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In order to solve the problem of inaccurate calculation of index weights, subjectivity and uncertainty of index assessment in the risk assessment process, this study aims to propose a scientific and reasonable centralized traffic control (CTC) system risk assessment method.

First, system-theoretic process analysis (STPA) is used to conduct risk analysis on the CTC system and constructs risk assessment indexes based on this analysis. Then, to enhance the accuracy of weight calculation, the fuzzy analytical hierarchy process (FAHP), fuzzy decision-making trial and evaluation laboratory (FDEMATEL) and entropy weight method are employed to calculate the subjective weight, relative weight and objective weight of each index. These three types of weights are combined using game theory to obtain the combined weight for each index. To reduce subjectivity and uncertainty in the assessment process, the backward cloud generator method is utilized to obtain the numerical character (NC) of the cloud model for each index. The NCs of the indexes are then weighted to derive the comprehensive cloud for risk assessment of the CTC system. This cloud model is used to obtain the CTC system's comprehensive risk assessment. The model's similarity measurement method gauges the likeness between the comprehensive risk assessment cloud and the risk standard cloud. Finally, this process yields the risk assessment results for the CTC system.

The cloud model can handle the subjectivity and fuzziness in the risk assessment process well. The cloud model-based risk assessment method was applied to the CTC system risk assessment of a railway group and achieved good results.

This study provides a cloud model-based method for risk assessment of CTC systems, which accurately calculates the weight of risk indexes and uses cloud models to reduce uncertainty and subjectivity in the assessment, achieving effective risk assessment of CTC systems. It can provide a reference and theoretical basis for risk management of the CTC system.

The occupational health risk associated with the production of prefabricated concrete components is often overlooked. This paper will use a damage assessment and cyclic mitigation (DACM) model to provide individualized exposure risk assessment and corresponding mitigation management measures for workers who are being exposed.

The DACM model is proposed based on the concept of life cycle assessment (LCA). The model uses Monte-Carlo simulation for uncertainty risk assessment, followed by quantitative damage assessment using disability-adjusted life year (DALY). Lastly, sensitivity analysis is used to identify the parameters with the greatest impact on health risks.

The results show that the dust concentration is centered around the mean, and the fitting results are close to normal distribution, so the mean value can be used to carry out the calculation of risk. However, calculations using the DACM model revealed that there are still some work areas at risk. DALY damage is most severe in concrete production area. Meanwhile, the inhalation rate (IR), exposure duration (ED), exposure frequency (EF) and average exposure time (AT) showed greater impacts based on the sensitivity analysis.

Based on the comparison, the DACM model can determine that the potential occupational health risk of prefabricated concrete component (PC) factory and the risk is less than that of on-site construction. It synthesizes field research and simulation to form the entire assessment process into a case-base system with the depth of the cycle, which allows the model to be continuously adjusted to reduce the occupational health damage caused by production pollution exposure.

Businesses are increasingly vulnerable and exposed to physical climate change risks, which can cascade through local, national and international supply chains. Currently, few methodologies can capture how physical risks impact businesses via the supply chains, yet outside the business literature, methodologies such as sustainability assessments can assess cascading impacts.

Adopting a scoping review framework by Arksey and O'Malley (2005) and the PRISMA extension for scoping reviews (PRISMA-ScR), this paper reviews 27 articles that assess climate risk in supply chains.

The literature on supply chain risks of climate change using quantitative techniques is limited. Our review confirms that no research adopts sustainability assessment methods to assess climate risk at a business-level.

Alongside the need to quantify physical risks to businesses is the growing awareness that climate change impacts traverse global supply chains. We review the state of the literature on methodological approaches and identify the opportunities for researchers to use sustainability assessment methods to assess climate risk in the supply chains of an individual business.

Consumers increasingly rely on organisations for online services and data storage while these same institutions seek to digitise the information assets they hold to create economic value. Cybersecurity failures arising from malicious or accidental actions can lead to significant reputational and financial loss which organisations must guard against. Despite having some critical weaknesses, qualitative cybersecurity risk analysis is widely used in developing cybersecurity plans. This research explores these weaknesses, considers how quantitative methods might address the constraints and seeks the insights and recommendations of leading cybersecurity practitioners on the use of qualitative and quantitative cyber risk assessment methods.

The study is based upon a literature review and thematic analysis of in-depth qualitative interviews with 16 senior cybersecurity practitioners representing financial services and advisory companies from across the world.

While most organisations continue to rely on qualitative methods for cybersecurity risk assessment, some are also actively using quantitative approaches to enhance their cybersecurity planning efforts. The primary recommendation of this paper is that organisations should adopt both a qualitative and quantitative cyber risk assessment approach.

This work provides the first insight into how senior practitioners are using and combining qualitative and quantitative cybersecurity risk assessment, and highlights the need for in-depth comparisons of these two different approaches.

In the evolution process of building construction accidents, there are key nodes of risk change. This paper aims to quickly identify the key nodes and quantitatively assess the node risk. Furthermore, it is essential to propose risk accumulation assessment method of building construction.

Authors analyzed 419 accidents investigation reports on building construction. In total, 39 risk factors were identified by accidents analysis. These risk factors were combined with 245 risk evolution chains. Based on those, Gephi software was used to draw the risk evolution network model for building construction. Topological parameters were applied to interpret the risk evolution network characteristic.

Combining complex network with risk matrix, the standard of quantitative classification of node risk level is formulated. After quantitative analysis of node risk, 7 items of medium-risk node, 3 items of high-risk node and 2 items of higher-risk nodes are determined. The application results show that the system risk of the project is 44.67%, which is the high risk level. It can reflect the actual safety conditions of the project in a more comprehensive way.

This paper determined the level of node risk only using the node degree and risk matrix. In future research, more node topological parameters that could be applied to node risk, such as clustering coefficients, mesoscopic numbers, centrality, PageRank, etc.

This article can quantitatively assess the risk accumulation of building construction. It would help safety managers could clarify the system risk status. Moreover, it also contributes to reveal the correspondence between risk accumulation and accident evolution.

This study comprehensively considers the likelihood, consequences and correlation to assess node risk. Based on this, single-node risk and system risk assessment methods of building construction systems were proposed. It provided a promising method and idea for the risk accumulation assessment method of building construction. Moreover, evolution process of node risk is explained from the perspective of risk accumulation.

The purpose of this paper is to develop a novel integrated risk assessment method from the system perspective to evaluate the risk of the cross-regional mega construction project (CMCP). Furthermore, this paper aims to confirm the core risk source factors and refine the risk management strategies of CMCPs through a case study.

Based on the analysis of the risk system of CMCPs, the concept model and risk assessment principles of integrated risk assessment were confirmed. The risk source factors and project objectives of the CMCP were identified from a literature review, export interview and case analysis. According to the vulnerability theory, the integrated risk assessment model was developed by involving vulnerabilities, threats, objectives and interaction of those factors synthetically. Then, ZW high-speed railway from China was analyzed to verify the feasibility and effectiveness of the proposed method.

As a result, 12 threat factors and 12 vulnerability factors were identified. Based on the case study, the main external threat comes from T13 (conflicts of interest between local governments) and T23 (harsh natural environment); the most easily exploited internal vulnerabilities were V11 (complexity of technology), V13 (lack of experience in technical application), V21 (inadequate experience) and V23 (lack of interest coordination mechanism). Moreover, the economic objective was most affected.

It is essential to develop an interest coordination mechanism for CMCPs. The harsh natural environment is a critical factor, but it also promotes technological innovation and iteration. Public opinions in different regions are critical for CMCPs, and more emphasis should be placed on public opinion surveys of CMCPs. Moreover, diverse and flexible environmental protection strategies should apply in CMCPs.

This research has the following three contributions. First, based on vulnerability theory, an integrated risk assessment approach of CMCPs is developed, which enriches the risk measurement method system and provides inspiration for future research on risk in the construction industry. Second, the risk sources of CMCPs are identified from the perspective of vulnerability and threat to provide clear guidance for the risk management of CMCPs. Third, the core risk source factors and management strategies confirmed by the case study will be beneficial for various governments in different regions and project managers to optimize the project management scheme, as they are transferable management experiences.

Floods have been identified as the most frequent and threatening disaster in Sri Lanka amidst an increasing trend of natural and man-made disasters in the world. Subject experts state that disaster risk management should be based on the results of risk assessments, but flood risk management in Sri Lanka is seemingly not based on community-level flood risk assessments. Accordingly, the purpose of this paper is to introduce a community-level flood risk assessment method to the local context of Sri Lanka.

The sample (n = 425) for the study was selected using the stratified random sampling method, and the Deduru Oya basin was selected as the study area. The risk assessment model introduced by Bollin et al. (2003) was used for the current study, but with some modifications. Accordingly, 16 variables were selected for the risk assessment. Descriptive data analysis methods were used in the study.

Community-level flood risk assessment method was introduced. Variable index, flood risk index and flood risk map were developed for the study area. The Grama Niladari Divisions (GNDs) were grouped into five categories from very high risk to very low risk. The GNDs named Wirakumandaluwa, Thimbilla, Deduru Oya, Bangadeniya and Elivitiya were ranked as the most flood-risk GNDs, respectively.

This paper produces a flood risk assessment method for the local context. Flood risk in the study area was assessed based on people’s perceptions. Accordingly, the flood risk index and flood risk map for the study area were developed based on the empirical data. GNDs were ranked based on the flood risk index.

The complex network structure causes several disruptions in the supply chain that make risk management essential for supply chain management including halal supply chain (HSM). During risk management, several challenges are associated with the risk assessment phase, such as incomplete and uncertain information about the system. To cater this, the authors propose a risk assessment framework that addresses the issues of uncertainty using neutrosophic theory and demonstrated the applicability of the proposed framework through the case of halal supply chain management (HSCM).

The proposed framework is using the capabilities of the neutrosophic number which can handle uncertain, vague and incomplete information. Initially, the risk related to the HSC is identified through a literature review and expert’s input. Further, the probability and impact of each HSM-related risk are assessed using experts’ input through linguistic terms. These linguistic values are transformed into single-value trapezoidal neutrosophic numbers (SVTNNs). Finally, the severity of each HSM-related risk is determined through the multiplication of the probability and impact of each risk and prioritised the risks based on their severity.

A comprehensive risk assessment framework is developed that could be used under uncertainty. Initially, 16 risks are identified related to the HSM. Further, the identified risks are prioritised using the severity of the risks. The high-priority risk is “raw material status”, “raw material wholesomeness” and “origin of raw material” while “information integrity” and “people integrity” are low-priority risks.

HSM risk can be effectively assessed through the proposed framework. The proposed framework applied neutrosophic numbers to represent real-life situations, and it could be used for other supply chains as well.

The proposed method is effectively addressing the issue of linguistic subjectivity, inconsistent information and uncertainty in the expert’s opinion. A case study of the HSC is adopted to illustrate the efficiency and applicability of the proposed risk framework.

The numerous spoil grounds brought about by mega transportation infrastructure projects which can be influenced by the ecological environment. To achieve better management of spoil grounds, this paper aims to assess their comprehensive risk levels and categorize them into different categories based on ecological environmental risks.

Based on analysis of the environmental characteristics of spoil grounds, this paper first comprehensively identified the ecological environmental risk factors and developed a risk assessment index system to quantitatively describe the comprehensive risk levels. Second, this paper proposed a comprehensive model to determine the risk assessment and categorization of spoil ground group in mega projects integrating improved projection pursuit clustering (PPC) method and K-means clustering algorithm. Finally, a case study of a spoil ground group (includes 50 spoil grounds) in a mega infrastructure project in western China is presented to demonstrate and validate the proposed method.

The results show that our proposed comprehensive model can efficiently assess and categorize the spoil grounds in the group based on their comprehensive ecological environmental risk. In addition, during the process of risk assessment and categorization of spoil grounds, it is necessary to distinguish between sensitive factors and nonsensitive factors. The differences between different categories of spoil grounds can be recognized based on nonsensitive factors, and high-risk spoil grounds which need to be focused more on can be identified according to sensitive factors.

This paper develops a comprehensive model of risk assessment and categorization of a group of spoil grounds based on their ecological environmental risks, which can provide a reference for the management of spoil grounds in mega projects.

The need for infrastructure is growing as urbanization picks up speed, and the infrastructure REITs financing model has been crucial in reviving the vast infrastructure stock, alleviating the pressure on government funds and diversifying investment entities. This study aims to propose a framework to better assess the risks of infrastructure REITs, which can serve for the researchers and the policy makers to propose risk mitigation strategies and policy recommendations more purposively to facilitate successful implementation and long-term development of infrastructure REITs.

The infrastructure REITs risk evaluation index system is established through literature review and factor analysis, and the optimal comprehensive weight of the index is calculated using the combination weight. Then, a risk evaluation cloud model of infrastructure REITs is constructed, and experts quantify the qualitative language of infrastructure REITs risks. This paper verifies the feasibility and effectiveness of the model by taking a basic REITs project in China as an example. This paper takes infrastructure REITs project in China as an example, to verify the feasibility and effectiveness of the cloud evaluation method.

The research outcome shows that infrastructure REITs risks manifest in the risk of policy and legal, underlying asset, market, operational and credit. The main influencing factors in terms of their weights are tax policy risk, operation and management risk, liquidity risk, termination risk and default risk. The financing project is at a higher risk, and the probability of risk is 64.2%.

This research contributes to the existing body of knowledge by supplementing a set of scientific and practical risk evaluation methods to assess the potential risks of infrastructure REITs project, which contributes the infrastructure financing risk management system. Identify key risk factors for infrastructure REITs with underlying assets, which contributes to infrastructure REITs project management. This research can help relevant stakeholders to control risks throughout the infrastructure investment and financing life cycle, provide them with reference for investment and financing decision-making and promote more sustainable and healthy development of infrastructure REITs in developing countries.