Modeling the values of private sector agents in multi-echelon humanitarian supply chains

© 2018 Elsevier B.V. Humanitarian organizations (HOs) increasingly look to engage private sector supply chains in achieving outcomes. The right engagement approach may require knowledge of agents' preferences across multi-echelon supply chains to align private sector value creation with humanitarian outcomes. We propose a multi-attribute value analysis (MAVA) framework to elucidate such preferences. We formalize this approach and apply it in collaboration with a HO pilot aiming to facilitate better private sector availability of malaria rapid diagnostic tests in Uganda. We demonstrate how HOs could use criteria weights and value functions from MAVA for project evaluation; in the process, we reveal business model insights for importers, distributors, and retailers in the pilot. We also show how MAVA facilitates the impact assessment of hypothetical options (i.e., combinations of products, services, and subsidies) to guide HO resource deployment. This paper offers the first attempt, to our knowledge, to develop quantitative measures for economic and non-economic objectives involving all agents in a multi-echelon supply chain, either humanitarian or commercial. We hope that this initial step stimulates further research to validate results and develop the framework proposed

Games for a new climate: experiencing the complexity of future risks

This repository item contains a single issue of the Pardee Center Task Force Reports, a publication series that began publishing in 2009 by the Boston University Frederick S. Pardee Center for the Study of the Longer-Range Future.This report is a product of the Pardee Center Task Force on Games for a New Climate, which met at Pardee House at Boston University in March 2012. The 12-member Task Force was convened on behalf of the Pardee Center by Visiting Research Fellow Pablo Suarez in collaboration with the Red Cross/Red Crescent Climate Centre to “explore the potential of participatory, game-based processes for accelerating learning, fostering dialogue, and promoting action through real-world decisions affecting the longer-range future, with an emphasis on humanitarian and development work, particularly involving climate risk management.” Compiled and edited by Janot Mendler de Suarez, Pablo Suarez and Carina Bachofen, the report includes contributions from all of the Task Force members and provides a detailed exploration of the current and potential ways in which games can be used to help a variety of stakeholders – including subsistence farmers, humanitarian workers, scientists, policymakers, and donors – to both understand and experience the difficulty and risks involved related to decision-making in a complex and uncertain future. The dozen Task Force experts who contributed to the report represent academic institutions, humanitarian organization, other non-governmental organizations, and game design firms with backgrounds ranging from climate modeling and anthropology to community-level disaster management and national and global policymaking as well as game design.Red Cross/Red Crescent Climate Centr

Elements for European logistics policy - A discussion paper

Following a Finnish initiative the European Commission is preparing a communication on logistics in 2006. To support the preparations Finland arranged the so called EULOC-process in which logistics experts from different countries were invited to participate. First, an industry foresight of European logistics in 2015 was created. Next, the mission, vision and policy priorities of the European logistics policy were discussed. The mission for European logistics policy was created from the viewpoint of citizens, companies, states and Europe. Seven vision elements were created. The driving visions are “Seamless systems” and “Intelligent regulation”. The guiding and enabling visions are “Resources” and “Cost efficiency”. The outcome visions are “Europe’s competitiveness”, “Equal business opportunity” and “Sustainability”. According to the experts’ views the priority areas of European logistics policy are Infrastructure – Seamless systems require investments Research, development and training – Strengthen the competitiveness of the European Union Enterprises – The reinforcement of logistic industry Regulation – Innovative and intelligent Cost Efficiency – Effective logistics Sustainability – From environmental, social and economic viewpoint, a must in modern logistics Co-Operation – A strategic issue in network society Public-Private Partnership – Agile solutions for investments

Integrated supply chain design

Ph.D.H. Donald Ratlif

Stochastic Analysis of Logistics Capacity in Disaster Response Networks

Quickly deploying relief items is key to reducing a population’s burden in case of sudden onset disasters. Emergency response organizations, such as FEMA or local and state agencies hold a strategic stockpile of critical relief items and contract for contingency stock in preparation for emergencies. Their response capacity depends on their decision to stock items at different depots, contracts with contingency suppliers, and procurement of transportation capacity to move these items. Building on prior work of Acimovic & Goentzel (2016) we develop a stochastic linear programming model to capture carrier capacity and contingency suppliers. Inputs to the model are a risk portfolio reflecting the particular disasters and the inherent uncertainty with respect to when an organization needs to address a large or a small disaster. Further inputs are the organic stockpile of critical relief items, referred to as the inventory portfolio, contracts with contingency suppliers, which we term the supplier portfolio, and the portfolio of carriers at any depot location. The model allows to conduct a system assessment and a system optimization. System assessment evaluates the current state and answers how well the current inventory, supplier, and carrier portfolio is able to meet a given risk portfolio. We present aggregate metrics to assess a system in three dimensions. We evaluate service metrics to answer how well the network meets demand of the affected population and how rapidly we reach the affected population, and efficiency metrics to indicate how much resources are necessary to meet demand. Taken together these metrics allow to evaluate the state of an emergency response network. System optimization identifies the optimal allocation of inventory for a given supplier and carrier portfolio against a given risk portfolio. The models provides the above mentioned metrics for a decision-maker to compare to optimal network to the current on. In addition, we prescribe an inventory balance, a carrier contract, and a carrier utilization metric to capture the value of improvement. In both – system assessment and system optimization – we evaluate a time-based model and a cost-based model to capture the inherent cost-time trade-off. Typically, more responsive suppliers and carriers are more expensive and less responsive suppliers and carriers are less expensive. When choosing where to allocate inventory, and which suppliers and carriers to contract an organization has to resolve this trade-off between cost and time. Our model provides insight into this trade-off and the impact on different performance metrics. We use data from the openFEMA API to construct a new risk portfolio and estimate an inventory and a carrier portfolio to show the feasibility and functionality of our approach.New England University Transportation Center Grant Number: DTRT13-G-UTC3

Data-driven optimization of OFDA's disaster response capacity: Python Source Code

USAI

Supply Chain Resilience: Restoring Business Operations After a Hurricane

MIT’s Humanitarian Response Lab at the Center for Transportation and Logistics (CTL) held a roundtable on supply chain resilience in the face of large-scale disasters. To gather a cross-sectional understanding of the issue, the event convened participants from academia, public sector, and private sector – who brought their respective perspectives to illuminate this crucial intersection of management science, government policy, and business strategy. To ensure candor, this report was prepared under the Chatham House Rule of not identifying the specific speakers or affiliations of the anecdotes, insights, or recommendations. The roundtable used three major hurricanes (Harvey, Irma, and Maria) during 2017 as a focal point for gathering multiple points of view from the public and private sector and spanning supply chains from manufacturer to retailer. The roundtable and this report are aimed to catalyze more systematic research of the issues and opportunities revealed by shared discussion of how business and government support survivors and restore a disaster-impacted economy

Data-driven optimization of OFDA's disaster response capacity: Phase I Report

Data-driven optimization of OFDA’s disaster response capacity: Phase I ReportThe United States Agency for International Development’s (USAID’s) Office of Foreign Disasters Assistance (OFDA) collaborates with the Massachusetts Institute of Technology’s Humanitarian Supply Chain Lab (HUSCL) at the Center for Transportation and Logistics (CTL) in the project “Optimization-based Evaluation of USAID/OFDA’s Global Logistics Capacity”. This collaboration intends to provide data-driven, model-based recommendations to optimize OFDA’s global response capabilities. The project runs from May 2019 until September 2020 and comprises two phases. In Phase I the project team conducted preliminary analyses to develop a deeper understanding of OFDA’s operations and collected the necessary information to conduct the modeling. Also, they used a preliminary model to showcase outputs and recommendations of a more tailored-modeling approach, which is the main focus of Phase II. This summary report highlights important findings and outlines a path forward for Phase II.USAI

Karamoja Resilience Map: The Basic Elements

This guide is for interpreting the Karamoja Resilience System Maps, and provides descriptions of the different element types and connections on the system mapsUSAI