There are substantial differences in travel behavior by gender on public transit. Studies have concluded that these differences are largely attributable to household responsibilities typically falling disproportionately on women, leading to women being more likely to utilize transit for purposes referred to by the umbrella concept of "mobility of care". In contrast to past studies that have quantified the impact of gender using survey and qualitative data, we propose a novel data-driven workflow utilizing a combination of previously developed origin, destination, and transfer inference (ODX) based on individual transit fare card transactions, name-based gender inference, and geospatial analysis as a framework to identify mobility of care trip making. We apply this framework to data from the Washington Metropolitan Area Transit Authority (WMATA). Analyzing data from millions of journeys conducted in the first quarter of 2019, the results of this study show that our proposed workflow can identify mobility of care travel behavior, detecting times and places of interest where the share of women travelers in an equally-sampled subset (on basis of inferred gender) of transit users is 10% - 15% higher than that of men. The workflow presented in this study provides a blueprint for combining transit origin-destination data, inferred customer demographics, and geospatial analyses enabling public transit agencies to assess, at the fare card level, the gendered impacts of different policy and operational decisions.

翻译：公共交通中的出行行为存在显著的性别差异。研究表明，这些差异很大程度上归因于女性通常承担了不成比例的家庭责任，导致女性更可能使用公交出行，其目的涵盖"照料流动性"这一总括性概念所指代的行为。与以往利用调查和定性数据量化性别影响的研究不同，我们提出一种新颖的数据驱动工作流，该工作流结合了基于个体公交票卡交易的起讫点与换乘推断（ODX）、基于姓名的性别推断以及地理空间分析，作为识别照料流动性出行行为的框架。我们将该框架应用于华盛顿都会区交通管理局（WMATA）的数据。通过分析2019年第一季度数百万次出行数据，本研究结果表明，我们提出的工作流能够识别照料流动性出行行为，并检测到在等量采样（基于推断性别）的公交用户子集中，女性出行者比例比男性高10%-15%的特定时间与地点。本研究提出的工作流为整合公交起讫点数据、推断的客户人口统计特征及地理空间分析提供了蓝图，使公共交通机构能够在票卡层面评估不同政策与运营决策的性别影响。