Understanding the timing of urban morning commuting trips on mass transit railway systems.

The disparity between rapid urbanization and limited service supplies has raised significant societal concerns, such as overcrowding, caused by a surfeit of individuals traveling at the same time. However, our understanding of how people decide the timing of their trips remains incomplete. Here we use anonymized smart card transaction data from mass transit railway (MTR) systems across three cities to study how commuters schedule travel time to arrive at their workplaces on time. We find two metrics—defined to scale commuters' time scheduling preferences by investigating relationships among MTR station entry, exit time and work start time—can well indicate arrival penalty risks (early arrival, late arrival, and no penalty), and is common among varying work start times across different cities. Additionally, we explore the varying attractiveness of origin–destination (OD) station pairs to commuters with a rank-flow approach and we develop a realistic determinant to measure the penalty risks with the time reserved for the last-mile trip. Our findings verify theoretical bottleneck models, aid in the understanding of distribution of commuting demand and land uses, and support policy making, such as flexible working-hour policies for peak demand managements. • Introduce two key trip metrics to scale commuters' time scheduling preferences. • Investigate the relationship among commuters' mass transit railway (MTR) station entry, exit and work start time. • Understand commuters' aversions to the arrival penalty risks. • Verify the theoretical bottleneck models with smart card transaction data. [ABSTRACT FROM AUTHOR]