2026-10-15T09:47:59Z https://data.mendeley.com/oai

oai:data.mendeley.com/6r6gh3b4s2.1 2024-09-10T07:20:43Z

AGNIHOTRI, PARUL Bicycle Sharing - Post Adoption Intentions Mendeley Data This study explores the post-adoption intentions of users regarding dockless bicycle-sharing services by integrating the Innovation Diffusion Theory (IDT) and Innovation Resistance Theory (IRT). The primary research hypotheses are that various factors (such as compatibility, de-ownership orientation, image barriers, value barriers, usage barriers, perceived scarcity risk, and risk barriers) influence self-efficacy, which in turn affects users' continued use intentions (CUI) and recommendation intentions (RI) of dockless bike-sharing services. Data for this study was collected via a web-based survey conducted in China’s first and second-tier cities, using the Questionnaire Star platform, China's largest survey tool. A total of 358 respondents participated, representing diverse demographic and cultural backgrounds. The survey included questions on compatibility, de-ownership orientation, perceived barriers (such as value, image, and usage barriers), perceived scarcity risk, and self-efficacy related to using dockless bike-sharing services. 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. Sharing Economy Dataset doi:10.17632/6r6gh3b4s2.1 oai:data.mendeley.com/6r6gh3b4s2.1 Creative Commons Attribution 4.0 International http://creativecommons.org/licenses/by/4.0 https://data.mendeley.com/datasets/6r6gh3b4s2 2024-09-10T07:20:43Z