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The construction industry is an industry with a high incidence of safety accidents, and the interactions of unsafe behaviors of construction workers are the main cause of accidents. The neglect of the interactions may lead to serious underestimation of safety risks. This research aims to analyze the cascading vulnerability of unsafe behaviors of construction workers from the perspective of network modeling.

An unsafe behavior network of construction workers and a cascading vulnerability analysis model were established based on 296 actual accident cases. The cascading vulnerability of each unsafe behavior was analyzed based on the degree attack strategy.

Complex network with 85 unsafe behavior nodes is established based on the collected accidents in total. The results showed that storing in improper location, does not wear a safety helmet, working with illness and working after drinking are unsafe behaviors with high cascading vulnerability. Coupling analysis revealed that differentiated management strategies of unsafe behaviors should be applied. Besides, more focus should be put on high cascading vulnerability behaviors.

This research proposed a method to construct the cascading failure model of unsafe behavior for individual construction workers. The key parameters of the cascading failure model of unsafe behaviors of construction workers were determined, which could provide a reference for the research of cascading failure of unsafe behaviors. Additionally, a dynamic vulnerability research framework based on complex network theory was proposed to analyze the cascading vulnerability of unsafe behaviors. The research synthesized the results of dynamic and static analysis and found the key control nodes to systematically control unsafe construction behaviors.

The behavior of the entities in a small and medium-sized enterprise (SME) cooperation network is influenced by the core enterprise. Addressing the problem of how the network vulnerability changes when the core enterprise is attacked is a challenging topic. The purpose of this paper is to reveal the failure process of SME cooperation networks caused by the failure of the core SME from the perspective of cascading failure.

According to the Torch High Technology Industry Development Center, Ministry of Science & Technology in China, 296 SMEs in Jiangsu province were used to construct an SME cooperation network of technology-based SMEs and an under-loading cascading failure model. The weight-based attack strategy was selected to mimic a deliberate node attack and was used to analyze the vulnerability of the SME cooperation network.

Some important conclusions are obtained from the simulation analysis: (1) The minimum boundary of node enterprises has a negative relationship with networks' invulnerability, while the breakdown probability has an inverted-U relationship with networks' invulnerability. (2) The combined effect of minimum boundary and breakdown probability indicates that the vulnerability of networks is mainly determined by the breakdown probability; while, minimum boundary helps prevent cascading failure occur. Furthermore, according to the case study, adapting capital needs and resilience in the cooperation network is the core problem in improving the robustness of SME cooperation networks.

This research proposed an under-loading cascading failure model to investigate the under-loading failure process caused by the shortage of resources when the core enterprise fails or withdraws from the SME cooperation network. Two key parameters in the proposed model—minimum capacity and breakdown probability—could serve as a guide for research on the vulnerability of SME cooperation networks. Additionally, practical meanings for each parameter in the proposed model are given, to suggest novel insights regarding network protection to facilitate the robustness and vulnerability in real SME cooperation networks.

The purpose of this paper is to test the invulnerability of the guarantee network at the equilibrium point.

This paper introduces a tractable guarantee network model that captures the invulnerability of the network in terms of cascade-based attack. Furthermore, the equilibrium points are introduced for banks to determine loan origination.

The proposed approach not only develops equilibrium analysis as an extended perspective in the guarantee network, but also applies cascading failure method to construct the guarantee network. The equilibrium points are examined by simulating experiment. The invulnerability of the guarantee network is quantified by the survival of firms in the simulating progress.

There is less study in equilibrium analysis of the guarantee network. Additionally, cascading failure model is expressed in the presented approach. Moreover, agent-based model can be extended in generating the guarantee network in the future study.

The approach of this paper presents a framework to analyze the equilibrium of the guarantee network. For this, the systemic risk of the whole guarantee network and each node's contribution are measured to predict the probability of default on cascading failure. Focusing on cascade failure process based on equilibrium point, the invulnerability of the guarantee network can be quantified.

This paper proposes a method of probabilistic security analysis of power systems including protection system failures. Protection system failure is the main cause of cascading outages. A protection system reliability model including two major protection failure modes is adopted to demonstrate the effects of different protection failure modes on power system reliability. The mechanism and scheme of protection system have been analyzed for their contribution to cascading outages as well as system stability after a fault occurs. All contingencies and responses in the power system are depicted in their inherent stochastic manner. Therefore, all simulations in this paper contain the features of a real power system. Non‐sequential Monte Carlo simulation approach is used to implement the stochastic properties of component contingencies and protection system failures. The WSCC‐9 bus system is used as the security test system. The security index “probability of stability” is calculated to quantify the vulnerability of a power system under cascading outages.

This paper aims to provide a preliminary systemic portrayal of risk relationships in the context of critical infrastructures (CIs) during disasters and assess the adequacy of the Hyogo Framework in addressing such relationships and the resultant cascading effects.

Using a systems thinking approach, this study views CIs as complex systems operating in the context of broader societies and disaster conditions. Using a causal loop diagramming technique, relationships across a large number of variables are mapped to capture pathways for cascading effects across CIs. This theoretical understanding is supplemented by cascading effects seen during the 2011 Japanese disaster. The Hyogo Framework indicators are mapped both to causal variables and disaster events to identify gaps. Data on cascading effects were collected from journals, news articles and reports by governments and NGOs.

The Hyogo Framework does not address facilitation by the host country of international aid during disasters; identification of infrastructure interdependencies and prioritization planning for recovery operations; national risk assessments that account for interrelated disasters; and private sector’s need to understand CIs’ dependencies and establish robust continuity plans that account for potential infrastructure failures.

This paper is the first attempt to assess the Hyogo Framework’s potential in addressing risk relationships and cascading effects. The knowledge provided in the paper is derived from the synthesis of previous cascading effects’ literature and examination of a real-life disaster. Findings are applicable to any disaster risk reduction initiative that seeks to anticipate and mitigate risk relationships and their implications for CIs during disasters.

The purpose of this paper is to present a novel approach that examines the vulnerability and interdependency of critical infrastructures using the network theory in geographic information system (GIS) setting in combination with literature and government reports. Specifically, the objectives of this study were to generate the network models of critical infrastructure systems (CISs), particularly electricity, roads and sewerage networks; to characterize the CISs’ interdependencies; and to outline the climate adaptation (CA) and flood mitigation measures of CIS.

An integrated approach was undertaken in assessing the vulnerability and interdependency of critical infrastructures. A single system model and system-of-systems model were operationalized to examine the vulnerability and interdependency of the identified critical infrastructures in GIS environment. Existing CA and flood mitigation measures from government reports were integrated in the above-mentioned findings to better understand and gain focus in the implementation of natural disaster risk reduction (DRR) policies, particularly during the 2010/2011 floods in Queensland, Australia.

Using the results from the above-mentioned approach, the spatially explicit framework was developed with four key operational dimensions: conceiving the climate risk environment; understanding the critical infrastructures’ common cause and cascade failures; modeling individual infrastructure system and system-of-systems level within GIS setting; and integrating the above-mentioned results with the government reports to increase CA and resilience measures of flood-affected critical infrastructures.

While natural DRR measures include preparation, response and recovery, this study focused on flood mitigation. Temporal analysis and application to other natural disasters were also not considered in the analysis.

By providing this information, government-owned corporations, CISs managers and other concerned stakeholders will allow to identify infrastructure assets that are highly critical, identify vulnerable infrastructures within areas of very high flood risk, examine the interdependency of critical infrastructures and the effects of cascaded failures, identify ways of reducing flood risk and extreme climate events and prioritize DRR measures and CA strategies.

The individualist or “pigeon-hole” approach has been the common method of analyzing infrastructures’ exposure to flood hazards and tends to separately examine the risk for different types of infrastructure (e.g. electricity, water, sewerage, roads and rails and stormwater). This study introduced an integrated approach of analyzing infrastructure risk to damage and cascade failure due to flooding. Aside from introducing the integrated approach, this study operationalized GIS-based vulnerability assessment and interdependency of critical infrastructures which had been unsubstantially considered in the past analytical frameworks. The authors considered this study of high significance, considering that floodplain planning schemes often lack the consideration of critical infrastructure interdependency.

The system of critical infrastructure in the United States is vast in size and geographic layout. These two factors along with the American system of Federalism impose great challenges in protecting these systems. Much of the physical protection of these assets is left to state and local governments making protection more difficult is that a large number of these critical infrastructures are owned by multinational corporations. It is through a complex coordinated effort spanning across all three levels of government that these systems are kept secure in the United States.

This paper aims to present a novel approach for assessing the resilience of transportation road infrastructure against different failure scenarios based on the topological properties of the network. The approach is implemented in the context of developing countries where data scarcity is the norm, taking the capital city of Beirut as a case study.

The approach is based on the graph theory concepts and uses spatial data and urban network analysis toolbox to estimate the resilience under random and rank-ordering failure scenarios. The quantitative approach is applied to statistically model the topological graph properties, centralities and appropriate resilience metrics.

The research approach is able to provide a unique insight into the network configuration in terms of resilience against failures. The road network of Beirut, with an average nodal degree of three, turns to act more similarly to a random graph when exposed to failures. Topological parameters, connectivity and density indices of the network decline through disruptions while revealing an entire dependence on the state of nodes. The Beirut random network responds similarly to random and targeted removals. Critical network components are highlighted following the approach.

The approach is limited to an undirected and weighted specific graph of Beirut where the capacity to collect and process the necessary data in such context is limited.

Decision-makers are better able to direct and optimize resources by prioritizing the critical network components, therefore reducing the failure-induced downtime in the functionality.

The resilience of Beirut transportation network is quantified uniquely through graph theory under various node removal modes.

Systems thinking is holistic, that is it deals with wholes rather than parts and is relevant to tackling ill‐structured “messy” problems. Reviews the literature on risk to identify the techniques and concepts used in the management of risk and the identification of potential failures. The majority of the concepts identified are found to be systematic and reductionist. Also identifies related concepts not used in the techniques which are found to be more holistic. Classifies the concepts according to their use and holistic qualities. Briefly describes a systems approach to failures. As risk is associated with uncertainty and ill‐structured problems, suggests that systems thinking could be a valuable aid to risk management.