Socio-economic Characteristics, Current Technology Use, and Willingness-to-Pay for Connected Vehicles: A Structural Equation Modeling Approach

This study answered an important question: “Which population groups are the first targets for diffusion of connected vehicles (CVs)?” Using a survey of drivers’ willingness-to-pay for CV technologies, attributes of potential early adopters of CVs were identified. It was hypothesized that certain personal characteristics and individuals’ current use of in-vehicle technology are related to their acceptance level (i.e., willingness-to-pay). To test the hypothesis, a structural equation model (SEM) was built. Two statistically significant fitted models were identified. The first structure model suggested that high-income individuals using recent in-vehicle safety, information, and entertainment technologies should be targeted at the earliest stage of CV deployment. The second structure model indicated that drivers who highly value vehicle safety, especially females, are likely to have a higher willingness-to-pay for CVs. These findings provide broader policy implications to facilitate faster diffusion of CVs. That is, targeting potential early adopters with attributes identified in this study would enhance CV adoption rates and bring about a “contagion” effect.