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Exploring side effects of ridesharing services in urban China: role of pollution–averting behavior

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Abstract

Ridesharing has become popular over the last decade, bringing significant changes to residents’ travel patterns and city traffic. Relevant to the growth and impact of ridesharing activities in populous urban areas are the side effects, such as air pollution and traffic congestion. Despite a number of studies on these side effects, few have focused on their underlying causes and explained the behavioral incentive. Drawing on the theory of averting behavior, this paper investigates the ridesharing choices of individuals who face but would prefer to avoid ambient air pollution. Such air pollution–averting behavior tends to increase the demand for ridesharing services, which further results in more motorized traffic and pollutant emissions. Utilizing trip records from DiDi company and data on air pollutants in Haikou, China, we find that an additional 10 μg/m3 of PM2.5 leads to an increase of 2.6% in the count of DiDi trip orders. Results also show that traffic congestion increases due to elevated DiDi usage and the effect varies with time. This could further worsen the air quality and bring other potential side effects. These empirical results offer unique insights into the impact of air pollution on ridesharing and traffic from the perspective of individual behavioral motivation.

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Notes

  1. https://mass.streetsblog.org/2020/01/27/fees-on-uber-and-lyft-accelerate-local-sustainable-transport-projects/. In its large cities, China over the last decade has experienced rapid growth in digital ridesharing services [23], [70]. We also examine the potential side effects of ridesharing in the context of urban China.

  2. World Health Organization, Ambient (outdoor) air quality and health: fact sheet. September 2016.

  3. We also include lagged effects more than 30 h later in the model. Results show that estimates after 30 h are not significant and, thus, they are not reported here.

  4. We include other air pollutants in the regression but do not report their coefficients here.

  5. As in Table 5, we include other air pollutants in the regression but do not report their coefficients here.

  6. We include in the regression lagged effects after 6 h. Results show that coefficients after 6 h are not significant, and, thus, they are not reported here.

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Authors and Affiliations

  1. Ohio State University, Columbus, OH, USA

    Jian Chen

  2. School of Agricultural Economics and Rural Development, Renmin University of China, Beijing, China

    Wei Chen

  3. Risk Management Foundation of the Harvard Medical Institution (CRICO), Boston, USA

    Guopeng Yin

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  1. Wei Chen
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Chen, W., Chen, J. & Yin, G. Exploring side effects of ridesharing services in urban China: role of pollution–averting behavior. Electron Commer Res 22, 1007–1034 (2022). https://doi.org/10.1007/s10660-020-09443-y

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