To Greener Pastures: An Action Research Study on the Environmental Sustainability of Humanitarian Supply Chains

Purpose: While humanitarian supply chains (HSCs) inherently contribute to social sustainability by alleviating the suffering of afflicted communities, their unintended adverse environmental impact has been overlooked hitherto. This paper draws upon contingency theory to synthesize green practices for HSCs, identify the contingency factors that impact on greening HSCs and explore how focal humanitarian organizations (HOs) can cope with such contingency factors. Design/methodology/approach: Deploying an action research methodology, two-and-a-half cycles of collaboration between researchers and a United Nations agency were completed. The first half-cycle developed a deductive greening framework, synthesizing extant green practices from the literature. In the second and third cycles, green practices were adopted/customized/developed reflecting organizational and contextual contingency factors. Action steps were implemented in the HSC for prophylactics, involving an operational mix of disaster relief and development programs. Findings: First, the study presents a greening framework that synthesizes extant green practices in a suitable form for HOs. Second, it identifies the contingency factors associated with greening HSCs regarding funding environment, stakeholders, field of activity and organizational management. Third, it outlines the mechanisms for coping with the contingency factors identified, inter alia, improving the visibility of headquarters over field operations, promoting collaboration and resource sharing with other HOs as well as among different implementing partners in each country, and working with suppliers for greener packaging. The study advances a set of actionable propositions for greening HSCs. Practical implications: Using an action research methodology, the study makes strong practical contributions. Humanitarian practitioners can adopt the greening framework and the lessons learnt from the implementation cycles presented in this study. Originality/value: This is one of the first empirical studies to integrate environmental sustainability and HSCs using an action research methodology

Toward resilient humanitarian cooperation: examining the performance of horizontal cooperation among humanitarian organizations using an agent-based modeling (ABM) approach

This article proposes a multi-agent simulation model to examine how different operational environments and incentive mechanisms affect the collective performance of complex humanitarian response systems. Using the UN Humanitarian Response Depot (UNHRD) system as an example, a stylized model of one service provider, two member organizations and multiple humanitarian crises is developed to illustrate the changing uses of four alternative relief goods sourcing options, namely: i) own storage for own items ii) UN storage for own items iii) stock-swaps and iv) white stock uses. Under the plausible assumption that the past success of sourcing options influences member organizations' future resource allocation, the model indicates that the additional buffer stock capacity offered by horizontal cooperation induces undesirable system dependency: while it gives member organizations more flexibility to meet highly stochastic demands under uncertainty, it also encourage them to store less of their own relief goods as a result. This tendency was particularly notable under a flexible budgeting regime, highlighting the further need to understand and evaluate the details of the decision-making heuristics of individual member organizations

On the dynamic inventory routing problem in humanitarian logistics: a simulation optimization approach using agent-based modeling

80 páginasIn the immediate aftermath of any disaster event, operational decisions are made to relieve the affected population and minimize casualties and human suffering. To do so, humanitarian logistics planners should be supported by strong decision-making tools to better respond to disaster events. One of the most important decisions is the delivery of the correct amount of humanitarian aid in the right moment to the right place. This decision should be made considering the dynamism of the disaster response operations where the information is not known beforehand and vary over time. For instance, the effect of the Word-of-Mouth and shortages in distribution points’ demand can impact the operational decisions. Therefore, the inventory and transportation decisions should be made constantly to better serve the affected people. This work presents a simulation-optimization approach to make disaster relief distribution decisions dynamically. An agent-based simulation model solves the inventory routing problem dynamically, considering changes in the humanitarian supply chain over the planning horizon. Additionally, the inventory routing schemes are made using a proposed mathematical model that aims to minimize the level of shortage and inventory at risk (associated to the risk of losing it). The computational proposal is implemented in the ANYLOGIC and CPLEX software. Finally, a case study motivated by the 2017 Mocoa-Colombia landslide is developed using real data and is presented to be used in conjunction with the proposed framework. Computational experimentations show the impact of the word-of-mouth and the frequency in decision making in distribution points’ shortages and service levels. Therefore, considering changes in demand over the planning horizon contributes to lowering the shortages and contributes to making better distributions plans in the response phase of a disaster.Después de la ocurrencia de cualquier desastre se deben tomar decisiones para aliviar a la población afectada minimizando las pérdidas humanas y el sufrimiento. Para ello, los responsables de la logística humanitaria deben contar con robustas herramientas para tomar decisiones acertadas que respondan adecuadamente ante esos eventos. Una de las decisiones más importantes es la entrega de ayuda humanitaria en el lugar, las cantidades y en el momento correcto. La anterior decisión debe ser tomada teniendo en cuenta el dinamismo de las operaciones de respuesta humanitaria en donde la información no es conocida de antemano y varía en el tiempo. Por ejemplo, el efecto del Voz a Voz y la escasez en los puntos de distribución de ayuda humanitaira pueden impactar las decisiones operacionales. Es por lo anterior, que las decisiones de transporte de ayuda humanitaria deben ser realizadas constantemente para servir de una mejor forma a la población afectada. Este trabajo presenta una propuesta de simulación-optimización para tomar las decisiones de ruteo de inventario de ayuda humanitaria de forma dinámica. A través de un modelo de simulación basado en agentes se resuelve dinámicamente el problema de ruteo de inventario considerando cambios en la cadena de suministro humanitaria. Adicionalmente, las decisiones de ruteo de inventario son tomadas mediante un modelo matemático propuesto que busca minimizar el nivel de inventario en riesgo y el nivel de escases simultáneamente. La propuesta computacional es implementada en los programas ANYLOGIC y CPLEX. Finalmente mediante un caso de estudio basado en la catastrofe de Mocoa-Colombia en 2017 se evaluará la propuesta. Experimentos computacionales muestran el impacto del voz-a-voz y frecuencia de toma de decisiones en la escasez y el nivel de servicio en los puntos de distribución. Por lo tanto, considerar cambios en la demanda contribuye a disminuir la escasez y hacer mejores esquemas de distribución de ayuda humanitaria.Maestría en Diseño y Gestión de ProcesosMagíster en Diseño y Gestión de Proceso

The roles of artificial intelligence and knowledge management in emergency telecommunications

Over the past decade, the international community has recognized the substantive role modern telecommunications can play in disaster relief operations and humanitarian actions.The Tampere Convention on “Emergency Telecommunications” was an initiative to facilitate these activities, endorsed by various international conferences.The role of artificial intelligence and knowledge management in emergency telecommunications could be tremendous, with applications potentially ranging from network and workflow management to training and decision support.In the future, a greater convergence among different technologies, artificial intelligence and knowledge management included, in the service of emergency telecommunications could be foreseen, thus achieving the noble goal of utilizing modern information and communications technologies for disaster mitigation

Simulation-based Assessment of Hyperconnected Humanitarian Supply Chains Response Readiness

The escalating disasters and increasingly complex external environment are forcing humanitarian organizations to continually improve their operations to provide better humanitarian relief. Transformation towards hyperconnected humanitarian supply chains is one of the most promising paths and the Physical Internet could provide a paradigm for this evolution. However, the impact of this shift on the humanitarian supply chain's performance, particularly readiness, has been understudied. To address this issue, a simulation-based assessment of hyperconnected humanitarian supply chains' response readiness is conducted. Different combinations of multiple potentials of the Physical Internet are simulated, and the corresponding effects on relief operations are analyzed. The findings of this work provide greater insight into the transformation towards hyperconnectivity and thus are helpful for decision-makers to design appropriate evolutionary avenues for today's humanitarian supply chains

The Stochastic Dynamic Post-Disaster Inventory Allocation Problem with Trucks and UAVs

Humanitarian logistics operations face increasing difficulties due to rising demands for aid in disaster areas. This paper investigates the dynamic allocation of scarce relief supplies across multiple affected districts over time. It introduces a novel stochastic dynamic post-disaster inventory allocation problem with trucks and unmanned aerial vehicles delivering relief goods under uncertain supply and demand. The relevance of this humanitarian logistics problem lies in the importance of considering the inter-temporal social impact of deliveries. We achieve this by incorporating deprivation costs when allocating scarce supplies. Furthermore, we consider the inherent uncertainties of disaster areas and the potential use of cargo UAVs to enhance operational efficiency. This study proposes two anticipatory solution methods based on approximate dynamic programming, specifically decomposed linear value function approximation and neural network value function approximation to effectively manage uncertainties in the dynamic allocation process. We compare DL-VFA and NN-VFA with various state-of-the-art methods (exact re-optimization, PPO) and results show a 6-8% improvement compared to the best benchmarks. NN-VFA provides the best performance and captures nonlinearities in the problem, whereas DL-VFA shows excellent scalability against a minor performance loss. The experiments reveal that consideration of deprivation costs results in improved allocation of scarce supplies both across affected districts and over time. Finally, results show that deploying UAVs can play a crucial role in the allocation of relief goods, especially in the first stages after a disaster. The use of UAVs reduces transportation- and deprivation costs together by 16-20% and reduces maximum deprivation times by 19-40%, while maintaining similar levels of demand coverage, showcasing efficient and effective operations

A Novel Approach to Include Social Costs in Humanitarian Objective Functions

Social cost functions in humanitarian operations are defined as the sum of logistics and deprivation costs. They are widely regarded as appropriate objective functions, even though the way they were introduced requires cautiously formulated deprivation cost functions for the analyzed goods and do not allow decision makers to include their individual preferences. We develop this approach further and introduce a normalized weighted sum approach to increase decision makers\u27 understanding of the tradeoffs between cost and suffering and, therefore, increase transparency significantly. Furthermore, we apply the approach to a case study of a hypothetical water system failure in the city of Berlin. We show that the normalized weighted sum approach significantly improves transparency and leads to a deeper understanding of the tradeoffs during the crisis. Consequently, it proved itself as a powerful tool for decision makers preparing for or navigating through a crisis

Factors Impacting Supply Chain Performance During Humanitarian Assistance/Disaster Response Operations

This study explored the factors that affect supply chain performance during humanitarian assistance and disaster response operations. We examined the following theoretical coordination nodes, resource sharing, standardization of operations, joint logistics effort, and postponement on humanitarian supply chain performance. We collected survey data from 207 military and civilian logistics practitioners. Data were used to test a conceptual model, using linear regression with each direct effect relationship and moderating relationship tested. Results reveal the positive direct effect of standardization of operations and joint logistics effort on supply chain performance. However, standardization of operations’ effect on supply chain performance is weakened by the moderating effect of resource redundancy. Results inform future military and civilian humanitarian assistance actors on the effects of studied coordination nodes on supply chain performance. We include implications and recommendations for further research