Waiting time (WT) is an important measure that can reflect accessibility to ridesourcing service. Previous studies explored the effects of built environment factors on WT based on estimated WT but did not control for trip-level characteristics, which may lead to biased parameter estimation. Thus, we further study this topic by using the actual WT recorded by the RideAustrin platform and considering trip-level variables. The single-level and multilevel proportional hazards models are constructed, and model comparison shows that the multilevel model performs better. We find that waiting time is positively correlated with trip-level characteristics such as traffic conditions, surge multiplier, and rainy weather. Regarding built environment factors, WT is positively related to distance to CBD and negatively related to road density, transit stop density, and land-use entropy. WT is also higher in areas with a high fraction of Hispanic/Latino and Black residents but lower in areas of low income.

等候时间（WT）是一项重要的指标，可以反映出骑行服务的可及性。先前的研究基于估计的WT探索了内置环境因素对WT的影响，但并未控制行程水平特征，这可能导致参数估计有偏差。因此，我们通过使用RideAustrin平台记录的实际WT并考虑行程级别变量来进一步研究该主题。建立了单级和多级比例风险模型，模型比较表明多级模型具有较好的性能。我们发现等待时间与出行级别的特征（如交通状况，浪涌倍增器和阴雨天气）呈正相关。关于建筑环境因素，WT与距CBD的距离呈正相关，与道路密度呈负相关，公交车站的密度和土地利用的熵。在西班牙裔/拉丁美洲裔和黑人居民比例较高的地区，WT较高，而在低收入地区，WT较低。