Resilient agri-food flow networks across spatial scales

Agriculture and food supply chains incorporate the production, distribution, intermediate processing, and consumption of perishable goods. These complex systems are essential to feed humanity. However, they have become subject to unforeseen threats, such as climate change, pandemics, cyber intrusions, geopolitical conflicts, and economic crises. While safeguarding the distribution of agri-food commodities 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, this dissertation recognizes agri-food supply chains as non-traditional defense objects. Particularly, the concentration is on their distribution step (i.e., food flow networks) which is the bridge between supply and demand. Here, a better understanding of the resilience characteristics of global, local, and individual nation-level agri-food flow networks is achieved, through descriptive and predictive analytical studies. In this dissertation, a total of five interdisciplinary frameworks are developed to cultivate the resilience of the agri-food flow networks across spatial 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 in Chapter 2. 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. In Chapter 3, a mean-variance optimization model with a mass balance constraint is developed to propose and evaluate the potential for nations to mitigate risks while lowering costs by supplier diversification. Beyond these two national agri-food distribution studies, three other interdisciplinary frameworks are introduced to advance the resilience of agri-food flow networks within the U.S. 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 in Chapter 4. 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 for each food commodity group in Chapter 5. Lastly, in Chapter 6, a unified framework of data analytics, network science, and geographic information science is introduced to map agri-food specific load on U.S. highways, railways, and waterways, as well as to assess the tradeoff between efficiency, sustainability, and resilience across these transportation modes. 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.

Name thesis:degree_name

Ph.D.

Level thesis:degree_level

Dissertation

Discipline thesis:degree_discipline

Civil Engineering

Grantor

University of Illinois at Urbana-Champaign

Year dc:date

2024

Author dc:creator

• Karakoc, Deniz Berfin

Contributors dc:contributor

• Konar, Megan
• Varshney, Lav
• Zhao, Lei
• Puma, Michael

• Agri-food Supply Chains
• Trade
• Resilience
• Efficiency
• Sustainability
• Tradeoff

Statement dc:rights

• Copyright 2024 Deniz Berfin Karakoc

Language dc:language

en, eng

Handle dc:identifier

https://hdl.handle.net/2142/125523

OAI record oai:identifier

https://www.ideals.illinois.edu/oai-pmh?verb=GetRecord&metadataPrefix=etdms&identifier=oai%3Awww.ideals.illinois.edu%3A2142%2F125523