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:在公共交通上的旅行行为存在很大的男女差异。研究表明这些差异主要归因于家庭职责通常落在女性身上,导致女性更容易利用“护理流动性”这一总称所指的公共交通系统。与过去使用调查和定性数据量化性别影响的研究不同,我们提出了一种新的数据驱动工作流,利用先前开发的个体交通支付方式数据推断技术(ODX)、基于姓名的性别推断和地理空间分析作为框架来识别护理流动性旅行行为。我们将这个框架应用到华盛顿都会区交通局(WMATA)的数据中。通过对2019年第一季度数百万次旅程的数据进行分析,本研究的结果表明,我们提出的工作流可以识别护理流动性旅行行为,检测到女性出行人数比男性多10%-15%的等样本子集(基于推断的性别)中感兴趣的时间和地点。本研究提出的工作流提供了一个蓝图,结合公共交通起始-终止数据、推测的客户人口统计数据以及地理空间分析,使公共交通机构能够在车票级别上评估不同政策和运营决策的性别影响。