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As evacuation is one of the most used response actions to such disasters, it is essential to understand correctly what a resilient evacuation would mean. One critical factor in evacuation resilience is the resilience level of evacuation infrastructures. Also, UN sustainable development has a goal to build resilient infrastructures. This study aims to investigate the characteristics of resilient evacuation infrastructures.

A systematic methodology for reviewing articles has been implemented to understand how vulnerable cities can be more prepared, especially for pedestrian evacuation.

This study has developed an evacuation scoring system framework for pedestrians to investigate evacuation infrastructure in terms of different resilience features, such as redundancy, safe-to-fail, readiness and capacity. The most practical evacuation system will be estimated. The output of this study can provide insight into a final output to provide the features of a successful pedestrian evacuation system for future policy drafting for infrastructure strategy decision-makers.

Climate change has made the risks of natural hazards such as tsunamis more intense for humans. Many people in the world live in hazardous environments and are susceptible to disasters. A community must be prepared to mitigate the destructive event and quickly respond to be called resilient.

This is an original work. The researcher has gone through a deep literature review and developed a cluster showing the features a resilient evacuation infrastructure should have.

This study aims to provide an analysis and evaluation of infrastructure resilience, one of the components of disaster resilience, to natural hazards.

The analysis of this study consists of four stages. First, descriptive statistical analyses were carried out on the soft and hard infrastructure resilience and natural hazard index. Second, the spatial data were visualized through the exploratory spatial data analysis to understand the spatial distribution and spatial characteristics of variables of the data. Third, the local indicators of the spatial association method were used to identify areas in clusters where infrastructure resilience is weak. Fourth, comparisons were made between the soft and hard infrastructure resilience and natural hazard index: the level of natural hazard is high but the soft and infrastructure resilience remain very vulnerable to disaster.

The study found that infrastructure resilience varies from community to community, particularly in the same community, in terms of hard infrastructure and soft infrastructure. In addition, the comparative analysis between infrastructure resilience and disaster risk levels resulted in communities that were likely to suffer greatly in the event of a disaster.

This study is meaningful in that infrastructure resilience of Korean local governments was discussed by dividing them into soft and hard infrastructure and comparing them to natural disaster risk levels. In particular, the comparison with the natural disaster risk level identified local governments that are likely to experience significant damage from the natural disaster, which is meaningful in that it serves as a basis for policy practitioners to actively build infrastructure and respond to disasters.

By analyzing the mechanisms by which rural infrastructure resilience (RIR) impacted population loss in Longxi County, this study proposes measures to improve RIR, which provides a practical reference for realizing China's rural revitalization strategy, besides providing ideas for alleviating population loss in similar regions around the world.

This study considered 213 administrative villages in Longxi County in the Longzhong loess hilly region as the evaluation unit. Based on the construction of a multidimensional RIR evaluation system, the spatial spillover effect of RIR on population loss was determined using the spatial Durbin model (SDM).

The average resilience of each subsystem of rural infrastructure in Longxi County was low, and there were large differences in the spatial distribution. The mean RIR index value was 0.2258, with obvious spatial directivity and agglomeration characteristics. The population loss index of Longxi County had a value of 0.1759, with 26.29 of villages having a high loss level. The population loss was relatively serious and was correlated with the spatial distribution of RIR. The villages with larger RIR index values had lower population loss. The RIR had a significant spatial spillover effect on population loss. Productive infrastructure resilience and living infrastructure resilience (LIR) had negative spillover effects on population loss, and social service infrastructure resilience (SSIR) had a positive spillover effect on population loss.

By analyzing the mechanisms by which RIR impacted on population loss in Longxi County, this study proposes measures to improve RIR, which provides a practical reference for realizing China's rural revitalization strategy, besides providing ideas for alleviating population loss in similar regions around the world.

The purpose of this study is to undertake an evaluation of the resilient capacity of the infrastructure systems in the city of Wuhan. This evaluation focuses on the ability of the infrastructure to cope with extreme weather from multiple dimensions and to propose effective interventions against such risks.

This research draws on a review and synthesis of the theory of resilience and adopts the literature induction method to build an evaluation index for five urban systems, namely: roads; water supply and drainage; energy and power; urban disaster reduction; and communications. Index data from the period of 1990–2019 are combined with the views of experts from Wuhan and analyzed using principal component analysis (PCA) to calculate the weightings of the five urban systems. A fuzzy comprehensive evaluation method is then used to investigate the resilient capacity of these five urban infrastructure systems in the city.

Generally, the results show that the resilience of the infrastructure systems in Wuhan are at a high level. Based on the results, the communications and roads systems are found to have higher levels of resilience, while the disaster mitigation system is found to have a relatively low level of resilience. Recommendations are suggested to help improve resilience and prioritize investments in the development of the city's infrastructure systems.

The development of these specific indicators and quantitative requirements have not been studied in detail, so a more comprehensive, systematic evaluation of quantitative indicators and methods of urban infrastructure resilience is still required. In addition, the research on the resilience of urban infrastructure under extreme weather is still in its infancy, and it is essential to further increase the quantitative assessment of the resilience of urban infrastructure under construction. This will also be indispensable information in the subsequent implementation of a resilient planning process.

This research builds a rigorous and reliable evaluation model that avoids any subjective bias in the results and represents a new approach to evaluate the resilience of the infrastructure systems in the city of Wuhan, which could be applied to other cities.

The purpose of this paper is to explore the pathway toward operationalizing resilience in management of transportation infrastructure.

The research approach includes a comprehensive survey of the State Transportation Agencies (STA) in the USA. The information collected from the survey is analyzed using statistical analysis to explore the determinants of operationalizing resilience in transportation infrastructure management.

The results reveal that the current practices of STA need improvement in terms of pre-disaster vulnerability and exposure analysis as well as pre-disaster retrofit and betterment efforts. A pathway toward this end is identified with the major components being: funding availability, integration of efforts across different units, use of risk and vulnerability assessment approaches, and use of resilience indices.

The pathway, along with the other findings, enhances the understanding of the status quo, drivers, and barriers toward operationalizing resilience in transportation infrastructure management. Such an understanding is critical for infrastructure agencies to better adapt and enhance the resilience of their assets in response to various stressors such as the impacts of climate change as well as natural disasters.

The study presented in this paper is the first of its kind to identify the pathway toward operationalizing resilience in transportation infrastructure management.

The purpose of this study is to investigate the effect of gender differences in the perception of civil engineers and construction (CEC) students toward resilience to natural hazards and extreme events in a changing climate. This study also explores to what extent CEC students perceive the status of the US infrastructure systems similar to an external evaluation model (i.e. American Society of Civil Engineers Infrastructure Report Card).

An empirical study was conducted to examine the perception of resilience among 103 females and 279 male CEC students from 15 universities across the USA. The obtained data were quantified, and different statistical methods were used to explore the similarities and differences in the gender group responses.

The results indicated a significant mean difference (disagreement) between male and female groups in the importance of community resilience, management and handling of natural hazards. In addition, while there was no meaningful difference between female and male students in their content knowledge, female students showed a more accurate perception about impacting factors involved.

The findings of this study offer new insight into the impacts of gender differences in the perception of resilience, which can be used to enhance the educational experience of CEC female students in areas related to community and infrastructure resilience.

As the global freight transport network has experienced high vulnerability and threats from both natural and man-made disasters, as a result, a huge amount of data is generated in freight transport system in form of continuous streams; it is becoming increasingly important to develop sustainable and resilient transport system to recover from any unforeseen circumstances quickly and efficiently. The aim of this paper is to develop a stream processing data driven decision-making model for higher environmental performance and resilience in sustainable logistics infrastructure by using fifteen dimensions with three interrelated domains.

A causal and hierarchical stream processing data driven decision-making model to evaluate the impact of different attributes and their interrelationships and to measure the level of environmental performance and resilience capacity of sustainable logistics infrastructure are proposed. This work uses fuzzy cognitive maps (FCMs) and fuzzy analytic hierarchy process (FAHP) techniques. A real-life case under a disruptive event scenario is further conducted.

The result shows which attributes have a greater impact on the level of environmental performance and resilience capacity in sustainable logistics infrastructure.

In this paper, causal and hierarchical stream processing data decision and control system model was proposed by identified three domains and fifteen dimensions to assess the level of environmental performance and resilience in sustainable logistics infrastructure. The proposed model gives researchers and practitioners insights about sustainability trade-offs for a resilient and sustainable global transport supply chain system by enabling to model interdependencies among the decision attributes under a fuzzy environment and streaming data.

Resource allocation is essential to infrastructure management. The purpose of this study is to develop a methodological framework for resource allocation that takes interdependencies among infrastructure systems into consideration to minimize the overall impact of infrastructure network disruptions due to extreme events.

Taking advantage of agent-based modeling techniques, the proposed methodology estimates the interdependent effects of a given infrastructure failure which are then used to optimize resource allocation such that the network-level resilience is maximized.

The findings of the study show that allocating resources with the proposed methodology, where optimal infrastructure reinforcement interventions are implemented, can improve the resilience of infrastructure networks with respect to both direct and interdependent risks of extreme events. These findings are also verified by the results of two case studies.

As the two case studies have shown, the proposed methodological framework can be applied to the resource allocation process in asset management practices.

The proposed methodology improves the resilience of the infrastructure network, which can alleviate the social and economic impact of extreme events on communities.

Capitalizing on the combination of agent-based modeling and simulation-based optimization techniques, this study fulfills a critical gap in infrastructure asset management by incorporating infrastructure interdependence and resilience concepts into the resource allocation process.

Public–private partnership (PPP) has been adopted in many areas especially within the architecture, engineering and construction research domain. However, the PPP in critical infrastructure resilience (CIR) has not received the needed attention even though it has been acclaimed to be the panacea for building infrastructure resilience. This paper aims to adopt a systematic review to proactively identify the risks factors that pertains to using PPP as a mechanism to build the resilience of critical infrastructure.

Using a systematic methodology, a total record of 51 academic publications and 5 institutional reports from reputable organizations were identified and analyzed.

The selected literature was subjected to content analysis to retrieve 46 risk factors in PPP in CIR. The outcome of the systematic revealed the topmost risks as corruption, natural and unavoidable catastrophes, wars, terrorism, sabotage, cost overrun issues, a lack of centralized mechanism for coordinating integrated actions, inconsistent government policies, inadequate supervision, high operational cost due to robust and redundant measure, lack of supporting infrastructure, lack of open and integrated communication, unstable government, political interference, lack of PPP experience and legislation change. A conceptual framework was developed by grouping the identified risks under 13 categories.

The outcome of this study will be a guide for decision makers and stakeholders with the responsibility of building the resilience of critical infrastructure.

The study contributes to CIR research area by providing an in-depth knowledge on risks that are inherent in PPP in CIR.

Housing infrastructure is the basic need for people of a community and due to disaster many houses may severaly damaged. Stakeholders and decision makers should focus on this issue and make the infrastructure more resilient against natural hazards. As dependency plays a very important role in resilience, it is important to study the dependencies and correlations among the housing infrastructure resilience factors. The evaluation of dependencies involve vagueness due to subjective judgement of experts.

In this work, the interaction between the housing infrastructure resilience factors are evaluated by using two different approaches such as crisp DEMATEL (Decision-Making and Trial Evaluation Laboratory) and rough DEMATEL (intregated crisp DEMATEL and rough set theory), where rough theory addressed the involvement of vagueness. These two approaches are compared with each other to find the effectiveness of rough DEMATEL over crisp DEMATEL.

The important factors of housing infrastructure resilience are identified by using both the approaches against flood hazard.

The limitation of rough DEMATEL method is that it does not differentiate the type of influence such as positive or negative.

The outcome of the work will helps the stakeholders and ecission makers to make the infrastructure more resilient.

This study identify the imporatnat resilience factors of housing infrastructure against flood hazard by using two methodologies.