Restaurant meals consumption in California: channel shifts during COVID-19, food justice, and efficient delivery
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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.