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This study aims to review the stages of the traditional disaster timeline, propose an extended version of this timeline and discuss the disaster strategies relevant to the different stages of the extended timeline.

An extensive review of the existing literature was made to discuss the need for an extended version of the conventional disaster timeline and to explain the differences between the various disaster management strategies. The research approach was based on theoretical and practical reasoning underpinned by the literature.

The proposed extended disaster timeline allows better allocation of a wider range of management strategies. Successful disaster management depends on prioritisation of efforts and the use of the right strategy(s) at the right time: before, during and after an incident.

This study provides a better conceptualisation of the disaster stages and corresponding strategies. It clarifies the role of each strategy, thus linking it more effectively with the disaster timeline. Subsequently, this study is expected to improve decision-making associated with the disaster management process. In the end, it is expected to help transforming the conventional disaster timeline into a more practical one that is result-oriented more than only being a conceptual model.

Disaster management strategies are used interchangeably very often in the literature. A few attempts were made to capture multiple strategies in one study to demonstrate what constitutes effective disaster management without mixing irrelevant strategies with the different disaster stages.

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.

Disasters can affect the important sector of tourism across the world. This study aims to combine qualitative findings from 13 publications to enhance disaster management plans for the security and resilience of the tourist industry.

The authors used Noblit and Hare’s seven-step meta-ethnography method, identifying 13 qualitative studies on tourism disaster management through extensive searches in key databases (WoS, Scopus and Google Scholar), meeting inclusion criteria. NVivo 12 aided in coding, translation and comprehension of related ideas.

Five interrelated and third-ordered conceptual categories were identified: extreme natural and malevolent events, lack of risk management and emerg+ency response, sustainable tourism, tourism resilience factors, disaster awareness and preparedness. Effective strategies demand collaboration, resource allocation and local engagement.

This study offers a novel synthesis of qualitative research in tourism disaster management, enhancing understanding of resilience in the industry. It provides unique insights on cross-cultural dynamics, stakeholder engagement and integrated strategies while showcasing the utility of meta-ethnography in business and management research.

This paper aims to examine and compare extant literature on the application of multi-criteria decision-making (MCDM) techniques in humanitarian operations (HOs) and humanitarian supply chains (HSCs). It identifies the status of existing research in the field and suggests a roadmap for academicians to undertake further research in HOs and HSCs using MCDM techniques.

The paper systematically reviews the research on MCDM applications in HO and HSC domains from 2011 to 2022, as the field gained traction post-2004 Indian Ocean Tsunami phenomena. In the first step, an exhaustive search for journal articles is conducted using 48 keyword searches. To ensure quality, only those articles published in journals featuring in the first quartile of the Scimago Journal Ranking were selected. A total of 103 peer-reviewed articles were selected for the review and then segregated into different categories for analysis.

The paper highlights insufficient high-quality research in HOs that utilizes MCDM methods. It proposes a roadmap for scholars to enhance the research outcomes by advocating adopting mixed methods. The analysis of various studies revealed a notable absence of contextual reference. A contextual mind map specific to HOs has been developed to assist future research endeavors. This resource can guide researchers in determining the appropriate contextual framework for their studies.

This paper will help practitioners understand the research carried out in the field. The aspiring researchers will identify the gap in the extant research and work on future research directions.

To the best of the authors’ knowledge, this is the first literature review on applying MCDM in HOs and HSCs. It summarises the current status and proposes future research directions.

This study aims to review the results of relevant studies to shed light on social trust-building in different contexts and the factors that affect it in disaster risk management.

This systematic review was conducted using the Preferred Reporting Items for Systematic reviews and Meta-Analyses model. The study keywords were searched for in PubMed, Scopus and Web of Science databases on August 2021. The inclusion criteria were English-written articles published in social trust and disaster relief efforts. Exclusion criteria were lack of access to the full text and article types such as nonoriginal articles.

Out of 1,359 articles found, 17 articles were included in the final analysis using four general categories: six articles on the role of local government in trust-building (local governments), five articles on the role of social media in trust-building (social media), four articles on the role of social capital in trust-building (social capital) and two articles on the importance of community participation in trust-building (community participation).

Understanding the role of social trust and the factors which influence it will help the development of community-based disaster risk management. Therefore, disaster management organizations and other relief agencies should take the findings of this study into account, as they can help guide policymaking and the adoption of strategies to improve public trust and participation in comprehensive disaster risk management. Further studies recommended understanding people’s experiences and perceptions of social trust, relief and disaster preparedness.

Global climate change speeds up ice melting and increases flooding incidents. China launched a sponge city policy as a holistic nature-based solution combined with urban planning and development to address flooding due to climate change. Using Weibo analytics, this paper aims to study public perceptions of sponge city.

This study collected 53,586 sponge city contents from Sina Weibo via Python. Various artificial intelligence tools, such as CX Data Science of Simply Sentiment, KH Coder and Tableau, were applied in the study.

76.8% of public opinion on sponge city were positive, confirming its positive contribution to flooding management and city branding. 17 out of 31 pilot sponge cities recorded the largest number of sponge cities related posts. Other cities with more Weibo posts suffered from rainwater and flooding hazards, such as Xi'an and Zhengzhou.

To the best of the authors’ knowledge, this study is the first to explore the public perception of sponge city in Sina Weibo.

Based on the perspective of knowledge management, this study aims to discuss how to build cross-city emergency management collaboration mechanism in major emergencies and explore the important role of knowledge management in emergency management collaboration.

Based on the theoretical analysis of knowledge management and the typical case study of cross-city emergency management collaborative rescue, this study provides an in-depth analysis of how these cities achieve high emergency management performance through multidimensional and multilevel knowledge collaboration, thus revealing the mechanism of knowledge transfer, integration and sharing in achieving high emergency management performance.

Through analyzing typical cases, this study finds that building a smooth mechanism for multichannel emergency rescue information can promote the diversification of knowledge transfer methods, building a platform-based integration mechanism for emergency rescue information can enhance knowledge integration capabilities and building a linkage mechanism for emergency rescue materials between cities can promote knowledge-sharing level, thereby improving emergency management performance level.

This study has great significance for how to build cross-city emergency management collaboration mechanism in the digital era. In the future, the authors need to further discuss the following two aspects in depth: research on the impact of cross-city emergency management collaboration mechanism on improving the knowledge management capabilities of government emergency management departments; and research on the impact mechanism of knowledge management capabilities on city resilience.

Through case analysis of cross-city emergency management collaborative rescue for major emergencies in China in recent years, this study proposes three specific strategies for cross-city emergency management (smooth, integration and linkage mechanisms) and reveals that these three strategies are essentially aimed at improving the government’s knowledge management level.

This research investigates the impact of the COVID-19 pandemic on the use of transitional spaces in a Korean academic setting, to assess the impact of the pandemic on users' utilization of transitional spaces and evaluate any changes in their usage patterns. The research explores whether transitional spaces can function as social interactive spaces, aligning with Ray Oldenburg's “third-place” theory. The focus is on South Korean academic settings, aiming to create neutral and safe zones for users.

The adopted methodology involves reviewing the literature and employing design charrette as a major data collection tool. The design charrette provided a platform for users to share insights on current transitional spaces during the pandemic and envision these spaces as future social and interactive spaces.

The design charrette participants advocated for modifying the current transitional space design to transform these spaces into shared spaces for both visitors and regular users in the future. Restricting access for external users to the main building area until necessary. The significance of site amenities in determining transitional spaces as “third-places” was emphasized. While the nature of the building, its location and transitional space amenities are crucial aspects to consider, designers may prioritize user opinions and preferences, as the success or failure of the design ultimately centers on user behaviors.

The research focused on a specific university, hindered by limited access to other institutions during the pandemic. Restrictions on external users discouraged entry without proper permission, which was challenging to obtain. The conventional design charrette outlined in the research method was impossible due to pandemic-related limitations on gathering participants in one location. Therefore, the researcher modified the design charrette method to align with strict social distancing measures.

The results of the research are not limited to academic settings, but they can be implied in other environments where social interaction spaces are required and where there is a constant flow of visitors and regular users. The design charrette can be used as a methodology for interior spaces along with large-scale projects of urban planning.

The research analyzed transitional spaces during the pandemic, suggesting redesign to serve and act as buffer zones between private and public areas and become a common social gathering place for visitors and regular users within the built environment.

This study provides a configurational examination of how policy designs influence the innovation performance of the emergency industry in China.

This study employs the Data Envelopment Analysis Malmquist index (DEA-Malmquist) to quantify the innovation performance of the emergency industry and then codes the innovation policies to calculate the syntactic components based on institutional grammar tools (IGTs). The configurations of syntactic components were determined by applying the fuzzy-set qualitative comparative analysis (fsQCA).

The results indicate that rules- and norms-oriented policy designs would improve the innovation performance of China's emergency industry. In the developed provinces, the “Deontic” and “aIm” combinations in the policy are useful for improving performance. In the developing provinces, the ambiguity of the “aIm” and “Context” conditions in the policy is leading to low performance. Additionally, a lack of strategy-oriented policy design would also result in poor performance.

Most previous studies used substitute variables to understand policy impacts. This study contributes to identifying the impacts of the syntactic components of policy designs on the innovation performance of the emergency industry. The findings can assist policymakers in developing more effective policies to stimulate innovation development in the emergency industry.

This study aims to analyze government hotline text data and generating forecasts could enable the effective detection of public demands and help government departments explore, mitigate and resolve social problems.

In this study, social problems were determined and analyzed by using the time attributes of government hotline data. Social public events with periodicity were quantitatively analyzed via the Prophet model. The Prophet model is decided after running a comparison study with other widely applied time series models. The validation of modeling and forecast was conducted for social events such as travel and educational services, human resources and public health.

The results show that the Prophet algorithm could generate relatively the best performance. Besides, the four types of social events showed obvious trends with periodicities and holidays and have strong interpretable results.

The research could help government departments pay attention to time dependency and periodicity features of the hotline data and be aware of early warnings of social events following periodicity and holidays, enabling them to rationally allocate resources to handle upcoming social events and problems and better promoting the role of the big data structure of government hotline data sets in urban governance innovations.