Understanding the Relationships between Demand for Shared Ride Modes: Case Study using Open Data from New York City

The concept of shared travel, making trips with other users via a common vehicle, is far from novel. However, a changing technological climate has laid the tracks for new dynamically shared modes in the form of transportation network companies (TNCs), to substantially impact travel behavior. The current body of research on how these modal offerings impact the demand for existing shared modes (e.g., bikeshare, transit) is growing. However, a comprehensive investigation of the temporal evolution of the demand for TNCs and their relationship to other shared modes, is lacking. This research tackles this important limitation by analyzing ridership data for TNCs, taxi, subway, and Citi Bike in New York City using daily ridership data from January 2015 through June 2017. The primary objective was to understand the relationship between TNCs and other shared modal offerings while accounting for the influence of temporal trends and other exogenous factors. A dynamic linear modeling framework was formulated to accommodate time-dependent trends, periodicity, and time-varying exogenous factors on the demand for TNCs. As a preliminary work, the findings of this study reinforce the observed substitution relationship between taxis and TNCs. The results may also indicate a substitutional relationship between TNCs and Citi Bike, and a complementary relationship with subway, however these results still need to be explored further. With potentially impactful findings for planning and policymakers, the predictive model developed in the study can be used to carry out forecasting in support of short- and long-term operations and planning applications.