Author
Listed:
- Liu, Jianxiao
- Gu, Hengyu
- Zhou, Lin
- Zhang, Hongmou
- Wang, Luyao
- Yu, Yue
- Liu, Zhewei
Abstract
The development of emerging mobility services, such as ride-hailing, has greatly changed urban mobility modes. However, the whole ride-hailing industry experienced significant disruptions during the COVID-19 pandemic, and there are still few studies investigating the associated lockdown's impacts on income levels and the derived inequality issues concerning disadvantaged stakeholders within the ride-hailing industry. Viewing this gap, this study utilizes a comprehensive dataset from a ride-hailing company in China and investigates the city-wide fluctuations in drivers' income across demographic subgroups during the pandemic. The results show that drivers' income quickly recovered to pre-pandemic levels after the lockdown ended. The income inequality (measured by the Gini Index) among drivers remained stable before and after the lockdown. Counterintuitively, groups that typically face systemic challenges in the workplace (i.e., female and older drivers) experienced less income loss during the lockdown and earned more than male and young drivers in the post-lockdown period. Working efficiencies across demographic subgroups were also found to be similar, and the underlying reason for higher income among female and older drivers is their commensurate working time. These demonstrate the limited long-term impacts of lockdowns on the ride-hailing industry and highlight its inclusivity by showing equal working efficiency and income for all demographic groups. The amount of working time, rather than other demographic factors like gender or age, is the major determinant of income level in the ride-hailing industry. Findings herein empirically investigate the influences of government lockdown regulations on the drivers' benefits and carry significant policy implications: involving potentially unprivileged communities in ride-hailing employment could be considered to promote overall social equality and welfare, especially in the post-COVID recovery era.
Suggested Citation
Liu, Jianxiao & Gu, Hengyu & Zhou, Lin & Zhang, Hongmou & Wang, Luyao & Yu, Yue & Liu, Zhewei, 2024.
"Resilience and recovery: Evaluating COVID pandemic effects on ride-hailing mobility and driver income dynamics,"
Journal of Transport Geography, Elsevier, vol. 117(C).
Handle:
RePEc:eee:jotrge:v:117:y:2024:i:c:s0966692324001108
DOI: 10.1016/j.jtrangeo.2024.103901
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