Abstract

The rapid growth of ride-hailing platforms has fundamentally altered urban mobility patterns, creating new competitive dynamics with established public transit systems. This study examines modal preferences using trip-level behavioral data from Santiago, Chile, combining smart card transactions and ride-hailing records to understand how travelers trade off service attributes. Our analysis employs econometric models that address endogeneity in both crowding levels and dynamic pricing through instrumental variables. Results demonstrate that passenger density significantly amplifies travel time disutility, with crowding effects substantially higher than previous stated preference estimates suggest. In this regard, the presence of a premium mobility alternative increases commuters' aversion to crowded conditions. These findings have significant policy implications, as they suggest that in contexts where premium mobility alternatives are available or emerging, capacity planning based on traditional crowding valuations may be inadequate for contemporary urban environments and could result in insufficient public transportation provision.