ABSTRACT
This predictive analytics research project contemplated a hybrid simulation model, applying system dynamics and agent-based simulation to estimate the demand of cars, utility vehicles, and pick-up trucks in Bogotá (Colombia). The research team analyzed the preferences of the population related to certain vehicles’ attributes, associating them with consumers’ conditions and their environment. The predictive analytics model allows estimating the demand under different scenarios and responds to a population of consumers with specific socio-demographic characteristics in an established macro-economic context. This research contributes to understanding the dynamics of the automotive market and the strategic decision-making processes related to the specification and sale of vehicles.
