Publication Detail

What Factors Influence the Adoption and Use of Dockless Electric Bike-Share? A Case Study From the Sacramento Region

UCD-ITS-RP-25-53

Journal Article

National Center for Sustainable Transportation, BicyclingPlus Research Collaborative

Suggested Citation:
Mohiuddin, Hossain, David S. Bunch, Tatsuya Fukushige, Dillon T. Fitch-Polse, Susan L. Handy (2025)

What Factors Influence the Adoption and Use of Dockless Electric Bike-Share? A Case Study From the Sacramento Region

. Transportation Research Part A 199

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.


Key words:

dockless electric bike-share, integrated choice and latent variable model, mode-related latent attitudes, statistical modeling, dockless shared bike availability index