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.

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.

An Assessment of Procurement Risks Management Systems in the Public Sector

Risk management in public procurement is a critical aspect that needs to be addressed in the public sector.Several studies have been conducted to understand the challenges and factors influencing risk management in public procurement.These studies have explored the importance of risk management principles,the role of political influence,and the need for effective risk assessment and anticipation.The research has also highlighted the need for specific risk management mechanisms and tools to be implemented in public procurement processes.Risk management reforms in the public sector are essential but often circumvented due to assorted reasons,such as political influence and the emergence of new risks.The research investigation employs a quantitative research design.A total of 380 questionnaires were recovered from respondents.The study showed that the public sector has a procurement risk management system that is effective,but there may be some areas for improvement in the prequalification process,onboarding process,and support provided to newly onboarded suppliers.Additionally,the public sector used some strategies to mitigate and control contract risks during the procurement process,but there were some areas for improvement in the review and lessons learned process,risk mitigation measures,contract monitoring and performance evaluation mechanisms,and communication and documentation process.Finally,the results suggest that there were constraints placed on the risk management strategies currently utilized by professionals working in the public sector.These constraints include insufficient support and buy-in from senior management and stakeholders,bureaucratic or administrative hurdles,inadequate policies and regulations,insufficient training and skill development opportunities,and insufficient resources.The study highlights the significance of tackling risk management in the realm of public procurement and offers valuable perspectives on avenues for enhancement,obstacles encountered by practitioners,and the necessity of thorough evaluation and revisions.Through the adoption of the suggestions originating from this study,governmental entities can improve their procurement risk management frameworks and guarantee improved adherence to risk management principles.

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.

Climate change drives flooding risk increases in the Yellow River Basin

The Yellow River Basin(YRB)has experienced severe floods and continuous riverbed elevation throughout history.Global climate change has been suggested to be driving a worldwide increase in flooding risk.However,owing to insufficient evidence,the quantitative correlation between flooding and climate change remains illdefined.We present a long time series of maximum flood discharge in the YRB dating back to 1843 compiled from historical documents and instrument measurements.Variations in yearly maximum flood discharge show distinct periods:a dramatic decreasing period from 1843 to 1950,and an oscillating gentle decreasing from 1950 to 2021,with the latter period also showing increasing more extreme floods.A Mann-Kendall test analysis suggests that the latter period can be further split into two distinct sub-periods:an oscillating gentle decreasing period from 1950 to 2000,and a clear recent increasing period from 2000 to 2021.We further predict that climate change will cause an ongoing remarkable increase in future flooding risk and an∼44.4 billion US dollars loss of floods in the YRB in 2100.

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.

Exploring the impacts of major events on the systemic risk of the international energy market

This study examines the systemic risk caused by major events in the international energy market(IEM)and proposes a management strategy to mitigate it. Using the tail-event driven network(TENET)method, this study constructed a tail-risk spillover network(TRSN) of IEM and simulated the dynamic spillover tail-risk process through the cascading failure mechanism. The study found that renewable energy markets contributed more to systemic risk during the Paris Agreement and the COVID-19pandemic, while fossil energy markets played a larger role during the Russia-Ukraine conflict. This study identifies systemically important markets(SM) and critical tail-risk spillover paths as potential sources of systemic risk. The research confirms that cutting off the IEM risk spillover path can greatly reduce systemic risk and the influence of SM. This study offers insights into the management of systemic risk in IEM and provides policy recommendations to reduce the impact of shock events.

Conceptual Strategy for Mitigating the Risk of Hydrogen as an Internal Hazard in Case of Severe Accidents at Nuclear Power Plant Considering Existing Risks and Uncertainties Associated with the Use of Traditional Strategies

Hydrogen challenge mitigation stands as one of the main objectives in the management of severe accidents at Nuclear Power Plants (NPPs). Key strategies for hydrogen control include atmospheric inertization and hydrogen removal with Passive Autocatalytic Recombiners (PARs) being a commonly accepted approach. However, an examination of PAR operation specificity reveals potential inefficiencies and reliability issues in certain severe accident scenarios. Moreover, during the in-vessel stage of severe accident development, in some severe accident scenarios PARs can unexpectedly become a source of hydrogen detonation. The effectiveness of hydrogen removal systems depends on various factors, including the chosen strategies, severe accident scenarios, reactor building design, and other influencing factors. Consequently, a comprehensive hydrogen mitigation strategy must effectively incorporate a combination of strategies rather than be based on one strategy, taking into consideration the probabilistic risks and uncertainties associated with the implementation of PARs or other traditional methods. In response to these considerations, within the framework of this research it has been suggested a conceptual strategy to mitigate the hydrogen challenge during the in-vessel stage of severe accident development.

Risk Analysis of the Development of Sustainable Dongtan

Dongtan is set to be developed as a sustainable urban-rural integration,aiming to attract a wide range of commercial and leisure investments.The Shanghai Industrial Investment Corporation(SIIC),the largest international investment group owned by the Shanghai municipal government,is leading the Dongtan project in partnership with Arup.The project’s risks are categorized into eight major groups:(1)Force majeure,(2)people-related risks,(3)financial and economic risks,(4)political and country risks,(5)environmental risks,(6)completion-related risks,(7)design-related risks,and(8)technology risks.Among these,political risk is particularly notable for its high probability and significant impact.Effective project risk management is essential to foresee and address uncertainties that could jeopardize the project’s objectives and timelines.Appropriate strategies must be implemented to manage and mitigate these risks.

Analytic Hierarchy Process for Technological Risks in the Process of Innovative Drug Development in China

Objective To identify the critical risks in the process of innovative drug research and development,and to provide reference for improving the efficiency of innovative drug development and risk control in China.Methods Expert investigation and analytic hierarchy process were used to determine the weights of different risks.Results and Conclusion The research and analysis results showed that the risks at different stages of development had different effects on the success rate of drug development,among which the risk at the drug discovery stage influenced the most.In the drug discovery stage,inappropriate target selection had the greatest impact on the success rate of drug development.The lack of appropriate cell tissue or animal models had the greatest impact on the success rate of drug development from the discovery of a compound to the application for clinical trials.The difference in changes between nonclinical and clinical studies had the greatest impact on the success rate of drug development from early clinical studies to pivotal clinical studies.Incorrect dose selection had the greatest impact on the success rate of drug development from pivotal clinical studies to marketing authorization applications.The biggest impact from the marketing authorization application to the approval stage was inadequate communication with regulators.After investigating the weight of risk factors in the process of innovative drug development based on scientific methods,a new perspective for the risk control of new drug development and improving the research and development efficiency is provided.

Identifying and Managing Technical Risks in the Process of Innovative Drugs Development in China

Objective To identify technical risks in the process of innovative drug development,and to provide reference for technical risk management so as to reduce the uncertainties and improve the efficiency of research and development.Methods The initial risk index was investigated by literature research.Then,the Likert scale was used to design a questionnaire,and the experts’opinion was used to analyze the risk factors affecting the different stages of the development of innovative drugs in China.Results and Conclusion Based on the analysis of questionnaire,31 risk indicators of five key stages in the development of innovative drugs from drug discovery to marketing authorization were established.The key risk indicators constructed in this study can provide reference for technology-related risk management in the process of innovative drug development.

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.