The Adoption of Connected Autonomous Vehicles and Other Innovations by Freight Transportation Organizations

This thesis presents a disaggregate market penetration model for freight transportation organizations adopting connected autonomous vehicle (CAV) technology and other transportation innovations. Innovation adoption research has largely ignored organizational adoption, and little work has been done to understand or predict the adoption of innovations by freight organizations. Therefore, numerous innovation adoption theoretical and methodological approaches are examined to determine which strategies are most appropriate for freight organizational adoption, with connected autonomous vehicles as a case study. A cellular automata model is generated using the theory of the diffusion of innovations and the principles of the Bass model. The model allows for heterogeneity between organizations by allowing certain model parameters to vary depending on the size of the organizations. The results of the thesis are predictions for the adoption rate of CAVs by freight organizations within Shelby County, TN, a demonstration of the impact of organizational heterogeneity on innovation adoption rates, and a discussion of the benefits and drawbacks of innovation adoption theoretical and methodological approaches