Headwind or tailwind? The evolution of bike-sharing and ride-hailing demand during the COVID-19 pandemic

The COVID-19 pandemic has significantly reshaped travel patterns globally, prompting shifts in mobility preferences and behaviors. After controling for temporal trends and weather, this paper investigates the impacts of the pandemic on station-based bike-sharing and ride-hailing services in New York City (NYC), spanning the periods before, during, and after the pandemic. Specifically, we examine how these transportation modes evolved across various land-use types and pandemic periods. To achieve this, we employ a spatial clustering method to group NYC traffic zones into distinct functional areas, i.e., Mixed Area, Commercial Area, Residential Area, and Educational Area, based on land use characteristics. Subsequently, we develop two time series models based on the seasonal autoregressive integrated moving average with exogenous variables (SARIMAX) model to analyze the impact of the pandemic on trip demand across different spatial areas and years. Our modeling analysis enables us to precisely quantify the average effects of pandemic phases on daily trip ridership, while also assessing shifts in daily trip demand trends across each COVID phase, accounting for variables such as land use and weather. Our findings uncover strikingly different recovery trajectories for bike-sharing and ride-hailing services. Bike-sharing rapidly rebounded, surpassing pre-pandemic trip levels by the end of the reopening phase. In contrast, ride-hailing has not yet fully recovered and continues to lag behind its pre-pandemic levels. Moreover, we observe disparities in cycling recovery across various land-use types, with Mixed and Residential Areas exhibiting faster recovery compared to Commercial and Educational zones. The varying recovery patterns can be attributed to evolving traveler sentiments and preferences, shifts in trip needs and purposes, and the implementation of local policies aimed at fostering sustainable transportation options.