This study investigates trip-level destination choice behavior of users of the dockless bike sharing service (DBS). A random parameter latent segmentation-based logit (RPLSL) model is developed utilizing the DBS users’ trip itinerary data for Kelowna, Canada. The RPLSL model captures multi-dimensional heterogeneity such as inter-segment and intra-segment heterogeneity. The model is developed at a micro-spatial resolution which is defined as the bicycle analysis zone. One of the key features of this study is to test the interdependencies between the origin and destination of a trip using their built environment attributes. Model results suggest that segment 1 is more likely to include trips originating from the urban neighborhoods; whereas, segment 2 includes trips originating from the suburban neighborhoods. The parameter estimation results reveal that DBS trips are more likely to be destined to locations with longer length of cycle tracks, higher employment density, and that are closer to the Central Business District and bus stops (i.e., within 500 m). The model confirms multi-layer heterogeneity. For instance, trips originating from the urban areas in segment 1 are more likely to be destined to destinations within 500 m of the designated bike return sites (i.e., havens). In contrast, shorter trips originating in suburban areas in segment 2 show a negative relationship. Interestingly, a bike-friendly environment might increase the attractiveness of destinations closer to havens, even for the trips originating in suburban areas. The findings of this study will assist in developing policies and infrastructure investment decision making at the destination locations to promote DBS usage.

这项研究调查了无底座自行车共享服务（DBS）用户的旅行级别目的地选择行为。利用DBS用户的加拿大基洛纳旅行行程数据，开发了基于随机参数潜在分段的logit（RPLSL）模型。RPLSL模型捕获多维异质性，例如段间和段内异质性。以微观空间分辨率开发模型，该分辨率定义为自行车分析区域。这项研究的关键特征之一是使用其构建的环境属性来测试旅行起点和终点之间的相互依赖性。模型结果表明，路段1更可能包含来自城市社区的旅行；而第2部分则包括来自郊区的旅行。参数估计结果表明，DBS出行更有可能到达自行车道长度较​​长，就业密度较高并且更靠近中央商务区和公交车站（即500 m以内）的位置。该模型证实了多层异质性。例如，来自第1段城市地区的旅行更有可能去往指定自行车归还地点（即避风港）500 m以内的目的地。相比之下，来自段2郊区的较短行程显示出负相关关系。有趣的是，即使是在郊区旅行，自行车友好的环境也可能会增加靠近避风港的目的地的吸引力。