspective or approach is needed to study various financial networks in order to improve or extend financial theories,as well as develop business applications.Moreover,with the advance of big data related technologies,and the availability of huge amounts of financial and economic network data,advanced computing technologies and data analytics that can comprehend such big data are also needed.We referred this approach as financial network analytics.We suggest that it will enable stakeholders better understand the network dynamics within the interconnected global financial system and help designing financial policies such as managing and monitoring banking systemic risk,as well as developing intelligent business applications like banking advisory systems.In this paper,we review the existing research about financial network analytics and then discuss its main research challenges from the economic,social,and technological perspectives.

Risk Management Concepts in Dam Safety Evaluation： Mosul Dam as a Case Study

Gradual shift has been observed lately of dam safety procedures from the conventional technical based towards a wider scope of risk management procedure based on risk analysis. The new approach considers the likelihood level of occurrence of a multitude of hazards and the magnitude of the resulting possible consequences in case of failure using rational cause and effect arguments. Most dam owners are shifting towards the use of the new risk based procedures; and even governments themselves are moving towards formalizing the new trend. Legislations in the United States were promulgated [1] after serious dam failures and the adoption of stringent levels of scrutiny led such federal dam owners to pioneer in this field and in developing the concepts and methods required. The comer stone in risk analysis is the definition of the potential modes that may lead to failure and assessment of the likelihood levels of their occurrence and possible category of the consequences which, after thorough evaluation, will shape the decision making. This type of analysis was applied to Mosul Dam as a case study and resulted in definite recommendations.

Analysis and evaluation of enterprise risk management capability elements

Research on enterprise risk management capability is conducted with a view of discerning and processing risks, in which an evaluation index system and an evaluation model of enterprise risk management capabilities are constructed. The risk management capability consists of four aspects, i.e. risk identification capability, risk assessment capability, risk planning capability and risk control capability. Risk identification and assessment capabilities reflect the level of enterprises on finding and analyzing risks efficiently, while risk planning and control capabilities reflect the level of enterprises on resolving risks effectively. Each of capabilities is then further divided into more detailed elements based on the characteristics of enterprise development for a quantitative analysis of enterprise risk management capability. The approach adopted is a quantitative technique based on the use of fuzzy comprehensive evaluation. Finally, a case is pulled in to illustrate the feasibility of the method from an empirical perspective. This study is expected to be helpful for enterprises in cultivating their core capabilities.

Implementation of a risk management plan in a hospital operating room

A risk management program based on ASeNZS4360 risk management standards was developed and implemented in the operating room of Peking University Third Hospital.To accomplish this task,we developed a risk quantification matrix and a risk register form to identify potential risks in the operating room,and then implemented operating room policies designed to reduce or eliminate those risks.We also established a consultation mechanism and risk monitoring system designed to minimize risks to operation room nurses.Finally,we continuously seek to improve our operating room risk management capabilities,so we can continue to improve the quality of service provided and guarantee the safety of surgical patients.

The Effect of the 2007/2008 Financial Crisis on Enterprise Risk Management Disclosure of Top US Banks

We document the effect of the 2007/2008 financial crisis on the volume and the quality of enterprise risk management （ERM） disclosure in the annual reports of the largest US banks, and analyze its determinants. Using a content analysis approach of the annual reports form 10-K for the years 2006, 2007, 2008, and 2009, we find that the ERM disclosure is significantly and positively associated with the crisis, bank size, board independence, duality and significantly and negatively associated with profitability, leverage, and board size. This paper seeks to fill a gap in the literature by investigating the effect of the crisis on ERM disclosure in the US banking sector context, and gives an insight into the factors affecting risk disclosure practices during the financial crisis.

Risk management in open cut coal mines

There are a number of geotechnical systems used at open cut operations of Anglo American's Metallurgical Coal business unit in Australia. These systems are mainly mine site specific, based on geological information and used as hazard plans. They are qualitative and reliant upon the experienced judgement of site based engineers and the general workforce. They are not suitable for calculating the associated risks of geological structures and mining responses. A uniform risk rating system that can be used to provide an unbiased, standard and quantifiable assessment of the risk from highwall and lowwall failures is therefore developed using the experience gained with such systems in Anglo American's South African operations. This system is a semi-quantitative risk rating system and takes into account the relative differences in the importance of hazards as experienced at each mine site as a result of different combinations of geotechnical factors and mining conditions. It is based on critical geotechnical and other parameters that have been identified by site mining engineers, geologists and geotechnical engineers. The primary advantage of this risk rating system is that all open cut mines in the Anglo American's Metallurgical Coal operations use a near identical system, which enables the user to compare the risk after each blast and with other mines. The system can be adjusted to meet local mine specific requirements. The implementation of this system, a computer program that automatically calculates the risks and recommends predetermined controls, has been made as practical and as easy to use as possible. This program can be used by personnel from other mining disciplines not directly related to geotechnical engineering.