Aproximación a un modelo multiagente para domiciliarios urbanos

Abstract

Context: There is a need to understand why fast-food couriers cluster in specific points of a city (Bogotá in this case) due to the rise of shared economy applications such as Rappi, Uber Eats, Domicilios.com, and other fast-food delivery apps. Additionally, there is an interest in comprehending the key factors influencing the emergence of these clusters. Method: Information was collected from primary sources and subsequently refined using statistical methods and expert systems, identifying the relevant variables that allowed for the formulation of a model and ultimately determining the appropriate simulation methodology for this case. Results: In contrast to the initial hypothesis that the primary motivation for couriers to gather in specific city points was to maximize the number of orders (income), factors such as safety, convenience, and above all, friendship, proved to be decisive for these agglomerations. Conclusions: The homogeneity of general characteristics among the population working as couriers turns out to be a crucial factor in explaining the emergence of clusters in specific city points.