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This study aims at investigating the evolution of disaster management by identifying the different phases it has gone through over time, and laying a ground for the next generation of disaster studies that focus on value-creating and value-adding activities.

An extensive review of the existing literature was made to develop an understanding of the evolution of disaster management. This study does not aim at assessing the tools or techniques used; rather it aims at identifying the major developments that took place over time.

Disaster management is a dynamic process. It has encountered/experienced different evolutionary phases that indicate that it has been developing over time. It continues to evolve until today as long as disasters occur. The nature and complexity of disasters are also changing. Most importantly, what seemed to be a practical approach for managing disasters yesterday might not fit for the use of today or tomorrow.

Understanding the evolution of disaster management mirrors the evolution of mankind and the ways people survived major incidents. As life itself evolves, disasters will continue to evolve which subsequently triggers the need for broader management insight to cope with.

This study traces the evolution of disaster management and the development of research and practice in this field over time. The existing literature rarely addresses the uniqueness of individual disasters and the need to treat them differently even the recurrent ones. To the best of the author’s knowledge, there is no single study that attempted to capture the evolution of disaster management during the 20th century until today. This study aims to achieve this goal.

The overall objective of this study is envisaged to provide decision makers with actionable insights and access to multi-risk maps for the most in-danger stave churches (SCs) among the existing 28 churches at high spatial resolution to better understand, reduce and mitigate single- and multi-risk. In addition, the present contribution aims to provide decision makers with some information to face the exacerbation of the risk caused by the expected climate change.

Material and data collection started with the consultation of the available literature related to: (1) SCs' conservation status, (2) available methodologies suitable in multi-hazard approach and (3) vulnerability leading indicators to consider when dealing with the impact of natural hazards specifically on immovable cultural heritage.

The paper contributes to a better understanding of place-based vulnerability with local mapping dimension also considering future threats posed by climate change. The results highlight the danger at which the SCs of Røldal, in case of floods, and of Ringebu, Torpo and Øye, in case of landslide, may face and stress the urgency of increasing awareness and preparedness on these potential hazards.

The contribution for the first time aims to homogeneously collect and report all together existing spread information on architectural features, conservation status and geographical attributes for the whole group of SCs by accompanying this information with as much as possible complete 2D sections collection from existing drawings and novel 3D drawn sketches created for this contribution. Then the paper contributes to a better understanding of place-based vulnerability with local mapping dimension also considering future threats posed by climate change. Then it highlights the danger of floods and landslides at which the 28 SCs are subjected. Finally it reports how these risks will change under the ongoing impact of climate change.

This research investigated the impacts of COVID-19 on construction enterprises and good practices adopted by the enterprises in reducing COVID-19 risks. The Sendai Framework (TSF) is widely accepted as a strategic roadmap to reduce disaster risks throughout the life cycle of a disaster. As such, with the aim of enhancing the resilience of Australian construction enterprises, the identified good practices were mapped with TSF priorities to consolidate COVID-19 risk reduction practices that can be adopted by Australian construction enterprises.

Case study research approach was used, and three case studies were conducted with small, medium and large construction enterprises. Small, medium and large enterprises were selected based on the Australian Bureau of Statistics classification of the business size. Data were collected through semi-structured interviews conducted with three executive members from the three enterprises. Data were analysed using content analysis.

The study found that construction enterprises faced demand and supply side impacts. Infrastructure projects, funded by public sector clients and larger enterprises were least affected. Investments and demand for residential and other building projects were reduced by private sector clients, affecting small and medium enterprises. Findings also show that the construction enterprises adopted good practices in identifying, managing, investing on resilience and recovery that align with TSF priorities. All three enterprises agreed on some common good practices on risk identification, risk management and effective recovery. Different views were shared on investments related to disaster resilience.

This study contributes to mitigate the COVID-19 impacts on construction enterprises and subsequent economic and social impacts.

This research found how Australian construction enterprises survived during COVID-19. The study adopted TSF to construction and COVID-19 context while consolidating COVID-19 risk reduction practices.

This conversation presents the reflections from five prominent disaster scholars and practitioners on the opportunities and challenges associated with research following disasters and explores the importance of ethics in disaster research.

This paper is based on the conversations that took place on Disasters: Deconstructed Podcast livestream on the 11th of June 2021.

The prominent themes in this conversation include ethical approaches to research, how we–as disaster researchers and practitioners–collaborate, engage, and cooperate, and whose voices are centred in a post-disaster research context.

The conversation contributes to ongoing discussions around the conduct and practice of disaster research.

This study aims to propose an analytical tool based on the activities–resources–actors (ARA) model to understand the coordination mechanisms in humanitarian action. The tool identifies the phases of humanitarian action and analyzes the underlying mechanisms that facilitate coordination among organizations.

This study uses a literature review to develop analytical grids and theoretical propositions based on the ARA model.

The ARA model is a useful tool for understanding coordination mechanisms in humanitarian action. The study identifies key elements of interaction systems and characterizes the phases of humanitarian action. Effective coordination among organizations is essential for successful aid delivery. The study provides four theoretical propositions.

Future research could validate the propositions formulated in this study through case studies.

The analytical grids proposed in this study can be used by humanitarian organizations to improve their coordination mechanisms and aid delivery processes.

Effective humanitarian action can help alleviate the suffering of individuals affected by crises and contribute to the overall well-being of communities. The analytical tool proposed in this study can improve the effectiveness of humanitarian action and ultimately benefit society.

This paper presents an original approach by leveraging the ARA model to develop an analytical tool for humanitarian action, which is useful for both practitioners and researchers. In addition, the paper attempts to overcome the siloed vision of humanitarian action by highlighting “emergency-development” aspect.

In recent years, due to fast growth of Kabul city in Afghanistan, newest construction has been taking place in unplanned ways and entailed illegal squatting on land and mountains. Such unplanned urban expansion, without any type of urban infrastructure and insufficient drainage systems, has created many problems including an increasing number of urban floods. Recent reports show that the number of female victims is higher than that of males affected by floods. First, this chapter highlights the country overview of the disaster and vulnerability, and then particularly focus on the vulnerability factors of urban women who are affected by floods and living in Kabul city. Data for this study were obtained through focus group discussions with urban women, and men and face-to-face interviews with governmental and non-governmental organizations (GOs-NGOs) at the local as well as national levels in Afghanistan. Interpretive Structural Modelling (ISM) was used to map the relationship among factors, and to stratify factors according to their importance. Findings show that the lack of education on disaster management and the lack of protective measures play an important role in increasing women’s vulnerability during disasters. Furthermore, the study finds that cultural issues represent a dominant vulnerability factor which affect women. The comparative results show that the women affected by the cultural norms during the flood are less important than the post-disaster. The study also found that the perception regarding these cultural norms and how they affect women’s behaviour during disasters differs between men and women. This chapter concluded some policy recommendations towards resilient livelihoods.

The paper reviews existing literature on South Asian ecosystem-based disaster risk reduction (DRR) and identifies how community participation can be used to plan and implement ecosystem-based DRR approaches.

The literature review methodology involved several stages. Firstly, the research objective was determined. Secondly keywords for the literature search were determined. Scopus, Google Scholar, JSTOR and AUT online library were utilized for the literature search. After the search, the literature was screened. The study design, methodology, results and limitations were identified and documented. After data extraction, the literature was analyzed. The patterns, trends and inconsistencies in the literature were identified based on the research question. Later the gaps, controversies and future research needs were identified. Then, a comprehensive and structured literature review that summarizes the relevant literature, synthesizes the findings and provides a critical evaluation of the literature was documented. After writing the document, it was reviewed and edited to ensure its clarity, accuracy and coherence.

The paper identifies four different themes recurrently emerging in literature on the importance of community participation in ecosystem-based DRR in South Asia. The themes are local community participation in ecosystem-based DRR governance, knowledge production, livelihood enhancement and increased public acceptance.

The paper also illustrates the challenges in integrating community participation with the dominant physical scientific approaches ecosystem-based DRR and proposes a five-element framework to facilitate the integration.

The COVID-19 pandemic has compelled higher educational institutions to implement alternative educational strategies that rely heavily on internet accessibility and utilisation to monitor and evaluate students. This study aims to find certain indicators for planning and designing future courses of inclusive online education in the domain of disaster risk reduction (DRR).

The study reviews and analyses online teaching and learning experiences of DRR courses. It uses online surveys and interviews to derive the perspectives of selected students and educators in universities in Asia and the Pacific region.

Active engagement is considered to be achieved when students are active in chat boxes, through presentations, through assignments and when the video cameras of students are turned on. On the contrary, students perceive active engagement differently because they face emotional disturbances and health issues due to prolonged screen/digital device use, have inadequate information and communications technology infrastructure or have digital literacy deficiencies among others. The study finds that online courses have many sets of strengths, weaknesses, opportunities and threats, when they are balanced, they can improve DRR courses in the future.

The study is based on the outcome of interviews with 10 experienced educators in DRR courses as well as students from different schools taking courses in DRR education. However, the students are not necessarily taking the courses of the educators interviewed due to the inability of some educators to avail themselves and the challenge of contacting the students. This notwithstanding, the results of this study give a general overview of the situation to be considered in the planning and design of online and distance education.

The results do not reflect the reaction of students and tutors of the same course. Future studies of collecting and analyzing the responses from the students and the educators with the same course could provide tailored solutions.

This study attempts to find solutions to bridging two different perspectives on teaching and learning. The results would be important to strengthening and designing future online courses.

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.