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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.

The purpose of this paper is to explore, analyse and discuss the published concepts of “the customer” and “customer service” in the context of managing international emergency relief chains.

This is a literature‐based approach that extends concepts usually applied in a commercial context to the area of humanitarian aid and emergency relief chains in particular.

Based on the most common associations of the terms in the literature, the paper proposes adopting a customer and customer‐service perspective in managing international emergency relief chains. An understanding of the various perspectives of customers described in this paper provides a starting point in the development of emergency relief chains that can deliver customer service and satisfaction to all concerned.

As managers of emergency relief chains strive to improve the performance of their organizations and supply chains in a highly challenging environment, the paper provides a useful and enhanced understanding of the roles that the “customer” and “customer service” play in their operations strategies. Although it is sometimes assumed that all participants in emergency relief chains are highly co‐operative, this is often not the case. Therefore, the concept of “humanitarian competitive advantage” is also presented to enable a better practical focus for managers of emergency relief chains.

The paper is believed to be the first to apply the terms “customer” and “customer service” systematically in a humanitarian context and thereby propose a customer service perspective in emergency relief chains.

Emergency relief supply chain (ERSC) design is an important strategic decision that significantly affects the overall performance of emergency management activities. The performance of an ERSC can be measured by several performance measures some of which may conflict with each other. The purpose of this paper is to propose an ERSC design framework by simultaneously taking total logistics cost (TLC), risk level, and amount of demands covered in an ERSC into consideration.

The study considers TLC of an ERSC as the sum of logistics cost from distribution warehouses (DWHs) to Break of Bulbs (BOBs) and from BOBs to affected neighborhoods. The risk level of an ERSC is measured by estimating the expected number of disrupted relief items (EDI) distributed from DWHs through BOBs to neighborhoods. The covered demand (CDM) is defined as total populations that are supported in case of an emergency, the populations within the maximal coverage distance (MCD) from relief facilities. Based on these performance measures, the authors formulate a Goal Programming (GP) model to distribute emergency relief items to affected locations. Ideal values of these performance measures are decided, and the GP model seeks to minimize the weighted sum of the percentage deviations of those performance measures from the ideal values. The relationships among performance measures have been thoroughly analyzed through detailed trade-off studies under two realistic case studies by changing weights of each performance measure.

Three performance measures are interdependent over specific values of weights. TLC and EDI have a trade-off relationship when the weight on each measure increases. TLC and CDM also have a trade-off relationship when the weight on EDI increases. However, this relationship becomes less apparent when the MCD increases. EDI and CDM also have the same trade-off relationship when the weight on TLC changes. Therefore, decision makers should thoroughly analyze these trade-off relationships when they design ERSCs. Overall, the study identified that an ERSC with higher MCD outperforms one with lower MCD in terms of TLC, EDI, and CDM.

The study presents a design framework to generate more balanced ERSCs by simultaneously taking three conflicting performance measures into consideration, and demonstrated the feasibility of the framework through realistic case studies. The trade-off analysis provides useful insights and theoretical knowledge to researchers and practitioners in the discipline of emergency logistics management. The results from this study are expected to contribute to the development of more balanced ERSCs.

The purpose of this paper is to discuss the challenges inherent in planning and responding to disaster events in a multi-agency context where numerous governmental and non-governmental actors and agencies are involved in the planning and response phases. In particular, the authors examine a situation where a lead agency has recently been delegated the responsibility for emergency relief logistics and how it might determine and implement best practice.

Adopting an iterative inductive approach, the authors gather data and insights from academic literature, emergency management policies, frameworks and documents and exploratory in-depth interviews with 12 key informants who have considerable experience with the challenges of logistic preparation and response to disasters in a developed country context. The data and context are limited to developed counties, especially the state of Queensland, Australia.

The authors discuss the challenge of achieving coordinated supply chain management where mandated/lead response agencies are required to meet stakeholder and local community expectations and outcomes. From these findings, the authors offer 11 practical recommendations to assist the delivery of best practice in emergency logistics.

Humanitarian logistics is usually examined from a low/middle-income country perspective, yet an efficient and effective disaster response is no less important for developed economies. In this respect, the authors offer a fresh examination of the challenges of delivering best practice for emergency logistics in order to achieve expected community outcomes.

One of the problems in post-earthquake disaster management in developing countries, such as Iran, is the prediction of the residual network available for disaster relief operations. Therefore, it is important to use methods that are executable in such countries given the limited amount of accurate data. The purpose of this paper is to present a multi-objective model that seeks to determine the set of roads of a transportation network that should preserve its role in carrying out disaster relief operations (i.e. known as “emergency road network” (ERN)) in the aftermath of earthquakes.

In this paper, the total travel time of emergency trips, the total length of network and the provision of coverage to the emergency demand/supply points have been incorporated as three important metrics of ERN into a multi-objective mixed integer linear programming model. The proposed model has been solved by adopting the e-constraint method.

The results of applying the model to Tehran’s highway network indicated that the least possible length for the emergency transportation network is about half the total length of its major roads (freeways and major arterials).

Gathering detailed data about origin-destination pair of emergency trips and network characteristics have a direct effect on designing a suitable emergency network in pre-disaster phase.

To become solvable in a reasonable time, especially in large-scale cases, the problem has been modeled based on a decomposing technique. The model has been solved successfully for the emergency roads of Tehran within about 10 min of CPU time.

This study aims to answer the question: What dynamic capabilities do diverse humanitarian organizations have?

We examine this question through the lens of dynamic capabilities with sensing, seizing and reconfiguring capacities. The research team interviewed 15 individuals from 12 humanitarian organizations that had (a) different geographic scopes (global versus local) and (b) different missions (emergency response versus long-term development aid). We also gathered data from secondary sources, including standard operating procedures, company websites, and news databases (Factiva, Reuters and Bloomberg).

The findings identify the operational and dynamic capabilities of global and local humanitarian organizations while distinguishing between their mission to provide long-term development aid or emergency relief. (1) The global organizations, with their beneficiary responsiveness, reconfigured their sensing and seizing capacities throughout the COVID-19 pandemic by pivoting quickly to local procurement or regional supply chains. The long-term development organizations pivoted to multi-year supplier agreements with fixed pricing to counter price uncertainty and accessed social capital with government bodies. In contrast, emergency response organizations developed end-to-end supply chain visibility to sense changes in supply and demand. (2) Local humanitarian organizations developed the capacity to sense demand and supply changes to reconfigure based on their experiential learning working with the local community. The long-term-development local organizations used un-owned and scalable relief infrastructure to seize opportunities to rebuild affected areas. In contrast, emergency response organizations developed their capacity to seize opportunities to provide aid stemming from their decentralized decision-making, a lack of structured procedures, and the authority for increased expenditure.

We propose a theoretical framework to identify humanitarian organizations' operational and dynamic capabilities, distinguishing between global and local organizations and their emergency response and long-term aid missions.

The purpose of this paper is to identify the issues and challenges in humanitarian logistics and to develop a framework for effectively managing the humanitarian logistics in disaster relief supply chain operations in India.

This paper presents a framework to manage humanitarian logistics effectively in disaster management through qualitative analysis. First, the author examines the challenges facing the humanitarian logistics and supply chain through the reviews of the literature on various disasters. Then, the author presented a framework based on the best practices and initiatives taken worldwide in the preparedness and response stage of the humanitarian supply chain to manage and reduce the aftermath of any disaster in context to India.

A framework has been developed to manage humanitarian logistics in the disaster relief operation, which would improve the humanitarian supply chain in India and help to effectively manage natural disasters in the preparedness and response stage at the state and district levels.

The paper mainly emphasises on the preparedness and response stage of disaster supply chain management in Indian context.

None of the disaster incidents can be stopped from taking place, but the impact can be minimised by proper preparedness and effective response during the operations of humanitarian logistics. With this hope, the framework has been developed, which if implemented would help to plan and manage any disaster incident in an effective manner, which ultimately would save millions of lives and cost in terms of infrastructure, property, assets etc.

As natural disaster incidents are occurring frequently in Indian states, there is an urgent need for a framework to manage the logistics operations effectively and efficiently during any disaster relief operations. Limited literature is found on developing and presenting a framework focusing on the preparedness and response phase of disaster supply chain management in context to India. Hence, this paper is believed to be the first to fulfil this gap with main emphasis on the preparedness and response stage of disaster supply chain management in Indian scenario.

Coordinating logistics in the midst of a relief operation is often an overwhelming job that can jeopardise the human life and assets if not done rapidly and practicably. The purpose of this paper is to evaluate the performance of relief logistics in a disaster situation in Ghana with emphasis on the coordination of emergency relief operation and effectiveness of inventory management.

A stratified sampling method was employed to a sample of 134 respondents from regional, district and municipal offices in the National Disaster Management Organisation in Ghana using a self-administered questionnaire.

The findings from this study revealed an effective assessment time but late delivery of relief items. They also revealed issues with respect to resource availability, inventory management and coordination with relief actors which resulted in slow response to affected population.

The result from this study reveals an ineffective disaster relief response. The practical implications of this issue have been highlighted. In addition, ways to effectively address this issue have been discussed.

Drawing insight from previous work and study finding, the paper presents a framework for effective relief logistics operation focussing on all relevant actors in each phase of disaster.

This paper intends to explore and appraise the humanitarian supply chain management enablers (HSCMEs) for efficient and effective humanitarian operations. This research aims to analyze the interaction of enablers for humanitarian supply chain management (HSCM) using a proposed hybrid framework consists of fuzzy Delphi (FD), interpretive structural modeling (ISM)–matriced impacts croises multiplication appliquee a un classement (MICMAC) and revised Simos approach.

This research is deliberate to identify 28 HSCMEs through a literature review and experts' opinions; out of which 20 HSCMEs are selected using FD. ISM is applied to know contextual relationship among the selected HSCMEs for developing a hierarchical model. The MICMAC analysis classifies the HSCMEs based on driving power and dependence power to validate the developed hierarchical ISM structure. The revised Simos technique is used to prioritize the HSCMEs to access its relative significance in humanitarian operations.

The finding of the analysis suggests that government policy and leadership support obtained the highest priority, having high driving power and low dependence power is significantly strategic and emerged as the leading driver for the HSCM implementation.

ISM model presents an insight into interrelationship among HSCMEs, but this cannot quantify the impact of each HSCMEs.

Disaster relief aid agencies and stakeholders may focus on the enablers having high driving power and higher weight in designing and executing an effective and efficient humanitarian supply chain and to improve their activities and strategies of HSCM.

This research helps humanitarian logisticians and humanitarian organizations to make better decisions to improve their operational performance in pre and postdisaster phases.

This paper explores the application of proposed hybrid framework to analyze the HSCMEs that can be considered as the original contribution.

The purpose of this paper is to highlight the importance of property rights institutions to disaster relief efforts, with a focus on the US Federal Emergency Management Agency in the aftermath of Hurricane Katrina in New Orleans, Louisiana.

The paper utilizes public choice, Austrian, and new institutional analyses of bureaucracy. It discusses private and public sector responses to the situation in New Orleans following Katrina and to disasters in general, and compares the institutional frameworks that develop over time in both sectors.

The paper finds that a large and bureaucratized response to disasters hinders economic calculation, incentive structure, and property rights institutions, all of which are crucial for rapid disaster response, the relief of human suffering, the minimization of knowledge problems, and the promotion of an efficient allocation of resources.

This research suggests that the role of the price system in allocating resources is especially important following disasters and that in order to ensure relief efforts are as efficient as possible, public‐sector actors should do nothing to impede them. It also suggests that the incentives to prepare an efficient emergency preparedness program are greater when those most affected by potential disasters are held responsible for their implementation.

The paper provides a critical evaluation of the role of highly centralized approaches to disaster relief.