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Finding an appropriate place for temporary housing after an earthquake is one of the main challenges of disaster risk management, especially in developing countries. Therefore, it is necessary to create pre-disaster location plans for the homeless population. This study aims to systematically find safe places and select suitable sites according to influential factors.

The research methodology used is a descriptive–analytical method. A field survey with a quantitative–qualitative approach is applied to recognize physical vulnerabilities and select suitable sites for temporary settlements. Due to the occurrence of several earthquakes in recent decades around the city of Isfahan, Iran, this area has been studied. Fuzzy analytic hierarchy process, geographic information system and rapid visual screening have been used for data analysis.

According to the site selection and vulnerability criteria and their prioritization, the findings indicate that 60% of the study area is vulnerable. Moreover, vacant lots, stadiums and public green spaces that can be used as multi-purpose sites are the most appropriate options for the temporary settlement.

The research criteria are generalizable and can be used for decision-making, concerning urban fabric vulnerability and site selection of temporary housing in cities exposed to earthquake risk.

Cultural features, accessibility, land conditions, the slope and type of land, availability and construction materials were addressed in locating temporary settlements. In addition to vacant lots and open spaces, safe buildings were also identified for temporary housing, and religious minorities and similar communities were considered.

Examine the effects of sudden environmental disasters on the advancement of both renewable and conventional energy technologies.

Utilizing panel data from 31 Chinese provinces spanning 2011 to 2022, the SEM (Spatial Error Model) dual fixed model is utilized to examine the impact of sudden environmental disasters on energy technologies.

The findings reveal that: (1) Sudden environmental disasters exert a markedly positive influence on the Innovation of Renewable Energy Technologies (IRET), while their impact on conventional energy technologies is positively non-significant. (2) Sudden environmental disasters not only significantly enhance innovation in local renewable energy technologies but also extend this positive influence to neighboring regions, demonstrating a spatial spillover phenomenon. (3) Research and Development (R&D) funding serves as a partial mediator in the relationship between sudden environmental disasters and renewable ETI. In contrast, Foreign Direct Investment (FDI) exhibits a masking effect.

Consequently, the study advocates for intensified efforts in post-disaster reconstruction following abrupt environmental events, an elevation in the quality of foreign direct investments, and leveraging research funding to catalyze innovation in renewable energy technologies amid unforeseen environmental crises.

Using critical disaster studies and state theory, we assess the disaster aid platform named Lebanon Reconstruction, Reform and Recovery Framework (3RF) that was put in place by international donors in the aftermath of the Beirut Port Blast in August 2020, in order to examine the effectiveness of its inclusive decision-making architecture, as well as its institutional building and legislative reform efforts.

The paper uses the case study approaach and relies on two original data sets compiled by authors, using desk reviews of academic literature and secondary data, in addition to 24 semi-structured expert interviews and participant observation for two years.

The aid platform appears innovative, participatory and effectively functioning toward recovery and reform. However, in practice, the government dismisses CSOs, undermines reforms and dodges state building, whereas the 3RF is structured in incoherent ways and operates according to conflicting logics, generating inertia and pitfalls that hinder effective participatory governance, prevent institutional building, and delay the making of projects.

The research contributes to critical scholarship as it addresses an important research gap concerning disaster aid platforms’ institutional design and governance that are under-studied in critical disaster studies and political studies. It also highlights the need for critical disaster studies to engage with state theory and vice-versa.

The research contributes to evaluations of disaster recovery processes and outcomes. It highlights the limits of disaster aid platforms’ claims for participatory decision-making, institutional-building and reforms.

The paper amplifies critical disaster studies, through the reflexive analysis of a case-study of an aid platform.

The most important need after natural disasters is the sheltering. However, most of the existing temporary shelters do not meet all requirements for long-term use and not provide adequate flexibility within the space. This paper aims to develop a transitional postdisaster shelter transforming from a closed shape to an expanded form in response to changing functional and spatial needs of disaster victims. The study also proposes alternative unit combinations for various functions, and settlement layouts to create a comfortable living environment for occupants.

The research methodology is based on theoretical and design frameworks which requires inductive and deductive approaches. Forming the background of the study, the theoretical framework consists of four parts which are literature review on temporary shelters presenting state-of-the-art; determination of design guidelines and strategies based on shelter standards; identification of technical requirements; and analysis of existing temporary shelters. Having three parts, the design framework includes design of transformable transitional shelter based on three-dimensional modeling, creation of different unit combinations to be used for various purposes and development of settlement layouts as case studies.

The analysis conducted in this study demonstrates that most of the existing temporary shelters have limited geometric configurations and major problems in terms of their performance, transportation and storage. On the other hand, the transformable shelter proposed by the authors can provide form and spatial flexibilities thanks to its expansion properties, occupy less space for transportation, easily be transported to any desired location in its compact state and be customized according to user needs. Several units can be combined either to serve larger families or to be used for different functions.

This paper contributes to the literature as presenting not only a theoretical framework on temporary shelters but also a design framework on transformable shelter design for the ones who are willing to develop similar transformable shelters based on the determined guidelines, strategies and requirements.

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 investigate barriers and enablers of social media usage by zooming on one specific type of domain: disaster management. First, by systematically reviewing previous studies using a typology to social media usage, this study identifies the challenges often faced. Second, the results are visualized by qualitatively analyzing the focus group discussion data.

This paper opted for an inductive thematic approach of grounded theory, including focus group discussion with ten participants from diverse backgrounds working in the disaster domain. The data is transcribed verbatim and coded using Atlas.ti software.

The findings suggest that the vogue of social media significantly ascends its usage in disaster management. Regulatory, software, physical, authenticity, cultural and demographic rose as challenges for social media usage in disaster management. Findings further indicate enablers as the rise in mobile penetration, democratic participation, increase in living standards, two-way real-time communication, global reach, expeditious decision-making, no space-time constraint and cheaper source of information. Social media, compared to traditional media, is explored. This study has practical implications in helping authorities understand the barriers and enablers for social media usage in disaster management.

Qualitative data analysis of social media usage for disaster management has received scant attention. The main takeaway of this research is to offer clear findings of the purview of social media usage for disaster management. It demonstrates the challenges and enablers of disaster management using social media in the Indian context. Results indicate that leveraging social media for disaster management can extend decision-making for effective disaster management.

The authors revisit the notion of co-production, highlight more critical and re-politicized forms of co-production and introduce three principles for its operationalization. The paper’s viewpoint aims to find entry points for enabling more equitable disaster research and actions via co-production.

The authors draw insights from the authors’ reflections as climate and disaster researchers and literature on knowledge politics in the context of disaster and climate change, especially within critical disaster studies and feminist political ecology.

Disaster studies can better contribute to disaster risk reduction via political co-production and situating local and Indigenous knowledge at the center through three principles, i.e. ensuring knowledge plurality, surfacing norms and assumptions in knowledge production and driving actions that tackle existing knowledge (and broader sociopolitical) structures.

The authors draw out three principles to enable the political function of co-production based on firsthand experiences of working with local and Indigenous peoples and insights from a diverse set of co-production, feminist political ecology and critical disaster studies literature. Future research can observe how it can utilize these principles in its respective contexts.

Pre-positioning and distributing relief items are important parts of disaster management as it simultaneously considers activities from both pre- and post-disaster stages. This study aims to address this problem with a novel mathematical model.

In this research, a bi-objective mixed-integer linear programming model is developed to tackle pre-positioning and distributing relief items, and it is formulated as an integrated location-allocation-routing problem with uncertain parameters. The humanitarian supply chain consists of relief facilities (RFs) and demand points (DPs). Perishable and imperishable relief commodities (RCs), different types of vehicles, different transportation modes, a time window for delivering perishable commodities and the occurrence of unmet demand are considered. A scenario-based game theory is applied for purchasing RCs from different suppliers and an integrated best-worst method-technique for order of preference by similarity to ideal solution technique is implemented to determine the importance of DPs. The proposed model is used to solve several random test problems for verification, and to validate the model, Iran’s flood in 2019 is investigated as a case study for which useful managerial insights are provided.

Managers can effectively adjust their preferences towards response time and total cost of the network and use sensitivity analysis results in their decisions.

The model locates RFs, allocates DPs to RFs in the pre-disaster stage, and determines the routing of RCs from RFs to DPs in the post-disaster stage with respect to minimizing total costs and response time of the humanitarian logistics network.

The built environment is responsible for approximately 40% of the world’s energy consumption, 30% of raw material use, 25% of solid waste, 25% of water use, 12% of land use and 33% of greenhouse gas emissions. Thus, environmental improvement and decarbonization are becoming increasingly critical objectives for the construction industry. Sustainable construction can be achieved through several practices, including: considering life-cycle assessment, circular construction, resource efficiency and waste management and providing eco-efficient materials, reducing energy demands and consumption and incorporating low-carbon technologies and renewable energy sources. To achieve sustainable construction goals, it is critical to educate the future workforce about decarbonization, circular construction and how to overcome the challenges involved in transitioning to sustainable construction. This study aims to understand the gap in student knowledge related to decarbonization and circular construction and the importance of incorporating these topics in civil engineering and construction management curricula.

This study surveyed 120 undergraduate and graduate students at one of the largest minority-serving institutions in the USA to understand the gap in student knowledge related to decarbonization and circular construction as well as the importance of incorporating these topics in civil engineering and construction management curricula. The authors conducted several statistical measures to assess the consistency, reliability and adequacy of the sample size, including the Kaiser–Meyer–Olkin measure of sampling adequacy, the normality test to evaluate the appropriateness of using an ordered probit regression analysis and a multicollinearity test to observe the correlation between independent variables. The data was analyzed using ordered probit regression analysis to investigate the need for a curriculum that serves in educating students about decarbonization and circular construction.

The results of this research highlight the gaps in students’ knowledge pertaining to sustainable practices and the importance of providing future construction workforce with such knowledge to tackle global inevitable challenges.

The findings of this study contribute to sustainable construction bodies of knowledge by advocating for a reformed curriculum to prepare the future workforce and adopt less carbonized, more circular approaches within the engineering and construction industry.

The objective of this study is to investigate the concept of “earthquake resistance” in high-rise buildings and assess the current level of structural strength in the areas where these structures are situated. The study aims to identify and implement necessary measures to enhance resilience in these areas. A comprehensive literature review was conducted to develop a conceptual framework focusing on earthquake resistance's meanings, stages and physical elements to achieve these goals.

This study focuses on Istanbul, a city known for its high earthquake risk, specifically targeting the Atasehir district. The research utilizes the DEMATEL (Decision-Making Trial and Evaluation Laboratory) method to evaluate urban resilience parameters. Additionally, the Fuzzy TOPSIS (Preference Ranking Technique by Similarity) method is employed to analyze the location of five buildings in Atasehir, using criterion weights derived from this methodology.

The findings indicate that resilience varies depending on the distance of the buffers. Moreover, the amount and quality of urban equipment in the study areas have a significant impact on the earthquake resistance level of the surrounding areas where high-rise buildings are situated. Building upon this analysis, the study suggests the implementation of measures aimed at augmenting the quantity and quality of urban facilities in the study areas, consequently enhancing urban resilience.

The originality and value of this study lie in its examination of seismic resilience within the context of high-rise buildings and the identification of necessary measures to increase resilience in areas where these structures are prevalent. By focusing on Istanbul, a city with a high earthquake risk, and specifically selecting the Atasehir district as the study area, this research provides a comprehensive conceptual framework for understanding urban resilience and its physical components. Moreover, the study offers a fresh perspective on urban resilience by highlighting the influence of tall buildings on the surrounding areas. Ultimately, it provides practical recommendations for architects, urban planners and other stakeholders to improve regional earthquake resilience.