What factors influence the adoption and use of dockless electric bike-share? A case study from the Sacramento region

• Key factors affect adoption and use frequency decisions differently. • Bike-related attitudes positively influence bike-share adoption decisions. • Car necessity perceptions negatively affect bike-share use frequency of adopters. • Spatial density of bike availability promotes adoption but not use frequency. • Modeling results demonstrate the importance of including attitudes, and how socio-demographics can have both direct and indirect effects on outcomes. Now that dockless electric bike-share systems have become a fixture in major cities in the U.S., it is important to understand why someone chooses to use the service. Beyond socio-demographics, factors such as mode-related attitudes, the social environment, and the availability of the service may influence both its adoption and frequency of use. In this study, we modeled dockless electric bike-share adoption and use frequency using data collected from a household survey and a bike-share user survey from the Sacramento region. We used integrated choice and latent variable models to understand the influence of attitudes on electric bike-share adoption and use frequency. We developed three latent variables − bike affinity, car necessity, and bike social environment − using responses to eleven statements. Our models show that apart from socio-demographics, attitudes related to bike affinity and bike social environments significantly and positively influence bike-share adoption with a large effect size, whereas the car necessity attitude significantly and negatively influences the use frequency with a large effect size. Individuals with low incomes are less likely to adopt the bike-share service. The availability of electric bike-share in key locations (home and/or work and/or school) where an individual frequently goes significantly and positively influences adoption with a large effect size but does not influence use frequency. Findings from this study can inform the dockless electric bike-share policies of cities as well as the rebalancing strategies of service providers.