Understanding and Modeling Dynamics of Household Automobile Ownership Decisions: A Canadian Experience

Abstract

The primary objective of this study was to develop a comprehensive dynamic model of household automobile transactions and choices at a disaggregate level to be used in a dynamic microsimulation modeling framework that can provide a direct forecast of consumer demand for personal-use vehicles given the available choices. A market-based decision making process and a transaction approach were applied for this project due to their consistency with the actual processes followed by a decision maker in a real world. The proposed framework has a nested tree with transaction choices (adding new vehicle to fleet, disposing one vehicle, trading one of the vehicles in fleet, or do-nothing decision) in the upper level and class and vintage choices in the lower levels. Different modeling approaches to operationalize such a framework were employed including hedonic price, multinomial logit, nested logit, artificial neural networks, and random parameter logit models.