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探索新冠疫情对全市出租车及网约车市场的影响：来自中国宁波的证据

Exploring impacts of COVID-19 on city-wide taxi and ride-sourcing markets: Evidence from Ningbo, China.

作者信息

Yu Jingru, Xie Ningke, Zhu Jiangtao, Qian Yiwei, Zheng Sijing, Chen Xiqun Michael

机构信息

College of Civil Engineering and Architecture, Zhejiang University, Hangzhou, China.

Polytechnic Institute, Zhejiang University, Hangzhou, China.

出版信息

Transp Policy (Oxf). 2022 Jan;115:220-238. doi: 10.1016/j.tranpol.2021.11.017. Epub 2021 Nov 22.

DOI:10.1016/j.tranpol.2021.11.017
PMID:34840441
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8608371/
Abstract

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.

摘要

新冠疫情的爆发给人类出行带来了巨大影响和变化。为了更好地理解和量化新冠疫情对全市网约车和出租车市场的影响，我们提供了关于冠状病毒病例相关属性、政策相关属性、交通运营状况、社会经济地位相关变量、人口统计学相关变量等因素的探索性证据。基于中国宁波5个月的真实世界网约车和出租车数据集（包括3700万次出行），我们研究了网约车和出租车车队司机工作特征和生产率的时间变化。从交通分析区（TAZ）的角度展示了新冠疫情对出租车和网约车出行影响的空间异质性。建立回归模型以检验包括新冠疫情相关变量在内的各种解释变量对出租车和网约车服务区级生产率的影响。结果表明，累计治愈的冠状病毒病例、封闭管理政策、公共交通运营状况以及人均交通费用支出对出租车和网约车车队的生产率有显著影响。本文实证揭示了疫情对网约车和出租车市场的影响以及时空变化。研究结果可为恢复网约车和出租车市场的决策提供支持，并有益于其他与新冠疫情相关的研究工作。

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