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People are increasingly utilizing electric bike-sharing (e-bike-sharing) for travel as a new mode of shared mobility comparable to bike-sharing. However, few studies have focused on the motivation to switch from bike-sharing to e-bike-sharing and to develop them in tandem. By accommodating socio-demographic, psychosocial, trip, and system attributes, this paper quantitatively estimates the inherent effects across the various attributes affecting e-bike-sharing and bike-sharing choices. Specifically, a web-based stated preference survey is designed to explore people’s preferences for different bike-sharing modes in China. For the empirical study, the data collected is used to create panel random parameters random utility multinomial logit model, and panel random parameters random regret logit model. The model findings are used to perform significance analysis and elasticity comparison. Additionally, for the two model frameworks, we undertake an extensive trade-off analysis between different attributes, which provides useful insights on e-bike-sharing and bike-sharing mode choices (what and how).