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This paper investigates how agile capabilities in humanitarian settings work in combination, and its effects on performance outcome. The study was conducted in the frame of reference of response operations during cyclones and floods, which is considered most complex and with the most widespread impact.

A survey-based method was used to collect empirical data on response operations from 131 field officers who were involved in disaster response during cyclones or floods. A partial least square based structural equation model was used to study the path model of interaction of agile capabilities, and their effect on performance outcomes.

The results show that integration of agile capabilities is important for enhancing effectiveness of humanitarian response. The results indicated a serial mediation effect involving visibility, responsiveness and flexibility capability on the effectiveness of emergency response.

This research has implications for response units of humanitarian organisations. This includes capacity building for key agile capabilities, integration, supply chain re-configuration and differential positioning of response phase as against preparedness and recovery phases.

This study is unique for the chosen humanitarian setting, which is considered most difficult. The authors demonstrate from empirical evidence the interaction effects of agile capabilities during response phase for cyclones and floods, and their impact. The research insights will help practitioners to configure and position supply chains for better effectiveness during response operations, which have markedly different objectives vis-à-vis other phases or types of humanitarian settings.

In an era overshadowed by the alarming consequences of climate change and the escalating peril of recurring floods for communities worldwide, the significance of proficient disaster risk management has reached unprecedented levels. The successful implementation of disaster risk management necessitates the ability to make informed decisions. To this end, the utilization of three-dimensional (3D) visualization and Web-based rendering offers decision-makers the opportunity to engage with interactive data representations. This study aims to focus on Thiruvananthapuram, India, where the analysis of flooding caused by the Karamana River aims to furnish valuable insights for facilitating well-informed decision-making in the realm of disaster management.

This work introduces a systematic procedure for evaluating the influence of flooding on 3D building models through the utilization of Web-based visualization and rendering techniques. To ensure precision, aerial light detection and ranging (LiDAR) data is used to generate accurate 3D building models in CityGML format, adhering to the standards set by the Open Geospatial Consortium. By using one-meter digital elevation models derived from LiDAR data, flood simulations are conducted to analyze flow patterns at different discharge levels. The integration of 3D building maps with geographic information system (GIS)-based vector maps and a flood risk map enables the assessment of the extent of inundation. To facilitate visualization and querying tasks, a Web-based graphical user interface (GUI) is developed.

The efficiency of comprehensive 3D building maps in evaluating flood consequences in Thiruvananthapuram has been established by the research. By merging with GIS-based vector maps and a flood risk map, it becomes possible to scrutinize the extent of inundation and the affected structures. Furthermore, the Web-based GUI facilitates interactive data exploration, visualization and querying, thereby assisting in decision-making.

The study introduces an innovative approach that merges LiDAR data, 3D building mapping, flood simulation and Web-based visualization, which can be advantageous for decision-makers in disaster risk management and may have practical use in various regions and urban areas.

This study aims to review the features and challenges of the flood relief chain, identifies administrative measures during and after the flood occurrence and prioritizes them using two machine learning (ML) and analytic hierarchy process (AHP) methods. This paper aims to provide a prioritization program based on flood conditions that optimize flood management and improves society’s resilience against flood occurrence.

The collected database in this paper has been trained by using ML algorithms, including support vector machine (SVM), Naive Bayes (NB) and k-nearest neighbors (kNN), to create a prioritization program. Furthermore, the administrative measures in two phases of during and after the flood are prioritized by using the AHP method and questionnaires completed by experts and relief workers in flood management.

Among the ML algorithms, the SVM method was selected with 91.37% accuracy. The prioritization program provided by the model, which distinguishes it from other existing models, considers five conditions of the flood occurrence to prioritize actions (season, population affected, area affected, damage to houses and human lives lost). Therefore, the model presents a specific plan for each flood with different occurrence conditions.

The main limitation is the lack of a comprehensive data set to determine the effect of all flood conditions on the prioritization program and the relief activities that have been done in previous flood disasters.

The originality of this paper is the use of ML methods to prioritize administrative measures during and after the flood and presents a prioritization program based on each flood’s conditions. Therefore, through this program, the authority and society can control the adverse impacts of flood more effectively and help to reduce human and financial losses as much as possible.

This study aims to explain the existing adaptation practices in an urbanized sub-region in the lower Chao Phraya River basin (CPRB) across different scales and dimensions. It offers an overview of water hazards in urban areas along the river basin to discover ways to deal with and recover from hazards via understanding the implications of existing and potential practice for the mitigation of hydrological hazards.

First, this study collected current adaptation strategies and measures from interview, focus group discussion, workshop organization, etc. to get the current adaptation strategies/measures for the whole CPRB and each specific area. Second, this study identified a set of criteria for evaluation from review of current publications and official reports. Then, the current adaptation strategies/measures were examined through a set of criteria to obtain the current situation of existing practices. Finally, analysis of key challenges and opportunities was done to propose supporting guidelines to reduce hydrological risks and incorporate further adaptation measures needed to boost resilience in the area.

Adaptation methods should focus on mixed adaptation, which integrates structural, social, organizational and natural adaptation, and to develop multi-dimensional collaboration. The adaption strategy has restricted the usage of some technologies and technical know-how, particularly in the area of climate change. As a result, intentional adaptation to become more inventive is required, to reduce hazards and improve disaster-response capacity. The various adaptation measures should be more integrated or more adaptive and to achieve greater cohesion and mutual benefit of individual measures, such as community-based adaptation or community-driven slum upgrading.

Hydrological risks are wreaking havoc on social, economic and environmental elements, particularly river flood, flash flood and drought in the Asia-Pacific region. Twenty-two existing adaptation options were evaluated with evaluation criteria such as scales of risks/impacts reduction, benefits of environmental and socio-economic and institutional aspects. The findings highlight the current situation of existing practices, key challenges and opportunities, which emphasized on natural-based solutions, raising knowledge and awareness and lessons learned on adaptation of hydrological risks. The existing adaptation measures will be suggested as supporting guidelines and master plans to minimize the hydrological risks.

Tehran’s health-care system is growing, yet it lacks emergency planning procedures. The premise of this study is that the urban environment around a hospital is just as robust as the hospital itself. This study aims to look at hospital resilience in an urban setting to see where it may be improved to keep the hospital operational during a disaster.

The urban resilience (UR) of Amir-Alam Hospital was analyzed in this study using a customized version of the United Nations Office for Disaster Risk Reduction’s City Resilience Profiling Tool. The 34 indications were broken down into five categories.

The result revealed that the hospital’s UR score was 51.75 out of 100, indicating medium resilience. The results of this study enable the decision-makers to determine what measures they may take to improve the hospital’s resilience in terms of its surrounding urban context.

The originality of this research is based on the surrounding urban environment’s resilience as an integral part of hospital resilience.

This study explored whether the critical incident management systems (CIMS) model can predict the EMS performance in the COVID-19 context. Past research has established the significance of early detection and response (ER) in the context of Ebola virus disease (EVD), prompting a question of whether the model can also be helpful in the COVID-19 context. Consequently, the authors assessed whether ER influences the impact of communication capacity (CC), reliable information channel (RC) and environment (EN) on COVID-19 EMS performance. Assessing these relationships will advance emerging infectious disease (EID) preparedness.

The authors employed standardized measurement instruments of the CIMS model (CC, ER, RC and EN) to predict the performance of COVID-19 EMS using structural equation modeling (SEM) in a study of 313 participants from frontline responders.

The results show that the relationship of ER and EN with COVID-19 EMS performance is positive, while that of EN on CC is negative. The relationship between EN and COVID-19 EMS performance was insignificant. Contrary to the hypothesis, CC was negatively significant to COVID-19 EMS performance due to poor communication capacities.

The authors acknowledge some limitations due to challenges faced in this study. First, Data collection was a significant limitation as these questionnaires were built and distributed in June 2020, but the response time was prolonged due to the recurring nature of the pandemic. The authors had wanted to implore the inputs of all stakeholders, and efforts were made to reach out to various Ministry of Health, the local CDC and related agencies in the region via repeated emails explaining the purpose of the study to no avail. The study finally used the frontline workers as the respondents. The authors used international students from various countries as the representatives to reach out to their countries' frontline workers. Second, since the study was only partially supported using the CIMS model, future studies may combine the CIMS model with other models or theories. Subsequent research reassesses this outcome in other contexts or regions. Consequently, further research can explore how CC can be improved with COVID-19 and another future EID in the region. This may improve the COVID-19 EMS performance, thereby expanding the lesson learned from the pandemic and sustaining public health EID response. Additionally, other authors may combine the CIMS model with other emergency management models or theories to establish a fully supported theoretical model in the context of COVID-19.

The findings have practical implications for incident managers, local CDCs, governments, international organizations and scholars. The outcome of the study might inform these stakeholders on future direction and contribution to EID preparedness. This study unfolds the impact of lessons learned in the region demonstrated by moderating early detection and responses with other constructs to achieve COVID-19 EMS performance. The findings reveal that countries that experienced the 2013–2016 Ebola outbreak, were not necessarily more prepared for an epidemic or pandemic, judging by the negative moderating impact of early detection and response. However, these experiences provide a foundation for the fight against COVID-19. There is a need for localized plans tailored to each country's situation, resources, culture and lifestyle. The localized plan will be to mitigate and prevent an unsustainable EID management system, post-epidemic fund withdrawals and governance. This plan might be more adaptable and sustainable for the local health system when international interventions are withdrawn after an epidemic. Public health EID plans must be adapted to each country's unique situation to ensure sustainability and constantly improve EID management of epidemics and pandemics in emergency response. The high to moderate importation risk in African countries shows Africa's largest window of vulnerability to be West Africa (Gilbert et al., 2020). Therefore, they should be in the spotlight for heightened assistance towards the preparedness and response for a future pandemic like COVID-19. The West African region has a low capacity to manage the health emergency to match the population capacities. The COVID-19 outbreak in West Africa undoubtedly inflicted many disruptions in most countries' economic, social and environmental circumstances. The region's unique challenges observed in this study with CC and reliable information channels as being negatively significant highlight the poor maintenance culture and weak institutions due to brain drain and inadequate training and monitoring. This outcome practically informs West African stakeholders and governments on aspects to indulge when trying to improve emergency preparedness as the outcomes from other regions might not be applicable.

This study explored the relevance of the CIMS model in the context of the COVID-19 pandemic, revealing different patterns of influence on COVID-19 EMS performance. In contrast to the extant literature on EVD, the authors found the moderating effects of ER in the COVID-19 context. Thus, the authors contribute to the COVID-19 EMS performance domain by developing a context-driven EMS model. The authors discuss the theoretical and practical implications.

The survivorship of firms under extreme weather poses an essential question about the local economy's health. Over 90% of agricultural banks are categorized as community banks, which are important financial institutions promoting local growth. While previous studies suggest that climate change and weather shocks adversely impact community banks' resiliency, studies on whether these institutions engage in risk-reducing management strategies have been limited. In this study, the authors examine strategic choices of local community banks when facing flood events which include (1) safety net increase, (2) portfolio diversification, and (3) branch opening. These strategic choices are the coping mechanisms banks can take to survive while affecting the local competitive lending market.

The authors use panel-fixed effect regressions based on the storm data from National Oceanic and Atmospheric Administration (NOAA)'s National Weather Service (NWS) and the call reports from the Federal Deposit Insurance Corporation (FDIC). The authors focus on community banks' account variable characteristics and the number of offices to examine whether community banks take an active role in managing flood risk.

Results suggest that community banks do employ the selected strategic choices to a certain degree, as it is found that there is an increase in the core capital that absorbs shocks and portfolio diversification. However, the magnitudes of these activities are rather small and not large enough to fully mitigate the climate risk. Also, the authors do not find any evidence of branch expansion associated with local floods.

This study contributes to the literature by examining different strategic choices of community banks in the face of natural uncertainty. Even though concerns of climate risk have been raised in the regulatory setting, a lack of guidance or assessment tools could contribute to the passive action of these community banks, even though climate risks can have a significant economic impact. Thus, the evidence documented from this study calls for further guidelines and the importance of highlighting climate risks on community banks so that they can actively engage in risk-reducing strategies.

This paper aims to clarify the resistance degree of group road logistics to flood disaster resilience. The paper measures the resilience of group road logistics by establishing network structure model. The purpose of this study is to improve the resilience of road log.

This paper adopts Delphi method to collect data, interviews mainly flood management experts and supply chain risk management experts, and then analyzes the data through the network structure model combined with interpretative structure model (ISM) and analytical network process (ANP).

The results show that flood frequency and drainage systems are the main factors affecting the resilience of road transport logistics in urban areas. These research results provide useful guidance for the effective planning and design of urban road construction and infrastructure.

However, the main factors affecting the resilience of road transport logistics are likely to change with the development of factors such as climate, economy and environment. Therefore, in future work, the authors' research will focus on the further application of this evaluation method.

The results show that the impact of flooding on the four dimensions of road logistics resilience varies. This shows that in deciding what intervention measures are to be taken to improve the resilience of the road network to flooding, various measures need to be considered.

This paper provides a more scientific analysis of the risk management ability of the road network in the face of floods. In addition, it also provides a useful reference for urban road planners.

This paper addresses a clear need to study how to build models to improve the resilience of road logistics in flood risk.

This study aims to predict the consequences associated with the propagation of the flood wave that may occur after the failure of the Taksebt dam and suggest an efficient emergency action plan for mitigation purposes.

To achieve the objectives of this study, the hydrodynamic model HEC-RAS 2D was used for the flood routing of the dam-break wave, which gave an estimate of the hydraulic characteristics downstream the Taksebt dam.

Geospatial analysis of the simulation results conducted in a geographic information system (GIS) environment showed that many residential areas are considered to be in danger in case of the Taksebt dam-break event. Based on the obtained results, an emergency actions plan was suggested to moderate the causalities in the downstream area at risk.

Overall, this study showed that the integration of 2D hydraulic modeling and GIS provides great capabilities in providing realistic view of the dam-break wave propagation that enhances assessing the associated risks and proposing appropriate mitigation measures.

Due to the unknown location, size and timing of disasters, the rapid response required by humanitarian operations (HO) faces high uncertainty and limited time to raise funds. These harsh realities make HO challenging. This study aims to systematically capture the complex dynamic relationships between operations in humanitarian settings.

To achieve this goal, the authors undertook a systematic review of the extant academic literature linking HO to system dynamics (SD) simulation.

The research reviews 88 papers to propose a taxonomy of different topics covered in the literature; a framework represented through a causal loop diagram (CLD) to summarise the taxonomy, offering a view of operational activities and their linkages before and after disasters; and a research agenda for future research avenues.

As the authors provide an adequate representation of reality, the findings can help decision makers understand the problems faced in HO and make more effective decisions.

While other reviews on the application of SD in HO have focused on specific subjects, the current research presents a broad view, summarising the main results of a comprehensive CLD.