Modeling Supply Chains and Markets to Support Humanitarian Response Analysis

In a crisis, information about supply chains and markets for essential commodities can be sparse, yet an understanding of them is critical to delivering effective humanitarian assistance. Humanitarian organizations are looking to improve their processes to assess and analyze supply chains and market...

Full description

Bibliographic Details
Main Author: Downing, Tristan
Other Authors: Goentzel, Jarrod
Format: Thesis
Published: Massachusetts Institute of Technology 2022
Online Access:https://hdl.handle.net/1721.1/140417
Description
Summary:In a crisis, information about supply chains and markets for essential commodities can be sparse, yet an understanding of them is critical to delivering effective humanitarian assistance. Humanitarian organizations are looking to improve their processes to assess and analyze supply chains and markets to inform response option analysis. Existing methods remain limited in their consideration of supply chains and markets as inherently dynamic and complex systems; this thesis develops and applies two complementary methods to capture this dynamism and complexity to produce outputs useful for decision-making. The first method, multi-mode information aggregation, involves continuously synthesizing new information from a range of sources to form an understanding of the situation. It was developed and applied to guide United States Agency for International Development (USAID) food security programming to support the maize market system in Uganda in response to the COVID-19 pandemic. A key insight from this application was that female rural traders in border areas may be more significantly affected than other traders. The second method, a system dynamics model, models the behavior of a supply chain for essential commodities in a crisis. It was developed and applied to study the effects of the displacement crisis in Northeast Nigeria on the supply chain for rice in Borno State, and to inform International Committee of the Red Cross (ICRC) processes and response. The model was used to project outcomes for target populations under different scenarios and humanitarian response options, incorporating in-kind assistance, cash assistance, and credit for supply chain actors. A key finding was that when cash assistance is being provided to a broad target population, further humanitarian spending may be significantly more effective as credit to supply chain actors instead of as more cash assistance to the target population. Results from the model also highlighted potential other areas for humanitarian intervention, such as improving access to market information. Broadly, both these methods highlight the need to consider supply chains and markets as complex and dynamic systems that can be disrupted by a crisis and the resulting humanitarian programming, but can also be harnessed to deliver assistance more effectively to people in need.