This is our second COVID19 related study, completed in 2020 and published in Transportation Research Part A in 2021. You may read  the other one here, which is about optimally adapting transit design and operations in a pandemic.

We examined taxi trajectory data collected in four weeks that cover the onset of COVID19, the shutdown, and phased reopening in the city of Shenzhen. Our analysis revealed how the pandemic and the travel restriction policies affected both the supply and the demand of the taxi market in the city.   One of the more interesting findings is that the city’s stimulus policy, designed to boost taxi supply and help taxi drivers, might have led to oversupply, by inducing taxi drivers to spend more time on the road than what the prevailing market condition would justify.  We uncovered direct evidence from data to support this finding through a clustering analysis.

A preprint is available here.

Abstract: This paper traces the plunge and rebound of the taxi market in Shenzhen, China through the COVID-19 lockdown. A four-week taxi GPS trajectory data set is collected in the first quarter of 2020, which covers the period of lockdown and phased reopening in the city. We conduct a spatiotemporal analysis of taxi demand using the data, and then select taxis that continued to operate through the analysis period to examine whether and how they adjusted operational strategies. We find, among other things: (i) the taxi demand in Shenzhen shrank more than 85% in the lockdown phase and barely recovered from that bottom even after the city began to reopen; (ii) the recovery of taxi travel fell far behind that of the overall vehicle travel in the city; (iii) most taxis significantly cut back work hours in response to the lockdown, and many adjusted work schedule to focus on serving peak-time demand after it was lifted; (iv) taxi drivers demonstrate distinct behavioral adaptations to the pandemic that can be identified by a clustering analysis; and (v) while the level of taxi service dropped precipitately at the beginning, it quickly rebounded to exceed the pre-pandemic level, thanks to the government’s incentive policy. These empirical findings suggest (i) incentives aiming at boosting supply should more precisely target where the boost is most needed; (ii) the taxi market conditions should be closely monitored to support and adjust policies; and (iii) when the demand is severely depressed by lockdown orders or when the market is oversupplied, taxi drivers should be encouraged and aided to use more centralized dispatching modes.