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This paper estimates the social welfare effect of China’s largest online ride-sharing platform. Under the plausible assumption that consumers would change from traditional transportation to online ride-sharing when the marginal benefit of saved time outgrows the additional cost, we calculate the distribution of implied wage rate of passengers. We then use the passenger wage rate to calculate the social welfare generated by the decrease in waiting time and the reduction of waiting uncertainty brought about by the ride-sharing platform. Our estimate suggests that the ride-sharing platform created a total of 130.5 billion Yuan of social welfare in the three years between 2016 and 2018, and the consumer surplus and producer surplus created by an average transaction are 5.4 Yuan and 2.5 Yuan, respectively. The robustness test finds that our results were insensitive to the assumed risk aversion coefficient in the model, the subsample number used for each city, and the inclusion of nonlinear terms in the model. Alternative hypotheses, such as learning effect, seem unable to explain our result. [ABSTRACT FROM AUTHOR]

Road safety conditions in China have worsened following rapid urbanization and motorization. For a long time now, China has ranked first in the world in the number of road accidents and fatalities. Therefore, evaluating safety levels is essential to implementing effective countermeasures. For developing countries like China, however, assessing safety levels via crash data statistical analysis is difficult because of limitations on a short history of collecting crash data, small samples and an incomplete collection of information. To address these limitations, the method of surrogate safety analysis using the traffic conflict technique (TCT) has become a widely used evaluation procedure. On the basis of the mechanism analysis of TCT, the paper presents a conflict hazardous assessment model (CHAM) for the mixed traffic safety evaluation of urban intersections. In the proposed model, the principle of the conservation of momentum is used. CHAM is a model used for assessing safety levels from the aspects of severe conflict numbers and conflict hazardous levels (CHLs) when traffic conflicts among mixed-traffic modes occur. Factors such as the conflict type and conflict angle of different traffic modes, weight and velocity are considered and incorporated into the model through the integration of the accident collision theory and the head injury criterion (HIC) index for head hazard assessments. The calibration and validation of CHL models are also carried out using 341 intersection crash reports in Beijing from 2006 to 2008. The results show that the established CHL models have good validity. [ABSTRACT FROM AUTHOR]