Assessing the equity impacts of transportation systems/policies has become a crucial component in transportation planning. Existing statistical modeling approaches for transportation equity analysis have typically assumed that parameter estimates are constant across all observations and used data aggregated to certain geographic units for the analysis. Such methods cannot capture unobserved factors that are not contained in the dataset, i.e., unobserved heterogeneity, which is likely to be present in the increasingly popular disaggregated datasets. To investigate whether there is unobserved heterogeneity in transportation equity impacts, this study carries out an empirical study focusing on the distribution of individual accessibility to activity locations via bike-sharing in southern Tampa. A disaggregated dataset containing information on individual bike-sharing accessibility and socio-economic factors is modeled with a random parameters logit model that allows for the investigation of possible unobserved heterogeneity. Further, models are estimated using data aggregated to parcel- and TAZ-levels to explore the impacts of data aggregation on model estimation results. The models unveil the unobserved heterogeneity in bike-sharing accessibility among populations in different groups defined by different sociodemographic factors in southern Tampa. These results shed insights into how the inconsistent disparity direction of transportation outcomes across individuals in a population group can be measured from the heterogeneity effects. Finally, a comparison between different models show that to capture such inconsistency, the use of disaggregated data with heterogeneity models is highly recommended for transportation equity analysis.

评估运输系统/政策的公平影响已成为运输规划中的关键组成部分。用于运输资产分析的现有统计建模方法通常假设参数估计值在所有观测值中都是恒定的，并且使用汇总到某些地理单位的数据进行分析。此类方法无法捕获数据集中未包含的未观察因素，即未观察到的异质性，这可能会出现在越来越流行的分类数据集中。为了调查运输公平影响中是否存在未观察到的异质性，本研究进行了一项实证研究，重点研究了在坦帕南部通过自行车共享到达活动地点的个人可及性的分布。使用随机参数logit模型对包含有关单个自行车共享可及性和社会经济因素的信息的分类数据集进行建模，该模型允许调查可能的未观察到的异质性。此外，使用汇总到宗地和TAZ级别的数据来估计模型，以探索数据汇总对模型估计结果的影响。这些模型揭示了坦帕南部南部不同社会人口因素所定义的不同群体中的自行车共享可访问性的异质性。这些结果为如何从异质性效应来衡量人群中个体之间运输结果不一致的差异方向提供了见解。最后，不同模型之间的比较表明，要捕获此类不一致之处，强烈建议将分类数据与异质性模型一起使用来进行运输公平性分析。