Bicycle Sharing - Post Adoption Intentions

Participants were also asked about their intentions to continue using and recommending these services. The data was analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM), a robust method for examining complex relationships between latent variables. PLS-SEM was chosen due to its suitability for exploratory research in less-studied areas, such as bicycle-sharing practices.

The analysis proceeded in two stages: first, evaluating the measurement model for reliability and validity, and second, examining the structural model to assess relationships between latent variables. The study finds that self-efficacy is a critical factor in the continued use and recommendation of dockless bike-sharing services. Positive influences on self-efficacy include the service's compatibility with users' lifestyles and a de-ownership orientation, while negative influences include perceived scarcity, usage barriers, and value concerns.

Interestingly, concerns about social status (image barriers) can also enhance self-efficacy if addressed effectively. The data suggests that service providers should focus on improving compatibility, promoting the benefits of de-ownership, ensuring bike availability, and reducing practical barriers. For urban planners, creating supportive environments with dedicated infrastructure and policies can further foster adoption and sustained use of bike-sharing services.