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Natural disasters profoundly influence agricultural trade sustainability. This study investigates the effects of natural disasters on agricultural production imports in China within 2002 and 2018. This exploration estimates the mediating role of transportation infrastructure and agriculture value-added and the moderating role of government effectiveness and diplomatic relations.

This investigation uses Probit, Logit, Cloglog and Ordinary Least Squares (OLS) models.

The results confirm the mediating role of transportation infrastructure and agriculture value-added and the moderating role of government effectiveness and diplomatic relations in China. According to the findings, natural disasters in trading partners heighten the risk to the agricultural imports. This risk raises, if disasters damage overall agricultural yield or transportation infrastructure. Moreover, governments’ effective response or diplomatic ties with China mitigate the risk. Finally, the effect of disasters varies by the developmental status of the country involved, with events in developed nations posing a greater risk to China’s imports than those in developing nations.

China should devise an early warning system to protect its agricultural imports by using advanced technologies such as data analytics, remote sensing and artificial intelligence. In addition, it can leverage this system by improving its collaboration with trading partners, involvement in international forums and agreement for mutual support in crisis.

Policy coherence is a complex and tough task for many developing nations because their capacity to examine and deliver evidence-based inputs to policymaking is limited, and policy dialogue platforms need to be effectively used. Resolving these difficulties is a critical requirement for policy consistency. As a result, the study focuses on the level of policy coherence for climate change adaptation (CCA), disaster risk reduction (DRR) and sustainable development goals (SDG) in Sri Lanka and suggests routes for policy coherence for Resilience. This study aims to investigate the coherent approach of CCA, DRR and SDG; to identify concerns in policy documents addressing the coherence of CCA, DRR and SDG in local context; and to propose policy coherence suggestions for resilience in Sri Lanka.

Methodology comprises a review and content analysis of 17 policy and legal documents in Sri Lanka and a qualitative study. The qualitative approach consists of semistructured interviews that obtained deep and broad expertise knowledge with ten government representatives and stakeholders. Both content analysis and interview data were analyzed by using NVivo.

It was discovered that there are several issues with the coherence of policies in Sri Lanka, including the fragmented approach, lack of integration, inadequate coordination, limited resources and lack of monitoring and evaluation. The policies are inspired by international frameworks, and local implementations are not focused, leading to inadequate implementation of policies. The lack of development cooperation for the use of innovative approaches, such as climate-resilient infrastructure and environmentally friendly solutions for CCA and DRR, further aggravates the situation. Another concern is the lack of land use management and responsibility for the development of physical infrastructure for DRR integration with CCA. It is found that there is a limited community involvement which is vital for the implementation of policies. Local implementations are encouraged to fill the gaps in existing policies/acts. The analytical framework of the study is based on a preliminary examination of policy documents, a review of the literature and discussions with practitioners. The framework reflects the current situation of policy integration which addresses strategic, conceptual, institutional, operational and financial coherence. The research suggests pathways for achieving policy coherence in CCA, DRR and SDG in Sri Lanka, such as enhancing the strategic coherence by improving goals to increase the coherence within CCA, DRR and SDG; improving the credibility of the unified approach for developing DRR and CCA risk assessments; intensifying institutional cooperation and stakeholder management; improving the common monitoring and evaluation; establishing implementation strategies; and increasing the community involvement.

The study on policy coherence in Sri Lanka recommends increasing community and professional involvement, conducting more research, developing a national strategy, increasing capacity building, strengthening international collaboration and fostering multisectoral collaboration. These recommendations can help improve policy coherence between CCA, DRR and SDGs, align policies with national goals and priorities and improve implementation effectiveness. By implementing these recommendations, Sri Lanka can address the challenges of climate change and natural disasters and achieve SDGs.

The study on policy coherence for resilience in Sri Lanka has practical implications, including improved coordination and resource allocation, increased capacity building, improved reputation and sustainability. By integrating CCA, DRR and SDGs, this study can help Sri Lanka become more resilient to climate change and natural disasters, achieve SDGs and become a responsible actor in the international community. These implications can contribute to a more sustainable future and ensure that development goals are achieved in a way that is resilient to climate change and natural disasters.

Increased community participation: the study emphasizes the importance of community involvement in the policy development process. This can help build trust between communities and government agencies, improve transparency and ensure that policies are developed in a way that is responsive to local needs and priorities.

Based on the identified existing loopholes in the policies and pathways to policy coherence, the issues in policymaking could be overcome. It could be used to establish strong linkages between policies based on CCA, DRR and SDGs to achieve long-term resilience.

Community centers play a socio-economic and urban role of combining different communal necessities, that serve inhabitants, at different neighborhoods in cities. Their role emerged in importance as being a hub for improving and customizing quality of life experiences of the public. This research presents a code-based risk assessment tool for evaluating fire safety measures that can be adapted in the context of community centers. It also provides an exemplary case study to demonstrate its application.

The study identified the factors that render community centers as a high-risk type of facilities in fire events. Various fire codes and standards were reviewed to describe the relevant fire safety measures. A code-based fire risk assessment tool was developed and implemented, through a case study. A set of recommendations were developed to improve the fire safety conditions of the case study facility.

Several violations to fire safety were identified in the case study building. The findings led to identifying a set of recommendations to improve its fire safety conditions.

This research introduced a systematic approach to raise awareness about fire incidences and consequences in community centers, and provides facilities managers with a tool, to assess compliance based on international fire code requirements.

In fire events, community centers are considered as high-risk facilities that may lead to significant losses of human lives and damages to assets. It is significant to study the causes of fire, for ensuring effective prevention and safe operations.

The purpose of this study is to review the role of knowledge management (KM) in disaster management and crisis. Disaster causes many detrimental impacts on human lives through loss of life and damage to properties. KM has been shown to dampen the impact of the disaster on the utilization of knowledge among agencies involved and the local communities impacted by disasters.

Through a bibliometric methodology (co-citation, bibliographic coupling and co-word analysis), this study presents significant themes in the past, current and future predictions on the role of KM in disaster management. In this review paper, 437 publications were retrieved from the Web of Science and analyzed through VOSviewer software to visualize and explore the knowledge map on the subject domain.

Findings suggest that the significant themes derived are centralized to disaster preparedness during disaster and disaster postrecovery. This review presents a state-of-art bibliometric analysis of the crucial role of KM in building networks and interconnection among relevant players and stakeholders involved in disaster management.

The main implication of this study is how the authorities, stakeholders and local community can integrate the KM system within the three stages of disasters and the crucial role of technologies and social media in facilitating disaster management.

To the best of the authors’ knowledge, this is the first study to present a bibliometric analysis in mapping KM’s past, present and future trends in disaster management.

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.

This study aims to develop an extended social attachment model for expatriates, integrating a multiple stakeholder perspective, to understand evacuation decisions during disasters.

Through interviews with 12 Tokyo-based expatriates who experienced the 2011 Tohoku earthquake, tsunami and nuclear disasters, this study collects the lived experiences of a diverse set of expatriates. This data is analyzed abductively to map relevant evacuation factors and to propose a reaction typology.

While the 2011 Tohoku disasters caused regional destruction and fears of nuclear fallout, Tokyo remained largely unscathed. Still, many expatriates based in Tokyo chose to leave the country. Evacuation decisions were shaped by an interplay of threat assessment, location of attachment figures and cross-cultural adjustment. The study also discusses the influence of expatriate types.

Disaster planning is often overlooked or designed primarily with host country nationals in mind. Expatriates often lack the disaster experience and readiness of host country nationals in disaster-prone regions in Asia and beyond, and thus might need special attention when disaster strikes. This study provides advice for how to do so.

By unpacking the under-researched and complex phenomenon of expatriate reactions to disasters, this study contributes to the fields of international human resource and disaster management. Specifically, seven proposition on casual links leading to expatriate evacuation are suggested, paving the way for future research.

This study aims to investigate the quality of disclosure of a cutting-edge reporting tool – integrated reporting (<IR>) – in terms of its effectiveness to report on COVID-19 pandemic information, its ability to provide forward-looking information and risk impact implications, and its quality determinants in challenging times.

Thanks to a content analysis of 247 <IR> for FY20, an integrated reporting disclosure score was developed to assess the disclosure quality provided by the sampled companies. Three research questions were tested through logistic regressions.

Non-financial disclosure activities struggle to provide adequate information in terms of potential future scenarios, risk assessment and forward-looking analyses. However, companies incorporated in “Anglo-Saxon” territories drafted integrated reports of higher quality. More recently, incorporated companies have made a greater effort to measure and report COVID-19 pandemic impacts on environmental, social and governance and business activities, also increasing their risk assessment and mitigation efforts. Concerning the determinants of disclosure quality, leverage, corporate governance structures, country of incorporation and belonging to “high impact” industries all lead to a higher quality of <IR> disclosure.

Examining in detail corporate social responsibility activities and corporate governance integrity is pivotal to orienting strategy towards sustainable trajectories: to do so, corporate reporting and disclosure practices are essential tools. In this context, corporate governance systems that emphasize board diversity are proven, even in disruptive circumstances, to play a crucial role in providing corporate reports of higher quality. High disclosure quality that goes beyond mere financial results is considered to be necessary to remain competitive strategically, socially and environmentally.

This research is aimed at preparing landslide susceptibility using spatial analysis and soft computing machine learning techniques based on convolutional neural networks (CNNs), artificial neural networks (ANNs) and logistic regression (LR) models.

Using the Geographical Information System (GIS), a spatial database including topographic, hydrologic, geological and landuse data is created for the study area. The data are randomly divided between a training set (70%), a validation (10%) and a test set (20%).

The validation findings demonstrate that the CNN model (has an 89% success rate and an 84% prediction rate). The ANN model (with an 84% success rate and an 81% prediction rate) predicts landslides better than the LR model (with a success rate of 82% and a prediction rate of 79%). In comparison, the CNN proves to be more accurate than the logistic regression and is utilized for final susceptibility.

Land cover data and geological data are limited in largescale, making it challenging to develop accurate and comprehensive susceptibility maps.

It helps to identify areas with a higher likelihood of experiencing landslides. This information is crucial for assessing the risk posed to human lives, infrastructure and properties in these areas. It allows authorities and stakeholders to prioritize risk management efforts and allocate resources more effectively.

The social implications of a landslide susceptibility map are profound, as it provides vital information for disaster preparedness, risk mitigation and landuse planning. Communities can utilize these maps to identify vulnerable areas, implement zoning regulations and develop evacuation plans, ultimately safeguarding lives and property. Additionally, access to such information promotes public awareness and education about landslide risks, fostering a proactive approach to disaster management. However, reliance solely on these maps may also create a false sense of security, necessitating continuous updates and integration with other risk assessment measures to ensure effective disaster resilience strategies are in place.

Landslide susceptibility mapping provides a proactive approach to identifying areas at higher risk of landslides before any significant events occur. Researchers continually explore new data sources, modeling techniques and validation approaches, leading to a better understanding of landslide dynamics and susceptibility factors.

Built environments are highly vulnerable to climatic disasters such as extreme floods, droughts and storms. Inaccurate decisions in adopting emerging construction technologies can result in missed opportunities to improve the resilience of built environments. Therefore, understanding the effectiveness of emerging construction technologies in improving built environment resilience can help in making better strategic decisions at the national and organizational levels. This study aims to evaluate the effectiveness of Construction 4.0 technologies in improving built environment resilience.

A list of Construction 4.0 technologies was adopted from a national strategic plan. Then, the data were collected using the fuzzy technique for order preference by similarity to ideal solution technique from selected built environment experts to determine the relative effectiveness of Construction 4.0 technologies in improving built environment resilience.

Six Construction 4.0 technologies are critical in improving built environment resilience (in rank order): building information modeling, autonomous construction, advanced building materials, big data and predictive analytics, internet of Things and prefabrication and modular construction. In addition, adopting Construction 4.0 technologies collectively is crucial, as moderate to strong connections exist among the technologies in improving built environment resilience.

To the best of the authors’ knowledge, this is one of the first papers that evaluate the effectiveness of Construction 4.0 technologies in improving built environment resilience. Industry professionals, researchers and policymakers can use the study findings to make well-informed decisions on selecting Construction 4.0 technologies that improve built environment resilience to climatic disasters.

Golestan province in the northern part of Iran has been affected by devastating floods. There has been a significant change in the pattern of rainfall in Golestan province based on an analysis of the seven heaviest rainfall events in recent decades. Climate change appears to be a significant contributing factor to destructive floods. Thus, this paper aims to assess the susceptibility of this area to flash floods in case of heavy downpours.

This paper uses a variety of computational approaches. Following the collection of data, spatial analyses have been conducted and validated. The layers of information are then weighted, and a final risk map is created. Fuzzy analytical hierarchy process, geographic information system and frequency ratio have been used for data analysis. In the final step, a flood risk map is prepared and discussed.

Due to the complex interaction between thermal fluctuations and precipitation, the situation in the area is further complicated by climate change and the variations in its patterns and intensities. According to the study results, coastal areas of the Caspian Sea, the Gorganrood Basin and the southern regions of the province are predicted to experience flash floods in the future. The research criteria are generalizable and can be used for decision-making in areas exposed to flash flood risk.

The unique feature of this paper is that it evaluates flash flood risks and predicts flood-prone areas in the northern part of Iran. Furthermore, some interventions (e.g. remapping land use and urban zoning) are provided based on the socioeconomic characteristics of the region to reduce flood risk. Based on the generated risk map, a practical suggestion would be to install and operate an integrated rapid flood warning system in high-risk zones.