Decrease of Taxi Ridership due to the Impact of COVID-19: A Case Study of New York City

Juan Li, Yicheng Song, Xinan Zhou, Jinjin Yue, Hongtai Yang
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引用次数: 1

Abstract

The outbreak of COVID-19 has greatly impacted all industries of many countries in the world. As an important part of people's daily life, transportation is one of the most severely impacted industries. Taking New York City as an example, this paper explores the decline of taxi ridership due to the COVID-19. The decreased ratio of the actual taxi ridership to the taxi ridership predicted for the no COVID-19 scenario based on historical data is calculated as the dependent variable. The fractional response model is used to study the effect of built environment factors including demographic and socioeconomic, land use, and road-related on the decline of ridership. One model is constructed for each of the four periods, to explore the influence of influencing factors on the dependent variables in different periods. The model results show that the percentage of taxi trips decline is associated with the proportion of high-income people living in the area. The reason could be that these people have more flexible working hours and working places. They can choose to telecommute or travel by private cars to avoid contacting other people during transportation. The analysis of the other factors shows that industrial jobs are related to the low percentage of decline. The model results reveal to us the problem of equity exposed in New York City during the pandemic: limited by jobs(race/income), a portion of citizens are not fully free to choose their travel mode during the pandemic. According to the findings, this paper gives traffic management some policy suggestions. As a result, this study could provide an important reference for policymakers to develop appropriate measures to control the epidemic.
新冠肺炎影响下出租车客流量下降:以纽约市为例
新冠肺炎疫情给世界各国各行各业带来了巨大冲击。交通运输作为人们日常生活的重要组成部分,是受影响最严重的行业之一。本文以纽约市为例,探讨新冠肺炎疫情导致出租车客流量下降的原因。因变量为根据历史数据预测的无新冠肺炎情景下,实际出租车客流量减少率与出租车客流量减少率之比。采用分数响应模型研究了人口、社会经济、土地利用和道路等建筑环境因素对客流量下降的影响。四个时期各构建一个模型,探讨不同时期影响因素对因变量的影响。模型结果表明,出租车出行下降的百分比与居住在该地区的高收入人群比例有关。原因可能是这些人有更灵活的工作时间和工作地点。他们可以选择远程办公或乘坐私家车,以避免在交通中与他人接触。对其他因素的分析表明,工业岗位的下降与低百分比有关。模型结果向我们揭示了大流行期间纽约市暴露的公平问题:受工作(种族/收入)的限制,一部分市民在大流行期间不能完全自由选择自己的出行方式。根据研究结果,提出了交通管理的政策建议。因此,本研究可为决策者制定适当的控制措施提供重要参考。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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