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This paper aims to provide a general overview of the international Tsunami warning system mandated by the United Nations, particularly on cataloging past studies and a strategic focus in the Indian Ocean, particularly on the Bay of Bengal region.

Present research assimilates the secondary non-classified data on the Tsunami warning system installed in the Indian Ocean. Qualitative review and exploratory research methodology have been followed to provide a holistic profile of the Tsunami rarly warning system (TEWS) and its role in coastal resilience.

The study finds the need for strategic focus to expand and interlink regional early warning cooperation mechanisms and partnerships to enhance capacities through cooperation and international assistance and mobilize resources necessary to maintain the TEWS in the Indian Ocean region. The enhanced capacity of the TEWS certainly improves the resilience of Indian Ocean coastal communities and infrastructures.

The study is original research and useful for policy planning and regional cooperation on data interlinkages for effective TEWS in the Indian Ocean region.

This short paper builds on and critiques work presenting potential non-disasters: disasters that did not seem to happen despite a major hazard. Previous work does not differentiate among different types of potential non-disasters. This short paper uses local information to propose three categories according to reasons for vulnerability being low or absent. These proposed categories are used to critique the construct of “potential non-disasters”.

This short paper uses a subjective approach to examples of potential non-disasters in 2022, focusing on local information that describes what happened. This information is applied and analysed for the three proposed categories using examples from Japan, Nepal, the Philippines and Vietnam. Such comparisons are useful for critiquing “potential non-disasters”, by understanding better local approaches and information available for reporting on situations that could be disasters.

Potential non-disasters remain relevant for exploring mechanisms, tools and actions for educating about vulnerability causes and vulnerability reduction to avert disasters. Limitations are evident by relying on media reports, even local ones with local authors. A suggestion is to implement a grant programme for collecting data immediately after a major hazard without an evident, major disaster. Additionally, an annual report and critique of each year's potential non-disasters, categorised and analysed, would help to evidence the presence and limits of the “potential non-disaster” construct.

This short paper contributes a much deeper theoretical dive into understanding potential non-disasters, both describing them and the drawbacks of the construct. To practitioners, the construct now offers more avenues for actions while illustrating their effectiveness in reducing vulnerabilities. Thus, this paper supports multiple, linked pathways towards more non-disasters.

This paper aims to show the pragmatic studies that examine whether novel COVID-19 affects the national and international stock markets and reinforces the existing literature by highlighting the factors that are resultant from COVID 19.

The systematic literature review and bibliometric approach have been used in the study covering 585 selected articles published in journals of high repute from January 2020 to January 2022. The process of bibliometric analysis has been divided into three stages, namely, assembling, arranging and assessing. From the Scopus database, one of the most reliable and authentic database total of 585 records were collected, out of which 12 were specifically focused on communities, and information gathered in the comma-separated value documents design was compared and interpreted based on year, document types, subject area, country and research fields with the help of graphs and pie charts. The study has analyzed fact-based and reliable studies to draw inferences from existing literature regarding the pandemic impacting the financial markets. In the extant study, an attempt has been made to explore the factors that are resultant from the COVID-19 pandemic and affects the stock market performance, which can be further classified into a few common factors by using factor analysis.

It originated from the majority of the studies that the stock market retorted destructively to the upsurge in the figure of COVID-19 cases and fatalities. It also emphasized that the market has reacted differently in comparison to earlier catastrophes such as the great depression of 2008 and the Spanish flu. Various factors such as fear of losing capital, standstill economy, lower valuation, increased mortality rate, halt in business operations, retrenchment, trade war, liquidity issues, panic buying and selling, digitalization, negative media coverage, government interference, financial behavior of investors, hoarding of COVID supplies, promotion of start-up in health-care and education sector, news bulletins, prevention campaigns, use of medical devices and COVID-19 vaccination, etc. have been conferred from the studies that have an immediate consequence on the actions of investors in the stock market. It was further highlighted in the study that the Indian stock market has been less explored in respect of implications of COVID-19 contagion as the majority of studies were based on either international stock exchanges or combinations of varied nation’s stock markets. It was witnessed in the interpretation section that the number of studies is increasing at a fast pace as new variants of COVID-19 are emerging over time. Significant contribution has been done in enhancing the literature on COVID-19 and the stock market by China and the USA. The maximum contribution in this domain has been done in the form of articles in the present literature. Few studies were focusing on communities, so the present study will try to fill this research gap to some extent.

This conceptual paper is demarcated by unsatisfactory analyses of writings from multi-discipline to get a comprehensive scope of notional understanding. Furthermore, there is a perchance that some other imperative phenomena or variables that prejudiced trading bustle have not been captured by present reviews of research papers. The influences of other macroeconomic variables should be explored to understand the concrete results of this pandemic.

Most of the studies were based on foreign stock exchanges, so there is an opportunity to explore the Indian stock market concerning the implications of the coronavirus pandemic. In the literature, it was examined that short-term studies have been undertaken, which cannot determine the long-term implications of COVID-19. Over time, besides COVID-19, various other factors have started impacting the stock market, so it has become difficult to examine the influence of COVID-19 on the stock market in isolation.

The study will be helpful for future learnings in the arena of the stock market as it provides vast exposure to the present literature related to the impact of COVID-19 on economic markets. On the other hand, investors will also become aware of factors that are resultant of COVID-19 and will take the right decisions to save their investments in light of pandemic implications. The extensive review of studies will also help enterprising communities to take judicial steps to remain active in the period of economic slowdown.

The paper provides significant implications to the investors in the stock market, and it will provide useful insight to improve their returns on their portfolios. The learning from the study will help investors to take fruitful decisions considering the uncertainty during the pandemic period. The inferences drawn from rich existing literature will be guiding enterprises to take timely actions to avoid the situation of loss in the market and adapt new models to ensure continuity of business operations. Different markets had reacted differently, so investors need to be cautious before taking trading decisions.

Despite striving for resilience and a sustainable urban future, European cities face a multitude of crisis caused by both natural and human-induced risks. This paper asks two key questions: How have cities experienced and managed crises situations they encountered? and What are the plans and actions for embedding sustainability at a local level within a clear decision-making structure? Hence, it aims to examine urban resilience in the context of urban crisis and the associated health concerns that took place because of crisis situations, while identifying sustainable urban development initiatives and strategies that were conceived and implemented beyond crisis.

An evidence-based analytical approach is undertaken following two lines of inquiry. The first is case-based and identifies 11 cities that have experienced crisis situations and a further 10 cities that have instigated urban resilience strategies. The second is theme-based and engages with identifying strategies relevant to sustainable urban development at city and project levels. The outcomes of the two lines of inquiry are verified by mapping the lessons learned from the analysis to recent international guidance and a further co-visioning workshop with 6 experts.

The evidence-based analysis reveals key lessons which were classified under two primary types of findings: (a) lessons learned for a future urban resilience resulting from the 1st line of Inquiry (case-based) and (b) lessons learned for a future sustainable urban development resulting from the 2nd line of inquiry (theme-based). The verified lessons provide four areas that can be utilised as key priorities for future urban resilience and sustainable urban development including (a) Governance, effective communication, and decision making for city resilience and urban sustainability; (b) the social dimension of resilience and participatory practices for sustainable urban development; (c) from implicit strategies for health to positive impact on health; and (d) diversification of initiatives and localisation of sustainable development endeavours.

There is always limitation on what a bibliometrics analysis can offer in terms of the nature of evidence and the type of knowledge generated from the investigation. This limitation manifests in the fact that the analysis engages with the body of knowledge but not based on engaging physically or socially with the contexts within which the cases took place or through empirical investigations including systematic observations, focused interviews, and attitude surveys. While the study does not generate empirical findings, the rigour of the bibliometrics analysis offers a credible and reliable evidence on how cities experienced and managed crises situations and their current plans and priority actions for embedding and localising sustainable development measures.

This research conveys significant implications for policy, practice, and action in that it crystalises the view that understanding urban resilience and sustainability, at the city or urban level, requires coupling the two. The findings offer a solid foundation for a more contextualised, evidence-based examination of urban resilience and sustainability during and beyond crisis. Highlighting urban and health challenges that emerged from experienced crisis situations, how these were managed and developing an understanding of sustainable urban development and local resilience strategies elucidate insights that can be adopted and acted upon by city councils and built environment practitioners.

The analysis provides comprehensive insights into urban resilience and sustainable urban development at both city and continental Europe scales in the form of key lessons that represent the first step towards developing rudiments for building a better urban future. Little is known about resilience and sustainability at these scales. The originality of this work lies in the breadth and depth for capturing an inclusive understanding of urban resilience and sustainable urban development based on systematic inquiry and scrutinising the body of knowledge emerged over the past 2 decades.

This study aims to investigate the supply chain gaps during the COVID-19 pandemic in Tanzania amid the pandemic era.

This study adopted a mixed approach, using both structured questionnaires and individual interviews to gather raw data (quantitative and qualitative data). To assess quantitative data for statistical (descriptive and inferential) analysis, this study used a sample of 57 wholesale and retail pharmacies and 10 hospital pharmacies, which were randomly selected. The thematic analysis was applied to the gathered qualitative data to authenticate the quantitative findings and conclusions which were the outcome of the descriptive and inferential analysis (binary logistics regression) analysed by the SPSS.

The results revealed the presence of various supply chain gaps in terms of target gaps, time gaps and coverage gaps. This study highlighted the disruption on demand and uncertainty in business environment as ways that the COVID-19 pandemic contributed to the gaps and revealed the negative effects of the supply chain gaps on the effectiveness of medical supplies in Tanzania.

The results revealed the presence of various supply chain gaps (in terms of target gaps, time gaps and coverage gaps), underlined the disruption in demand and uncertainty in the business environment as ways that the COVID-19 pandemic contributed to the gaps and revealed the negative effects of the supply chain gaps on the effectiveness of medical supplies in Tanzania.

Data generated and used in this study is from participants from one country only (Tanzania), despite the supply chain gaps being common to many developing countries in general.

This study provides a novel framework in medical supply chain literature by identifying numerous disruptions in the medical supply chain which emerged during the COVID-19 emergence and serves as a basis for future studies on how to counter the gaps and rebuild a resilient and sustainable medical supply chain in developing countries.

The study aims to develop a multilayer high-effective ensemble of ensembles predictive model (stacking ensemble) using several hyperparameter optimized ensemble machine learning (ML) methods (bagging and boosting ensembles) trained with high-volume data points retrieved from Internet of Things (IoT) emission sensors, time-corresponding meteorology and traffic data.

For a start, the study experimented big data hypothesis theory by developing sample ensemble predictive models on different data sample sizes and compared their results. Second, it developed a standalone model and several bagging and boosting ensemble models and compared their results. Finally, it used the best performing bagging and boosting predictive models as input estimators to develop a novel multilayer high-effective stacking ensemble predictive model.

Results proved data size to be one of the main determinants to ensemble ML predictive power. Second, it proved that, as compared to using a single algorithm, the cumulative result from ensemble ML algorithms is usually always better in terms of predicted accuracy. Finally, it proved stacking ensemble to be a better model for predicting PM_2.5 concentration level than bagging and boosting ensemble models.

A limitation of this study is the trade-off between performance of this novel model and the computational time required to train it. Whether this gap can be closed remains an open research question. As a result, future research should attempt to close this gap. Also, future studies can integrate this novel model to a personal air quality messaging system to inform public of pollution levels and improve public access to air quality forecast.

The outcome of this study will aid the public to proactively identify highly polluted areas thus potentially reducing pollution-associated/ triggered COVID-19 (and other lung diseases) deaths/ complications/ transmission by encouraging avoidance behavior and support informed decision to lock down by government bodies when integrated into an air pollution monitoring system

This study fills a gap in literature by providing a justification for selecting appropriate ensemble ML algorithms for PM_2.5 concentration level predictive modeling. Second, it contributes to the big data hypothesis theory, which suggests that data size is one of the most important factors of ML predictive capability. Third, it supports the premise that when using ensemble ML algorithms, the cumulative output is usually always better in terms of predicted accuracy than using a single algorithm. Finally developing a novel multilayer high-performant hyperparameter optimized ensemble of ensembles predictive model that can accurately predict PM_2.5 concentration levels with improved model interpretability and enhanced generalizability, as well as the provision of a novel databank of historic pollution data from IoT emission sensors that can be purchased for research, consultancy and policymaking.

This research paper aims to empirically explore how stock market investors’ perceptions are affected by extreme climatic events like El Nino and floods in Malaysia.

This study uses structural equation modelling (SEM) to analyse the empirical data gathered through a questionnaire survey involving 273 individual investors from Bursa Malaysia between January and June 2019.

Results reveal that companies’ efforts, especially for agriculture and plantation-based industries, to adapt to climate change risk at the production, business and stock market levels significantly impact investors’ behaviour and investment decisions. Moreover, stock market investors’ climate change knowledge shows a significant moderating effect on corporate climate change adaptation initiatives and investors’ decisions to invest in Malaysian agricultural and plantation industry stocks.

This research has significant implications for practice and policy, as it measures the stock market investors’ level of awareness about climate change events and explores the companies’ strategies to reduce climatic risks to their business model.

This study shows the way to adjust the climate change information in the stock market investment decision to improve market efficiency and sustainable stock exchanges initiative.

To the best of the authors’ knowledge, this paper is the pioneer one to provide a comprehensive link between climate change events and business performances at production level, business level and stock market levels by drawing inferences from empirical data on investors’ behaviours. This study also added value in investment theories and financial literature by observing the climate change as an important factor to determine the investors’ decisions in the stock market.

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.

This paper aims to describe the phenomenon of multiple simultaneous un/natural disasters (MSDs). This study also aims to describe the importance and contribution of philosophy in describing MSDs warning and alarming systems.

The paper summarizes topics in the philosophy of MSDs that were covered in detail in previous research in order to continue with the topic of the philosophy of MSDs alarming and warning. A practical solution to conceptual paradoxes is researched by means of conceptual-morphological analysis.

The paper proposes a conceptual idea for MSDs alarming system which is its main topic; namely, it offers a conceptual solution to a series of practical-conceptual paradoxes that occur before, during and after MSDs.

This is only a conceptual research, and it does not deal with particular technological solutions.

The proposed solution of this research could be implemented in various warning and alarm systems.

The proposed concept of a universal alarm system for MSDs was not previously proposed.