Date of Award

Spring 2015

Document Type

Thesis

Degree Name

Master of Science (MS)

Department

Systems Engineering

First Advisor

Davis, Lauren Dr.

Abstract

According to the Centers for Disease Control and Prevention (CDC), one in six Americans become ill or die from foodborne contaminations (CDC, 2011). Contamination (intentional or unintentional) can occur at any point in the food supply chain. Flaws in security, quality control, or transportation are some examples of how food is susceptible to intentional acts of sabotage. Certain foods are more susceptible to contamination such as meats, dairy, fruits, vegetables, and eggs. In order to build a secure and resilient food supply chain network, food producers and manufacturers need to have the ability to assess contamination risks resulting from manufacturing processes. This research quantifies risk as a function of purchasing and consumption frequency of food susceptible to recalls. A survey is constructed and administered to identify consumption and purchasing behavior of high risk foods. Using the data from the survey, a logistic regression model is developed to determine the likelihood of purchasing high risk food items based on shopping behavior and demographic information. Subsequently, a Poisson regression model is developed to predict consumers' consumption frequency. The results of the research will lead to a better understanding of consumer behavior in relation to food choices. Furthermore, understanding purchasing and consumption behavior will enable food producers to design better policies for securing the nation's food supply.

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