The outbreak of the COVID-19 epidemic has brought enormous impacts and changes to human mobility. To better understand and quantify the impacts of COVID-19 on city-wide ride-sourcing and taxi markets, we present exploratory evidence on the factors such as coronavirus cases related attributes, policy-related attributes, operational status of transportation, socio-economic status related variables, demographics related variables, and other factors. Based on 5-month real-world ride-sourcing and taxi datasets in Ningbo, China, including 37-million trips, we study the temporal variations of drivers' working characteristics and productivity of ride-sourcing and taxi fleets. The spatial heterogeneity of the impacts of COVID-19 on taxi and ride-sourcing trips is demonstrated in terms of traffic analysis zones (TAZs). Regression models are established to examine the impacts of a variety of explanatory variables, including COVID-19 related variables, on the district-level productivity of taxi and ride-sourcing services. The results show that the accumulated cured coronavirus cases, policy of closed management, operational status of mass transit, and average fee spent on transportation per capita significantly impact the productivity of the taxi and ride-sourcing fleets. This paper empirically reveals the influence of the epidemic on ride-sourcing and taxi markets and the temporal and spatial variations. The findings can support decision-making to restore the ride-sourcing and taxi markets and benefit other COVID-19 related research efforts.
Keywords: COVID-19; Productivity analysis; Regression analysis; Ride-sourcing and taxi markets; Spatial heterogeneity.
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