LanguageTerm (authority = ISO 639-3:2007); (type = text)
English
Abstract (type = abstract)
New Jersey is known as the Garden State for its dynamic, thriving food production industry that runs the gamut from vegetable growing to sophisticated manufacturing operations. Today New Jersey has a thriving $126 billion food industry and agriculture sector that grows every day. With such a vast and complex system, the food supply chain in New Jersey is vulnerable because a single disruption to one element could spread out and bring huge impact to the entire system. Such a ripple effect may have a tremendous impact on not only the state’s economy and job market, but also the state’s security, vulnerability, and resiliency. Food supply chain risks may occur naturally, intentionally, or accidentally. No matter how a risk originates, it may propagate along the connected members and then impact the entire network. Hence, it is critical to identify the risks in the New Jersey food supply chain and analyze their impacts. Understanding how risks propagate through the network will provide us with important insights into vulnerability assessment for the critical assets in the New Jersey food supply chain. Risks can then be better controlled, mitigated, and prepared for.
This thesis first introduces the current status of the New Jersey food supply chain and then reviews the existing studies on supply chain risk modeling and propagation. To identify the critical assets in the New Jersey food supply chain and their relationship, the important nodes, links, risks, and failure probabilities are analyzed. The New Jersey food supply chain is then configured with 293 nodes. A new model for risk propagation is developed based on the traditional virus propagation models. The proposed model is then implemented in simulation for the New Jersey food supply chain network. Simulation results demonstrate how risks propagate through the network and which assets are the most critical ones in the New Jersey food supply chain. Future efforts will be devoted to more simulation analysis and improving the risk propagation model.
Subject (authority = RUETD)
Topic
Industrial and Systems Engineering
Subject (authority = LCSH)
Topic
Food supply -- New Jersey -- Risk assessment
Subject (authority = LCSH)
Topic
Food supply -- New Jersey -- Risk management
RelatedItem (type = host)
TitleInfo
Title
Rutgers University Electronic Theses and Dissertations
I hereby grant to the Rutgers University Libraries and to my school the non-exclusive right to archive, reproduce and distribute my thesis or dissertation, in whole or in part, and/or my abstract, in whole or in part, in and from an electronic format, subject to the release date subsequently stipulated in this submittal form and approved by my school. I represent and stipulate that the thesis or dissertation and its abstract are my original work, that they do not infringe or violate any rights of others, and that I make these grants as the sole owner of the rights to my thesis or dissertation and its abstract. I represent that I have obtained written permissions, when necessary, from the owner(s) of each third party copyrighted matter to be included in my thesis or dissertation and will supply copies of such upon request by my school. I acknowledge that RU ETD and my school will not distribute my thesis or dissertation or its abstract if, in their reasonable judgment, they believe all such rights have not been secured. I acknowledge that I retain ownership rights to the copyright of my work. I also retain the right to use all or part of this thesis or dissertation in future works, such as articles or books.