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Urban rail transit networks provide critical access to opportunities andlivelihood in many urban systems. Ensuring that these services are resilient(that is, exhibiting efficient response to and recovery from disruptions) is akey economic and social priority. Increasingly, the ability of urban railsystems to cope with disruptions is a function of a complex patchwork ofmobility options, wherein alternative modes can complement and fill servicegaps. This study analyzes the role of ridesourcing in providing adaptivemobility capacity that could be leveraged to fill no-notice gaps in railtransit services, addressing the question of distributional impacts ofresilience. Using a natural experiment, we systematically identify 28 majortransit disruptions over the period of one year in Chicago and match them, bothtemporally and spatially, with ridesourcing trip data. Using multilevel mixedmodeling, we quantify variation in the adaptive use of on-demand mobilityacross the racially and economically diverse city of Chicago. Our findings showthat the gap-filling potential of adaptive ridesourcing during rail transitdisruptions is significantly influenced by station-, community-, anddistrict-level factors. Specifically, greater shifts to ridesourcing occurduring weekdays, nonholidays, and more severe disruptions, in community areasthat have higher percentages of White residents and transit commuters, and inthe more affluent North district of the city. These findings suggest that whileridesourcing appears to provide adaptive capacity during rail disruptions, itsbenefits do not appear to be equitable for lower-income communities of colorthat already experience limited mobility options.

Does ridesourcing respond to unplanned rail disruptions? A natural experiment analysis of mobility resilience and disparity