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The purpose of this paper is to empirically explore the potential of outsourcing of humanitarian logistics activities to commercial logistics service providers (LSPs) throughout the different disaster phases. The authors identify incentives for initiating outsourcing of humanitarian logistics activities to commercial logistics providers, humanitarian logistics activities to be outsourced and selection criteria for partners.

This study is based on empirical data collected by interviewing 12 practitioners from commercial LSPs and 12 practitioners from humanitarian organizations (HOs). A review of related literature guided this research.

This research shows that incentives for initiating outsourcing engagements, partner selection criteria and activities to be outsourced are changing throughout the different disaster phases. A number of research propositions are presented.

This research constitutes a first step towards the goal of a comprehensive analysis of humanitarian logistics outsourcing throughout the different disaster phases. The authors collected data from practitioners and large organizations based mainly in Europe and the USA. Hence, insights from national and local organizations of other parts of the world are missing.

This research provides a deeper understanding of outsourcing of humanitarian logistics activities. As the main implication for practice, the research suggests a strategic use of outsourcing during the three disaster phases. The authors acknowledge that business objectives, risks, stakeholder agendas and requirements, as well as costs play a vital and changing role for outsourcing decision-making during the three disaster stages. The managerial implications arising from the research can provide support to commercial LSPs and HOs that initiate or develop strategic outsourcing relationships.

This study covers the gap in the humanitarian literature related to context-specific factors of outsourcing in humanitarian logistics by empirically investigating the phenomenon. This is one of the first studies that empirically investigate the potential of outsourcing of humanitarian logistics activities throughout the disaster phases.

This study aims to explain the importance of human resources and attempts to identify the competencies required by the personnel involved in disaster management operations.

The research uses a qualitative methodology to explore the competencies required by the relief workers using a content analysis approach to analyze the disaster literature and the job advertisements. The data for the content analysis was developed with the help of 23 independent coders, and exploratory inferences were drawn.

A detailed review of the literature highlighted the importance of competent personnel in disaster relief organizations. The analysis listed 34 mutually exclusive competencies and their relative importance, which were further divided into four competency clusters. The study also creates a competency dictionary that defines the competencies with the expected behaviors.

Deploying the right resources in the acute time frame during a disaster event can make a difference, and with lives at stake, such deployment acquires prime importance. In addition to contributing to humanitarian logistics literature, the competency model developed will also help forecast the future requirements and help the organization choose “the right person for the right job.”

The inferences drawn in the study are based on disaster management areas, unlike earlier research which also considered business logistics research.

The purpose of this paper is to maximize the total demand covered by the established additive manufacturing and distribution centers and maximize the total literal weight assigned to the drones.

Disaster management or humanitarian supply chains (HSCs) differ from commercial supply chains in the fact that the aim of HSCs is to minimize the response time to a disaster as compared to the profit maximization goal of commercial supply chains. In this paper, the authors develop a relief chain structure that accommodates emerging technologies in humanitarian logistics into the two phases of disaster management – the preparedness stage and the response stage.

Solving the model by the genetic and the cuckoo optimization algorithm (COA) and comparing the results with the ones obtained by The General Algebraic Modeling System (GAMS) clear that genetic algorithm overcomes other options as it has led to objective functions that are 1.6% and 24.1% better comparing to GAMS and COA, respectively.

Finally, the presented model has been solved with three methods including one exact method and two metaheuristic methods. Results of implementation show that Non-dominated sorting genetic algorithm II (NSGA-II) has better performance in finding the optimal solutions.

This study aims to help understand individual donors’ preferences over different designs of humanitarian–business partnerships in managing humanitarian operations and to help understand if donors’ preferences align with their actual donation behavior.

Choice-based conjoint analysis was used to understand donation preferences for partnership designs, and a donation experiment was performed using real money to understand the alignment of donors’ preferences with actual donation behavior.

The results show that partnering with the business sector can be a valuable asset for humanitarian organizations in attracting individual donors if these partnerships are managed well in terms of partnership strategy, partnership history and partnership report and disclosure. In particular, the study finds that the donation of services and products from businesses corporations to humanitarian organizations are preferable to individual donors, rather than cash. Furthermore, donors’ preferences are not necessarily aligned with actual donation behavior.

The results highlight the importance of presenting objective data on projects to individual donors. The results also show that donors value the provision of services and products by business corporations to humanitarian operations.

Partnerships between humanitarian organizations and business corporations are important for the success of humanitarian operations. However, little is known about which partnership designs are most preferable to individual donors and have the biggest chance of being supported financially.

The aim of this paper is to conduct a systematic literature review to understand the state of the art of partnerships between humanitarian organizations and business corporations in managing humanitarian logistics.

A systematic literature review is conducted based on the steps proposed by Denyer and Tranfield (2009). The context-intervention-mechanism-outcome (CIMO) logic is applied to identify the state of the art of partnerships between humanitarian organizations and business corporations in humanitarian logistics. Thirty-six papers related to the topic are extracted from recognized journal databases and then classified into four categories based on the CIMO logic: situational context, intervention factors, mechanisms and outcomes.

The study shows that while the context and mechanisms for developing cross-sector partnerships between the humanitarian and the business sector have been examined and illuminated by many researchers, additional research (in particular, empirical studies) is needed to measure outcomes as well as the contributions of partnerships to the performance of humanitarian logistics. In addition to synthesizing the literature in this area, this study also presents challenges of such partnerships.

The study improves the understanding of the state of cross-sector partnerships in humanitarian logistics as well as identifies opportunities for future research in this area. The study provides reasons and motives of initiating humanitarian–business partnerships in humanitarian logistics as well as their mechanisms and potential outcomes. This may help in developing successful logistics partnerships with each other.

This is the first systematic literature review to examine the nature of partnerships between humanitarian organizations and business corporations in humanitarian logistics using CIMO logic.

Unforeseen events can disrupt the operational process and negatively impact emergency resources optimization and its supply chain. A limited number of studies have addressed risk management issues in the context of emergency supply chains, and this existing research lacks inbuilt and practical techniques that can significantly affect the reliability of risk management outcomes. Therefore, this paper aims to identify and practically analyze the specific risk factors that can most likely disrupt the normal functioning of the emergency supply chain in disaster relief operations.

This paper has used a three-step process to investigate and evaluate risk factors associated with the emergency supply chain. First, the study conducts a comprehensive literature review to identify the risk factors. Second, the research develops a questionnaire survey to validate and classify the identified risk factors. At the end of this step, the study develops a hierarchical structure. Finally, the research investigates the weighted priority of the validated risk factors using the fuzzy-analytical hierarchy process (FAHP) methodology. Experts were required to provide subjective judgments.

This paper identified and validated 28 specific risk factors prevalent in emergency supply chains. Based on their contextual meanings, the research classified these risk factors into two main categories: internal and external risk factors; four subcategories: demand, supply, infrastructural and environmental risk factors; and 11 risk types: forecast, inventory, procurement, supplier, quality, transportation, warehousing, systems, disruption, social and political risk factors. The most significant risk factors include war and terrorism, the absence of legislative rules that can influence and support disaster relief operations, the impact of cascading disasters, limited quality of relief supplies and sanctions and constraints that can hinder stakeholder collaboration. Therefore, emergency supply chain managers should adopt appropriate strategies to mitigate these risk factors.

This study will contribute to the general knowledge of risk management in emergency supply chains. The identified risk factors and structural hierarchy taxonomic diagram will provide a comprehensive risk database for emergency supply chains.

The research findings will provide comprehensive and systemic support for respective practitioners and policymakers to obtain a firm understanding of the different risk categories and specific risk factors that can impede the effective functioning of the emergency supply chain during immediate disaster relief operations. Therefore, this will inform the need for the improvement of practices in critical aspects of the emergency supply chain through the selection of logistics and supply chain strategies that can ensure the robustness and resilience of the system.

This research uses empirical data to identify, categorize and validate risk factors in emergency supply chains. This study contributes to the theory of supply chain risk management. The study also adopts the fuzzy-AHP technique to evaluate and prioritize these risk factors to inform practitioners and policymakers of the most significant risk factors. Furthermore, this study serves as the first phase of managing risk in emergency supply chains since it motivates future studies to empirically identify, evaluate and select effective strategies that can eliminate or minimize the effects of these risk factors.

Disaster management and humanitarian logistics (HT) play crucial roles in large-scale events such as earthquakes, floods, hurricanes and tsunamis. Well-organized disaster response is crucial for effectively managing medical centres, staff allocation and casualty distribution during emergencies. To address this issue, this study aims to introduce a multi-objective stochastic programming model to enhance disaster preparedness and response, focusing on the critical first 72 h after earthquakes. The purpose is to optimize the allocation of resources, temporary medical centres and medical staff to save lives effectively.

This study uses stochastic programming-based dynamic modelling and a discrete-time Markov Chain to address uncertainty. The model considers potential road and hospital damage and distance limits and introduces an a-reliability level for untreated casualties. It divides the initial 72 h into four periods to capture earthquake dynamics.

Using a real case study in Istanbul’s Kartal district, the model’s effectiveness is demonstrated for earthquake scenarios. Key insights include optimal medical centre locations, required capacities, necessary medical staff and casualty allocation strategies, all vital for efficient disaster response within the critical first 72 h.

This study innovates by integrating stochastic programming and dynamic modelling to tackle post-disaster medical response. The use of a Markov Chain for uncertain health conditions and focus on the immediate aftermath of earthquakes offer practical value. By optimizing resource allocation amid uncertainties, the study contributes significantly to disaster management and HT research.

This article addresses some of the most pressing issues related to climate change and its potential consequences, namely population migration in Southeast Asia. It sheds light on how slow-onset events interact with other variables to limit the ability of people to adapt to stressors through human mobility.

The study adopts an analytical methodology to evaluate the extent to which the planning policy framework addresses these issues within the context of achieving resilient development.

Climate stressors will force millions of people to move within their own countries, while others will be forced to cross international borders, leaving others stranded. Desertification, sea level rise, ocean acidification, air pollution, changing rainfall patterns and biodiversity loss are all examples of slow-onset processes that the author believes will be exacerbated by climate change.

This will exacerbate many existing humanitarian issues, and more people may be forced to flee their homes as a result. This research helps improve the understanding of migration’s social, economic and environmental implications.

The research offers a novel perspective and analysis of the unique migration challenges arising from climate change in the Southeast Asian context.

The purpose of this paper is to review the relevant literature in order to identify trends and suggest some possible directions for future research in the framework of humanitarian aid distribution logistics with accessibility constraints.

The authors developed a systematic literature review to study the state of the art on distribution logistics considering accessibility constraints. The electronic databases used were Web of science, Scopus, Science Direct, Jstor, Emerald, EBSCO, Scielo and Redalyc. As a result, 49 articles were reviewed in detail.

This study identified some gaps, as well as some research opportunities. The main conclusions are the need for further studies on the interrelationships and hierarchies of multiple actors, explore intermodality, transshipment options and redistribution relief goods to avoid severe shortages in some nodes and excess inventory in others, studies of the vulnerability of transport networks, correlational analysis of road failures and other future lines.

The bibliography is limited to peer-reviewed academic journals due to their academic relevance, accessibility and ease of searching. Most of the studies included in the review were conducted in high-income countries, which may limit the generalizability of the results to low-income countries. However, the authors focused on databases covering important journals on humanitarian logistics.

This paper contextualises and synthesises research into humanitarian aid distribution logistics with accessibility constrains, highlights key themes and suggests areas for further research.