Enhancing the Resilience of Agri-Food Flow Networks Across Spatial Scales
Advisor: Professor Megan Konar
Abstract
Agriculture and food supply chains are complex systems that incorporate the production, distribution, intermediate processing, and consumption of perishable goods. Their continuous operability is essential to feed humanity. However, agri-food supply chains have become subject to an array of unforeseen threats, such as climate change, pandemics, cyber intrusions, geopolitical conflicts, and economic crises among others. While safeguarding the distribution of agri-food commodities against a set of unforeseen threats is paramount, it is also a challenging goal.
As “affordable and available food for everyone, at all times” ensures a stable economy and civil rest, the proposed research projects recognize agriculture and food supply chains as non-traditional defense objects. This dissertation concentrates particularly on the distribution step of these supply chains (i.e., food flow networks) which serves as the bridge between supply and demand. Here, ensuring resilient agri-food flow networks, thus, food security, is aimed and achieved through introducing descriptive and predictive analytical studies.
In particular, in this dissertation, five interdisciplinary frameworks are developed to cultivate the resilience of the agri-food flow networks across spatial scales. At the U.S. national scale, first, a data-driven statistical model is infused with the gravity model of trade-based linear programming method to estimate the temporal agri-food flows between the U.S. counties. Further, a network component-importance study is conducted by integrating multi-criteria decision-making and applied network science techniques to identify the logistics hubs within the U.S. agri-food supply chains. Lastly, a unified framework of data analytics, network science, and geographic information science is introduced to map agri-food commodity-specific load on the U.S. highways, railways, and waterways, as well as to assess the tradeoff between efficiency, sustainability, and resilience across these transportation modes. Beyond these three national agri-food distribution studies, two other interdisciplinary frameworks are introduced to advance the resilience of agri-food flow networks at global and individual-nation scales. At the global scale, the logistics of agri-food trade is captured and the tradeoff between efficiency and resilience is assessed by developing a complex network framework that is rooted in network connectivity. At the individual-nation scale, the interplay of unit cost, cost volatility, and supply diversity in national grain imports is explored with the modern portfolio theory. A mean-variance optimization model is developed with a mass balance constraint to propose and evaluate the potential for nations to mitigate risks while lowering costs by supplier diversification.
The research efforts within this dissertation contribute detailed agri-food distribution information in a finer resolution to guide decision-making regarding both national and global food security
