Restaurant meals consumption in California: channel shifts during COVID-19, food justice, and efficient delivery
This dissertation explores the evolving landscape of prepared food consumption, particularly restaurant meals, and proposes optimization strategies for managing delivery fleets. In the context of COVID-19, I examined shifts in meal consumption in California using Heterogeneous ordered logit models. I analyzed meal delivery, uncovering unique dynamics across regions and times and emphasizing the role of deliveries in enhancing food access for marginalized communities. Using graph theory, I also explored fleet management optimization, comparing Hopcroft-Karp and Karp algorithms. This research informs policy interventions, aids platform operators, restaurant owners, and urban planners, and bridges academia and practice through an interdisciplinary lens.