Exploring urban commuting imbalance by jobs and gender

Previous findings support that distance matters for job access. Typically, long distances act negatively on job access either due to the lack of information about the opportunities or the cost (time, transportation, etc.). Disparities in job access are explained with the workers’ demographic and socioeconomic characteristics and their spatial condition. Nevertheless, job access was not fully explored in multi-dimensional ways because of data and computational limitations. Recently, the wealth of commuting data, combined with the growing capacity of computation and methodological development, enables us to examine more commuting pattern details than what existing data provide at an aggregate level. This study uses a disaggregate journey-to-work model on 2000 Census Transportation Planning Package (CTPP) commuting data to investigate access to job by gender and occupation, in a more localized context. To explore this varying degree of job access and associated explanation, we analyzed disaggregate commuting flows and ran a regression model on them. This study has three main objectives: (1) to disaggregate journey-to-work flows by gender and occupation to estimate the number of commute trips between census tracts, (2) to explore the variations in job access by gender and occupation, and (3) to draw relationships between job access and various worker’s situations. The results show the details of commuting patterns, suggesting that some occupations have more gender imbalance than others. Further, the findings indicate that the same demographic, socioeconomic and spatial conditions have different effects on workers, and the effect is related to the workers’ demographic-socioeconomic status in complex ways. Unlike conventional research in which a particular worker group is compared to a control group of opposite characteristics, our methodology makes it possible to examine an overview of all the job and gender groups, providing advantages in 2-way comparisons between gender and occupation groups beyond a conventional comparison between two groups. Therefore, our study adds an additional dimension to the conventional comparison.

► We model disaggregate journey-to-work flows by gender and occupation of workers. ► We explore variations of job access for commuters. ► We draw relationships between job access and various worker's situations. ► Commutes between occupation groups vary more than those between gender groups. ► Our methodology examines an overview of all the job and gender groups.