Bike sharing systems gain traction worldwide, but previous research pay less attention to the more detailed operating characteristics at station level. This study aims to fill this void in the literature by looking into the stations’ performance with considering systemic intervention and user-driven usage. Methodologically, an innovative approach that captures the underlying relevance of trip records is proposed firstly to identify the bicycle-based operating states in its lifecycle, such as being redistributed, parked, or used. From bike to station, all the bicycle-based operating status information can be linked to associated stations, consequently, station vitality and station pattern are refined into stations’ operating performance. In addition to rational classification and discussion of operating features, this study has explored the impact of surrounding built environment on these specific operating features instead of simple trip intensity. To test the proposed methodology, trip record data from the bike sharing system of Boston in 2019 is used. The results indicate that user-driven and manual-scheduling bike movements are all particularly relevant to keeping stations’ sustainable daily operation, but vary across the stations in their ratio. In terms of station vitality and station pattern, some stations would embody the nature of high-output-scheduling, low-bike-turnover, or high-input-scheduling relative to the baseline scenario of operating performance. Heterogeneity of stations in operating is also proved to be caused by the surrounding built environment. The outcomes and methodological framework would facilitate the assessment of bike sharing system operating state at station level, as well as instilling new insights into bike sharing system design.

自行车共享系统在全球范围内受到关注，但之前的研究较少关注站点级别更详细的运行特征。本研究旨在通过考虑系统干预和用户驱动的使用来研究站点的性能，从而填补文献中的这一空白。在方法上，首先提出了一种捕获旅行记录潜在相关性的创新方法，以识别其生命周期中基于自行车的运行状态，例如重新分配、停放或使用。从自行车到车站，所有基于自行车的运营状态信息都可以链接到相关站点，从而将站点活力和站点模式细化为站点的运营绩效。除了合理的分类和操作特点的讨论，本研究探讨了周围建筑环境对这些特定操作特征的影响，而不是简单的出行强度。为了测试所提出的方法，使用了 2019 年波士顿自行车共享系统的旅行记录数据。结果表明，用户驱动和手动安排的自行车运动都与保持站点的可持续日常运营特别相关，但它们的比例因站点而异。在站点活力和站点模式方面，一些站点相对于运营绩效的基线情景会体现出高输出调度、低自行车周转或高投入调度的性质。车站运行的异质性也被证明是由周围的建成环境引起的。