In the humanitarian response, multiple decision-makers (DMs) need to collaborate in various problems, such as locating temporary relief distribution centres (RDCs). Several studies have argued that maximising demand coverage, reducing logistics costs and minimising response time are among the critical objectives when locating RDCs after a sudden-onset disaster. However, these objectives are often conflicting and the trade-offs can considerably complicate the situation for finding a consensus. To address the challenge and support the DMs, we suggest investigating the stability of non-dominated alternatives derived from a multi-objective model based on Monte Carlo Simulations. Our approach supports determining what trade-offs actually matter to facilitate discussions in the presence of multiple stakeholders. To validate our proposal, we extend a location-allocation model and apply our approach to an actual data-set from the 2015 Nepal earthquake response. Our analyses show that with the relative importance of covering demands ≤0.4, the trade-offs between logistics costs and response time affects the numbers and locations of RDCs considerably. We show through a small experiment that the outputs of our approach can effectively support group decision-making to develop relief plans in disasters response.@en

Information plays a critical role in humanitarian assistance. It has become a product that is shared for multiple purposes such as situational awareness, decision-making, coordination, reporting, and attracting funding. In the aftermath of sudden onset disasters, humanitarians are constrained with huge workload, time pressure, and uncertainties and thus, information products are often criticized with respect to quality issues. In this paper, we aim at developing an empirically grounded framework that can measure the quality of information products through accuracy, objectivity, completeness, and consistency. We validate the framework with the help of practitioners and apply it to the information products of UN WFP for the 2015 Nepal earthquake response. Our analysis shows that the quality of studied information products could be improved with respect to consistency, accuracy, and objectivity. We discuss the implications of our study and propose future research directions.@en

The efficient and effective response to disasters critically depends on humanitarian supply chains (HSCs). HSCs need to be flexible to adapt to uncertainties in needs, infrastructure conditions, and behavior of other organizations. The concept of ‘network flexibility’ is, however, not clearly defined. The lack of an unanimous definition has led to a lack of consistent understanding and comparisons. This paper makes a threefold contribution: first, it defines the concept of network flexibility for HSC in the context of sudden onset disasters. Second, it proposes a framework to measure network flexibility in HSCs. Third, we apply our framework to the 2015 Nepal earthquake case and provide evidence-based insights regarding how humanitarian organizations can improve network flexibility in HSCs. Our analyses for Nepal case show that delivery, IT support, and fleet criteria have the most influence on flexibility. Also, the application of our framework on the downstream network of nine humanitarian organizations shows low levels of network flexibility in all but one. This finding explains why several disruptions happened in relief distributions during the Nepal response.@en

Humanitarian supply chains (HSCs) play a central role in effective and efficient disaster relief operations. Transportation has a critical share in HSCs and managing its risks helps to avoid further disruptions in relief operations. However, there is no common approach to or culture of risk management that its applicability has been studied through recent cases. This paper incorporates an empirical research design and makes a threefold contribution: first, it identifies in-country transportation risks during Nepal response. Second, we evaluate afore identified risks through an expert driven risk assessment grid. Third, we use our field data to study how some humanitarian organizations in Nepal response used logistics service providers for managing moderate- and high-level transportation risks. In this paper, we use both qualitative and quantitative methods. Our qualitative analysis reveals that some of the most important in-country transportation risks were delivery delays; market fluctuations; insufficient capacity; loss of cargo; cargo decay; unreliable information; and ethical concerns. Our quantitative work shows that while participants categorized the first three risks as high-level, the rest were ranked as moderate-level. More investigation in our field data indicates that using logistics service providers (LSPs) helped humanitarians significantly to manage afore in-country transportation risks during Nepal response. It also improved overall HSC performance with respect to flexibility, effectiveness, efficiency, and responsiveness. While this finding empirically confirms the “tools” role of LSPs for managing in-country transportation risks in response, it implies another role for LSPs; “contributors” to performance improvements.@en

Humanitarian supply chains (HSCs) play a central role in effective and efficient disaster relief operations. Transportation has a critical share in HSCs and managing its risks helps to avoid further disruptions in relief operations. However, there is no common approach to or culture of risk management that its applicability has been studied through recent cases. This paper incorporates an empirical research design and makes a threefold contribution: first, it identifies in-country transportation risks during Nepal response. Second, we evaluate afore identified risks through an expert driven risk assessment grid. Third, we use our field data to study how some humanitarian organizations in Nepal response used logistics service providers for managing moderate- and high-level transportation risks. In this paper, we use both qualitative and quantitative methods. Our qualitative analysis reveals that some of the most important in-country transportation risks were delivery delays; market fluctuations; insufficient capacity; loss of cargo; cargo decay; unreliable information; and ethical concerns. Our quantitative work shows that while participants categorized the first three risks as high-level, the rest were ranked as moderate-level. More investigation in our field data indicates that using logistics service providers (LSPs) helped humanitarians significantly to manage afore in-country transportation risks during Nepal response. It also improved overall HSC performance with respect to flexibility, effectiveness, efficiency, and responsiveness. While this finding empirically confirms the “tools” role of LSPs for managing in-country transportation risks in response, it implies another role for LSPs; “contributors” to performance improvements.@en

The growing need for humanitarian assistance has inspired an increasing amount of academic publications in the field of humanitarian logistics. Over the past two decades, the humanitarian logistics literature has developed a powerful toolbox of standardized problem formulations to address problems ranging from distribution to scheduling or locations planning. At the same time, the humanitarian field is quickly evolving, and problem formulations heavily rely on the context, leading to calls for more evidence-based research. While mixed methods research designs provide a promising avenue to embed research in the reality of the field, there is a lack of rigorous mixed methods research designs tailored to translating field findings into relevant HL optimization models. In this paper, we set out to address this gap by providing a systematic mixed methods research design for HL problem in disasters response. The methodology includes eight steps taking into account specifics of humanitarian disasters. We illustrate our methodology by applying it to the 2015 Nepal earthquake response, resulting in two evidence-based HL optimization models.@en

Locating distribution centers is critical for humanitarians in the immediate aftermath of a sudden-onset disaster. A major challenge lies in balancing the complexity and uncertainty of the problem with time and resource constraints. To address this problem, we propose a location–allocation model that divides the topography of affected areas into multiple layers; considers constrained number and capacity of facilities and fleets; and allows decision-makers to explore trade-offs between response time and logistics costs. To illustrate our theoretical work, we apply the model to a real dataset from the 2015 Nepal earthquake response. For this case, our method results in a considerable reduction of logistics costs.@en

Blockchain technology promises to improve the efficiency, transparency, and accountability of humanitarian operations. Yet at the same time, especially the humanitarian context with its characteristic volatility poses unique challenges to any technology. Most prominent are the humanitarian principles that are fundamental to humanitarian operations. These ethical principles are set to protect the most vulnerable populations. Designing blockchain projects in the humanitarian context therefore requires a systematic framework that helps humanitarians make critical choices. While some design instructions can be found for commercial applications, the humanitarian context requires different design principles and guidelines. To address the lack of a design framework for humanitarian blockchain projects, in this paper, we design and validate guidelines for humanitarian blockchain-projects. We use data from two humanitarian blockchain pilots in Jordan and Kenya to design our framework. Thereafter, we benchmark its applicability and relevance against another pilot in Vanuatu. Our framework highlights the need to consider infrastructure, end-users, ethics, stakeholders, and privacy in contexts, scalability and in/out mechanisms in technology, and knowledge/skills and intellectual property in organisation-related design requirements.@en

Purpose This paper proposes a research design for effective use of qualitative data from field research in a quantitative analysis of humanitarian logistics. Design/methodology/approach Our research design is composed of qualitative and quantitative components. The qualitative part has four steps: preparation, data collection, data combination and analysis, and interpretation. We triangulate qualitative data through semi-structured interviews, observations, document review, and online surveys. We use frequency analysis to map out qualitative data to themes that were identified through literature review and best practices. After combining data from various sources, we apply content analysis and then interpret the findings. Findings The results of implementing our research design for Nepal case show its effectiveness for capturing the complexities of and the relation between variables in disasters. Its workflow and research methods exclusively enable using field insights to test theories, inform models, and find field driven research directions. We demonstrate these findings through examples from our field research after 2015 Nepal earthquake. Research limitations/implications (if applicable) Limitations: our disaster field research was constrained by the typical short time to prepare/conduct the research, lack of access to key informant and, limited sample size. Furthermore, the results of our research are based on one case. Implications: our research design resulted in an effective and a traceable use of field data for addressing challenges that practitioners were experiencing. Therefore, proposed research design can be adopted in future for conducting and empirically grounded research on HL. Practical implications (if applicable) Proposed research design enables developing field informed models that can be used as a decision support system in the immediate response. Original/value In this paper, we explicitly explain how we translated Nepal field work into a model and what the problems were in such settings. @en

As humanitarian organizations are struggling to reach an increasing number of beneficiaries, humanitarian-business partnerships, such as the use of logistics service providers (LSPs), promise to improve effectivity and efficiency of humanitarian assistance. Blockchain-based smart contracts which ensure automation, transparency, and efficiency promise to facilitate partnerships, particularly if trust is low. In this paper, blockchain-based smart contracts are critically examined for their application to humanitarian supply chains (HSCs). We identify various adoption barriers which we categorize into organizational, technological, and environmental. As the use of blockchain-based smart contracts in HSCs is in its early stages, we propose future research propositions and directions that can provide insights into overcoming barriers and challenges of adopting the technology in the humanitarian sector.@en