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This study aims to propose a novel deep learning (DL)-based framework, iRelevancy, for identifying the disaster relevancy of a social media (SM) message.

It is worth mentioning that a fusion-based DL model is introduced to objectively identify the relevancy of a SM message to the disaster. The proposed system is evaluated with cyclone Fani data and compared with state-of-the-art DL models and the recent relevant studies. The performance of the experiments is assessed by the accuracy, precision, recall, f1-score, area under receiver operating curve and precision–recall curve score.

The iRelevancy leads to a better performance in accuracy, precision, recall, F-score, the area under receiver operating characteristic and area under precision-recall curve, compared to other state-of-the-art methods in the literature.

The predictive performance of the proposed model is illustrated with experimental results on cyclone Fani data, along with misclassifications. Further, to analyze the performance of the iRelevancy, the results on other cyclonic disasters, i.e. cyclone Titli, cyclone Amphan and cyclone Nisarga are presented. In addition, the framework is implemented on catastrophic events of different natures, i.e. COVID-19. The research study can assist disaster managers in effectively maneuvering disasters during distress.

This paper aims to propose DisDSS: a Web-based smart disaster management (DM) system for decision-making that will assist disaster professionals in determining the nature of disaster-related social media (SM) messages. The research classifies the tweets into need-based, availability-based, situational-based, general and irrelevant categories and visualizes them on a web interface, location-wise.

It is worth mentioning that a fusion-based deep learning (DL) model is introduced to objectively determine the nature of an SM message. The proposed model uses the convolution neural network and bidirectional long short-term memory network layers.

The developed system leads to a better performance in accuracy, precision, recall, F-score, area under receiver operating characteristic curve and area under precision-recall curve, compared to other state-of-the-art methods in the literature. The contribution of this paper is three fold. First, it presents a new covid data set of SM messages with the label of nature of the message. Second, it offers a fusion-based DL model to classify SM data. Third, it presents a Web-based interface to visualize the structured information.

The architecture of DisDSS is analyzed based on the practical case study, i.e. COVID-19. The proposed DL-based model is embedded into a Web-based interface for decision support. To the best of the authors’ knowledge, this is India’s first SM-based DM system.

The purpose of this study is to analyze the operations and performance dynamics of a supply chain (SC) subject to disruptions. The preparedness of Moroccan responders in handling emergencies could be enhanced significantly, by devising digital twin-based decision support systems (DSSs).

The authors create a discrete-event simulation model to investigate proactively risks and resilience of a Moroccan basic-items SC (BISC). In this study, the authors analyze the effects of catastrophe-related disruptions (CRDs) on the Moroccan BISC, by the use of a simulation-based decision-supporting quantitative method.

In the disruption-free simulation experiment, the outcome was a satisfactory 100% coverage. By implementing CRDs, inventory levels have dropped, service levels decreased, lead time raised and there was an increase in backlogged products and late orders numbers. The highest impact was observed for the shutdown of paths linking suppliers to warehouses, whereas the increase in demand had a comparatively minor effect. The risk analysis approach helps to identify critical products for which the time-to-recover is longer and requires more commitment to enhance their resilience.

The model serves to deduce quantitative resilience assessment from simulation, streamline the selection of recovery strategies and enable the best-informed reactive decision-making to minimize the impact.

The research brings organizing solutions to catastrophe-related emergencies in Morocco. It would contribute significantly by visualizing, examining and unveiling the effects of disruptions on a BISC and offering actionable recommendations for remedial measures.

This study aims to examine the current state of academic research pertaining to the role played by artificial intelligence (AI) in the achievement of a critical sustainable development goal (SDG) – poverty alleviation and describe the field’s development by identifying themes, trends, roadblocks and promising areas for the future.

The authors analysed a corpus of 253 studies collected from the Scopus database to examine the current state of the academic literature using bibliometric methods.

This paper identifies and analyses key trends in the evolution of this domain. Further, the paper distils the extant literature to unpack the intermediary mechanisms through which AI and related technologies help tackle the critical global issue of poverty.

The corpus of literature used for the analysis is limited to English language studies from the Scopus database. The paper contributes to the extant research on AI for social good, and more broadly to the research on the value of emerging technologies such as AI.

Policymakers and government agencies will get an understanding of how technological interventions such as AI can help achieve critical SDGs such as poverty alleviation (SDG-1).

The primary focus of this paper is on the role of AI-related technological interventions to achieve a significant social objective – poverty alleviation.

To the best of the authors’ knowledge, this is the first study to conduct a comprehensive bibliometric analysis of a critical research domain such as AI and poverty alleviation.

The purpose of this article is to identify the role of cloud computing services in business continuity and disaster recovery plans and delineate responsibilities for their execution. In recent times, there has been a huge upsurge in the usage of cloud service models such as infrastructure-as-a-service, platform-as-a-service, software-as-a-service and disaster recovery-as-a-service. However, in case of an emergency event or during contract negotiations, a question might arise as to who should be accountable and responsible for the content and execution of recovery plans. The main stakeholders in this scenario are cloud service providers and cloud consumers.

After a review of academic articles, standards, guidelines and vendor documentation, a proposal for assigning accountability and responsibility for business continuity and disaster recovery plans is presented, based on the RACI (responsible, accountable, consulted and informed) matrix. In this regard, a critical information infrastructure protection plan, a disaster recovery plan, an information systems contingency plan and a business continuity plan have been elaborated on in the article.

RACI matrices are presented for three general cloud service models and for three DRaaS models (managed, assisted and self-service). Accountability and responsibilities depend on the deployed cloud service model and the roles of cloud service providers and cloud consumers.

The proposed model for accountability and responsibility assignment provides a guideline for the allocation of responsibilities to roles not only during recovery but also during contract negotiations between cloud service providers and cloud consumers. By delving into business continuity and disaster recovery processes and activities, similar yet nuanced RACI matrices should be developed, as presented in this paper. They need to be customised for the specific context.

This study examines the preparedness and responsiveness of Malaysian academic librarians in handling disruptions in library services during a disaster.

This qualitative approach involved semi-structured interviews with decision-makers, chief librarians and library managers from five selected public universities.

Thematic and qualitative data analysis produced several key themes based on (1) disaster preparedness involving policies, plans, asset protection, risk management, coordination of disaster management and preparative measures; and (2) disaster response involving strategies for information and communication access, community engagement, emergency response teams and procedures, and resource availability.

The findings are expected to be useful for policymakers in formulating policies and guidelines for library disaster management plans.

The interruptions of academic library services during a disaster may result in the disruption of the information sources and social information networks of students, academics and researchers alike. Effective disaster management is also the library’s responsibility to protect collections that belong to society at large.

This is one of the first attempts in disaster management research to focus on the preparedness and responses of academic libraries in Malaysia in the face of disasters. Therefore, the results of this study can be used as a baseline for policymakers to prepare policies, guidelines and manuals for management in the event of a disaster.

The purpose of this paper is to explore the application of smart systems and emerging technologies for disaster risk management (DRM) in Nepal. This delves into specific technologies, including advanced connection and communication technologies, AI, big data analytics, autonomous vehicles and advanced robotics, examining their capabilities and potential contributions to DRM. Further, it discusses the possibility of implementing these technologies in Nepal, considering the existing policies and regulations, as well as the challenges that need to be addressed for successful integration.

For this review journal series of search strategy for identifying relevant journals, the initial examination of results, a manual assessment, geographical refinement, establishment of criteria for the final selection, quality assessment and data management, along with a discussion of limitations. Before delving into the relevant literature within the field of research interest, the authors identified guiding keywords. Further, the authors refined the list by filtering for articles specifically related to Nepal, resulting in a final selection. The final selection of these 95 articles was based on their direct relevance to the research topics and their specific connection in the context of Nepal.

The way technology is used to reduce disaster risk has changed significantly in Nepal over the past few years. Every catastrophe has given us a chance to shift to something innovative. The use of new emerging technologies such as artificial intelligence (AI), big data analytics, autonomous vehicles, advanced robotics and advanced connection and communication technologies are increasing for the purpose of generating risk knowledge, reducing disaster risk and saving the loss of lives and properties. The authors conclude that the successful implementation of smart systems and emerging technologies for disaster risk management in Nepal has the potential to significantly improve the country's resilience and minimize the impact of future disasters. By leveraging data-driven decision-making, enhanced connectivity and automation, Nepal can build a more proactive, adaptive and efficient disaster management ecosystem.

Studies on the application of smart systems in Nepal are limited and scattered across different database. This work collects together such literatures to understand the current status of the application of the smart system and technologies and highlights the challenges and way forward for effective disaster risk management in Nepal. Therefore, this work is an original one and adds value to the existing literatures.

The world-over, it is evident that, numbers and frequency of natural disasters have increased tremendously. The effects have given birth to a worldwide, all-inclusive humanitarian response and preparedness. In Zimbabwe, Cyclone Idai has ushered in the exploitation of various social media platforms by humanitarian organisations as a way of reaching out to the wider population on critical issues pertaining to the devastating effects of the cyclone. This study herein, aims to interrogate the efficacy of various social media platforms that were exploited by various humanitarian organisation involved in the Cyclone Idai humanitarian response. The various social media platforms are interrogated to establish their contribution to inclusivity or lack of it in relaying humanitarian interventions.

A mixed-method approach was used to conduct the research. Quantitative and qualitative methods were applied to gather the data. Quantitative data was collected using questionnaires with Likert scales and other closed questions provided. These were administered to representatives from the government, United Nations, donors, non-governmental organisations (NGOs), and members of the community. On the contrary, qualitative data was gathered from members of the community and humanitarian organisations through open-ended responses provided from interviews. Quantitative data was collected from a total of 384 stakeholder representatives who were randomly selected from Chimanimani district of Manicaland province. In addition, 12 interview participants were purposively selected to complement the research tools listed above.

The study findings show that social media platforms to a greater extent are effective tools for creating inclusive humanitarian response. The study findings reveal that social media has a significant positive influence on inclusive humanitarian response, with a 5% level of significance. These quantitative results agree with results obtained from interviewed participants. Managers of NGOs, community-based groups, government agencies and churches engaged in managing rescue, relief and humanitarian aid are supposed to access the study's findings in the future, and may find the results resourceful.

This study's generalisability to other districts and countries is constrained because it was conducted in the setting of the Chimanimani district. Future research can therefore be expanded to other Zimbabwean areas as well as to other countries in the Southern African region and beyond.

Humanitarian supply chain managers engaged in managing rescue, relief and humanitarian aid are proposed as having access to the study's findings in the future as they may find them useful.

This study contributes to the literature by providing insights that can improve information flow. This can be achieved by including different stakeholders in decision-making through the use of social media during disaster preparedness and response processes and helping them to better prepare for and respond to future disasters.

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.

Earthquakes pose a significant challenge to human safety and the durability of infrastructure, highlighting the urgent need for innovative disaster management strategies. This study addresses the gap in current earthquake disaster management approaches, which are often related to issues of transparency, centralization and sluggish response times. By exploring the integration of blockchain technology into seismic hazard management, the purpose of the research is to overcome these limitations by offering a novel framework for integrating blockchain technology into earthquake risk mitigation and disaster management strategies of smart cities.

This study develops an innovative approach to address these issues by introducing a blockchain-based seismic monitoring and automated decision support system for earthquake disaster management in smart cities. This research aims to capitalize on the benefits of blockchain technology, specifically its real-time data accessibility, decentralization and automation capabilities, to enhance earthquake disaster management. The methodology employed integrates seismic monitoring data into a blockchain framework, ensuring accurate, reliable and comprehensive information. Additionally, smart contracts are utilized to handle decision-making and enable rapid responses during earthquake disasters, offering an effective alternative to traditional approaches.

The study results highlight the system’s potential to foster reliability, decentralization and efficiency in earthquake disaster management, promoting enhanced collaboration among stakeholders and facilitating swift actions to minimize human and capital loss. This research lays the foundation for further exploration of blockchain technology’s practical applications in other disaster management contexts and its potential to transform traditional practices.

Current methodologies, while contributing to the reduction of earthquake-related impacts, are often hindered by limitations such as lack of transparency, centralization and slow response times. In contrast, the adoption of blockchain technology can address these challenges and offer benefits over various aspects, including decentralized control, improved security, real-time data accessibility and enhanced inter-organizational collaboration.