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Conflict and violence are the main drivers of globally escalating humanitarian needs. Local grassroots initiatives are pivotal in distributing humanitarian supplies in the acute response phase until more established humanitarian aid organizations can enter. Nevertheless, scant research exists regarding the role of grassroots associations in providing humanitarian assistance during a military conflict. The purpose of this paper is to understand the role of grassroots associations and identify important themes for effective operations.

This paper adopts a case-study approach of three Ukrainian grassroots associations that began operating in the immediate days of the full-scale invasion of Ukraine. The findings are based on analyzing primary sources, including interviews with Ukrainian volunteers, and are supported by secondary sources.

Grassroots associations have local contacts and a contextual understanding of population needs and can respond more rapidly and effectively than large intergovernmental agencies. Four critical themes regarding the operations of grassroots associations emerged: information management, inventory management, coordination and performance measurement. Grassroots humanitarian response operations during conflict are challenged by personal security risks, the unpredictability of unsolicited supplies, emerging volunteer roles, dynamic transportation routes and shifting demands.

Grassroots responses are central to humanitarian responses during the acute phase of a military conflict. By examining the operations of grassroots associations in the early months of the 2022 war in Ukraine, the authors provide a unique perspective on humanitarian logistics. Nonetheless, more inclusive models of humanitarian responses are needed to harness the capacities and resilience of grassroots operations in practice.

This study aims to deepen the understanding of the challenges and implications entailed by deploying mobile clinics in conflict zones to reach populations affected by violence and cut off from health-care services.

This research combines an integrated literature review and an instrumental case study. The literature review comprises two targeted reviews to provide insights: one on conflict zones and one on mobile clinics. The case study describes the process and challenges faced throughout a mobile clinic deployment during and after the Iraq War. The data was gathered using mixed methods over a two-year period (2017–2018).

Armed conflicts directly impact the populations’ health and access to health care. Mobile clinic deployments are often used and recommended to provide health-care access to vulnerable populations cut off from health-care services. However, there is a dearth of peer-reviewed literature documenting decision support tools for mobile clinic deployments.

This study highlights the gaps in the literature and provides direction for future research to support the development of valuable insights and decision support tools for practitioners.

The purpose of this paper is to propose a scenario-based grey methodology using clustering and optimizing with imprecise and uncertain body size data in an emergency assembly point area to assign the people on a campus to reach the emergency assembly points under uncertain disaster times.

Grey clustering and a new grey p-median linear programming model are developed to determine which units to assign to the pre-determined assembly points for a main campus in case of a disaster. The models have two scenarios: 70 and 100% occurrence capacities of administrative and academic personnel and students.

In this study, the academic and administrative units have been assigned to determine five different emergency assembly points on the main campus by using the numbers of the academic and administrative personnel and student and distances of the units to the assembly point areas of each other. The alternative solutions are obtained effectively by evaluating capacity utilization rates in the scenarios.

It is often unclear when disasters can occur and therefore, a preliminary preparation time must be required to minimize the risk. In the case of natural, man-made (unnatural) or technological disasters, the people are required to defend themselves and move away from the disaster area as soon as possible in a proper direction. The proposed assignment model yields a final solution that effectively eliminates uncertainty regarding the selection of emergency assembly points for administrative and academic staff as well as students, in the event of disasters.

Grey clustering suggests an assignment plan and concurrently, an investigation is underway utilizing the grey p-median linear programming model. This investigation aims to optimize various scenarios and body sizes concerning emergency assembly areas. All campus users who are present at the disaster in units of the campus are getting uncertainty about which emergency assembly point to use, and with this study, the vital risks aim to be ultimately reduced with reasonable plans.

The purpose of this paper is to explore the feasibility of mud brick houses as an alternative to the more widely adopted emergency shelters used in war-torn Syria. It focuses on the mud houses’ sustainability, cost effectiveness, cultural preference, income generation and security.

This study uses a qualitative research approach to a single case study. Interviews were conducted with field experts from the Qatar Red Crescent Society and members of the internally displaced persons (IDPs) community living in mud brick houses.

The findings reveal that the utilisation of mud houses is a good alternative in relief efforts. The houses are sustainable and cost-effective, take into consideration cultural dynamics and provide economic empowerment to IDPs. However, the maintenance of mud brick houses turns out to be the largest flaw, and this problem requires further research.

The paper highlights the inefficiency of current emergency sheltering practices in Syria and reveals that tents are not a preferred mode of shelter. It further sheds light on a unique case study in which mud houses were used by an aid and development organisation, highlighting its strengths and weaknesses. This paper contributes to practical discussion and ideation on more appropriate housing for IDPs.

This study aims to analyse the structure of the Indian vaccine supply chain (SC) during the Covid-19 crisis and explore the underlying challenges at each stage in the network. It also brings out the difference in performance of various constituent states.

This study relied on both primary and secondary data for the analyses. For the primary data, the study gathered experts’ opinions to validate the authors’ inferences. For the secondary data, it relies on government data provided in websites.

Based on the quartile analysis and cluster analysis of the secondary data, the authors find that the constituent states responded differently during the first and second waves. This was due to the differences in SC characteristics attributed to varied demographics and administrative efficiency.

This paper’s analyses is primarily limited to secondary information and inferences are based on them. The study has important implications for implementing the large-scale vaccination drives by government and constituent states for better coordination and last-mile delivery.

The contribution is unique in studying the performance of constituent states using statistical techniques, with secondary data from authentic sources. It is also unique in combining this observation with validation from experts.

The coronavirus disease (COVID-19) pandemic has been negatively affecting international trade between countries; however, there is a lack of empirical studies on developing countries such as Vietnam. This article aims to investigate how the COVID-19 cases and related deaths and policy response by Vietnam and trading partners to the pandemic affect Vietnam's export activities.

The authors use the monthly trade data from the General Department of Vietnam Customs and employ the Poisson pseudo-maximum-likelihood (PPML) estimator to empirically investigate the effects of COVID-19 and policy response to the pandemic on Vietnam's exports at aggregate and sectoral levels over a 33-month period.

In the first year of the pandemic (January–December 2020) as well as the whole study period (January 2019–September 2021), trading partners' COVID-19 burden adversely affected Vietnam's aggregate exports, and the effect of COVID-19 deaths is significantly larger than that of COVID-19 cases. In the first year of the pandemic, estimates show a negative effect of Vietnam's COVID-19 cases on its exports, while no evidence reveals the impact of Vietnam's COVID-19 deaths. However, during the entire study period, there are remarkable adverse effects of Vietnam's COVID-19 deaths on its exports. The effect of the COVID-19 burden in Vietnam and in its trading partners differs significantly across major subsectors. In the first year, there is a positive role of government response to the pandemic by Vietnam and its trading partners in Vietnam's aggregate exports, while in the whole study period, only a positive effect of Vietnam's government response is found. Economic support and free trade agreements (FTAs) have a positive effect on Vietnam's exports. In the first year of the pandemic, Vietnam's export losses due to COVID-19 outweighed its export gains from the pandemic. However, Vietnam's exports have significantly improved over the nine months of 2021.

Efforts should aim to reduce the number of COVID-19 deaths rather than focus on reducing the number of COVID-19 cases. The application of stringency measures by both exporters and importers should be minimized, or at least those measures need to be combined with health methods, such as testing policy and contact tracing, short-term investment in healthcare and especially investments in vaccines. In addition, economic support, particularly debt relief, needs to be widely applied to assist firms, especially those involved in international trade. The expansion of FTA networks and diversifying export destinations may be helpful in maintaining production networks and export activities.

In the long-term period, the application of stringency measures by both exporters and importers should be minimized, or at least those measures need to be combined with health methods such as testing policy and contact tracing, short-term investment in healthcare and especially investments in vaccines. In addition, economic assistance, particularly debt relief, needs to be widely applied to assist firms, especially those involved in international trade activities.

To the best of the authors’ knowledge, the paper is among the first studies empirically investigating the impacts of COVID-19 and policy response to the pandemic on aggregate and sectoral exports from Vietnam. The paper also measures the absolute value of export gain and export loss due to the pandemic between Vietnam and trading countries.

Purpose: This study examines the effect of uncertainties on the hospitality industry from different perspectives across the globe. The hospitality industry faces several contemporary issues and challenges that have the potential to impact its growth and development. This study aims to analyse the current problems and uncertainties in the hospitality sector.

Need for the Study: The hospitality industry plays a significant role in the global economy with various services, including accommodation, food and beverage, events, and tourism. However, the sector faces several contemporary issues and challenges that have the potential to impact its growth and development. This study provides an overview of the most significant problems and challenges facing the hospitality industry today.

Methodology: A systematic literature review was conducted to identify and synthesise relevant studies on the effect of uncertainties issues on the hospitality industry. A systematic search of the Web of Science and Scopus databases was conducted to determine relevant studies published between 2010 and 2021. Studies were screened and selected based on pre-defined inclusion and exclusion criteria. A thematic analysis was performed to categorise the uncertainties and issues in the hospitality industry.

Findings: The study identified several uncertainties and issues facing the hospitality industry, including the pandemic uncertainties, financial crisis, whether positive and negative impacts, terrorism attacks on hotels and tourist places, uncertainties in government policies, situational risks like uncertainties, ambiguity, cultural differences, changes in tourist preferences and changing habits of the tourist.

This research explores the drivers that determine the ability of spontaneous volunteer groups (SVGs) to sustain their operations. That sustainability aims to support those affected in the community beyond the response phases of a disaster and into the recovery and mitigation phases to build resilience to the next disaster.

To investigate the sustainability of spontaneous volunteering that takes place in the aftermath of a disaster, we conducted qualitative interviews in three English locations where groups of spontaneous volunteers emerged following major floods. We analysed our qualitative data using thematic analysis.

Our findings theorise the drivers of SVG sustainability and present these in four themes: (1) assessment of ongoing needs; (2) organisation of resources to address that need; (3) leadership and followership creating a weight of operational capability and (4) influence of political will. Through exploring these drivers, we uncover key factors to developing a sustainable SVG system including trusted leadership and social capital.

We show how the four drivers interact to support the continuity of SVGs and sustain their operations. This has implications for how leaders of SVGs create a volunteering environment that encourages ongoing involvement and has implications for officials to view SVGs as a support rather than a risk.

The novelty of our paper is in rejecting the argument of the temporal limit of SVGs to the response phase by theorising the drivers that make their operations sustainable for recovery and resilience building to mitigate the next disaster. This includes our examination of the interplay between those drivers.

This paper aims to develop an algorithm to study the impact of dynamic resource disruption on project makespan and provide a suitable resource disruption ratio for various complex industrial and emergency projects.

This paper addresses the RCPSP in dynamic environments, which assumes resources will be disrupted randomly, that is, the information about resource disruption is not known in advance. To this end, a reactive scheduling model is proposed for the case of random dynamic disruptions of resources. To solve the reactive scheduling model, a hybrid genetic algorithm with a variable neighborhood search is proposed.

The results obtained on the PSLIB instances prove the performance advantage of the algorithm; through sensitivity analysis, it can be obtained, the project makespan increases exponentially as the number of disruptions increase. Furthermore, if more than 50% of the project's resources are randomly disrupted, the project makespan will be significantly impacted.

The paper focuses on the impact of dynamic resource disruptions on project makespan. Few studies have considered stochastic, dynamic resource uncertainty. In addition, this research proposes a reasonable scheduling algorithm for the research problem, and the conclusions drawn from the research provide decision support for project managers.