Two essays on food manufacturer resilience: regional factors and workforce challenges
Abstract
Researchers and policymakers worldwide have increasingly viewed resilient food systems as important. In the wake of the COVID-19 pandemic, there has been particular emphasis on food manufacturer resilience. This thesis investigates factors related to food manufacturer resilience. The first study defines resilience through a workforce lens. Utilizing logit models and Firth's penalized maximum likelihood estimation, it examines what drives worker shortages. Results suggest that food manufacturing plants prioritizing training and education face reduced odds of worker shortages. Additionally, results suggest plants view automation as a way to mitigate worker shortages, but that this strategy may not be effective. The second study defines resilience through a plant survival lens. Using Cox proportional hazards models, it explores what factors are related to meat processing plant survival, particularly small- and medium-sized plant survival. Results suggest that the relationship with survival is strongest and most robust for plant characteristics. This holds especially true for small- and medium-sized processors. However, local labor market characteristics are also related to plant survival. Specifically, probability of survival is higher where the county manufacturing employment share is higher, where plants are relatively remote, and where unemployment is lower, all else being equal. Overall, the two essays examine food processor resilience in largely different contexts -- one with detailed survey data and only in Missouri, the other national with high-level plant data -- but two themes do emerge: workforce factors matter for resilience, and plant-level factors matter for resilience. Results of the two essays have important implications, suggesting practices that may help both business managers as well as policymakers strengthen food manufacturer resilience.
Degree
M.S.