Analysis of the Impact of Ride-Hailing Services on Motor Vehicles Crashes in Madrid

María Flor,Jairo Casares,Armando Ortuño,Begoña Guirao

doi:10.3390/su13115855

María Flor, Jairo Casares + Show 2 more

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https://doi.org/10.3390/su13115855

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Abstract

In most cities, discretionary passenger transport by car is predominantly supplied by taxi services. These services face competition from new digital platforms (UBER, Cabify, etc.) that connect users with the services offered by authorized drivers with a license for rented vehicles with drivers (VTC). However, very little is known about the impacts that these services produce in cities where they operate. So far, most studies on this issue have focused on cities of the United States of America, and they broadly found a positive impact in terms of road safety. Road safety has become one of the priority focuses for ensuring social welfare, to the point of being integrated into the Sustainable Development Goals as a primary value to achieve sustainable, safe and responsible mobility. Within this context, the objective of this paper is to analyze the impact of ride-hailing platforms on the frequency of traffic accidents with at least one fatally or seriously injured person in the municipality of Madrid from 2014 to 2018. To do this, a regression analysis has been carried out using a random effects negative binomial regression (RENB). The results of the model show that Uber and Cabify services are associated with a decrease in fatal and serious accidents in Madrid.

Highlights

The extraordinary progress in the field of Information and Communication Technologies (ICT), especially with regard to the internet, has reconfigured the way people access information, the way they offer goods and services, and the way in which people communicate [1,2,3]
The mean and standard deviation for accidents at the weekends and on public holidays research 18.50 and 8.96 respectively; and accidents with alcohol or drugs involved, 2.79 and 2.57, respectively. These numbers imply that a negative binomial (NB) regression model is more suitable than a Poisson regression model; The average population is 152,670 inhabitants per district, but the ratio of population goes from a minimum of 45,950 to a maximum of 253,430 inhabitants; Madrid has an average of 860 leisure establishments per district; The indicator of socio-economic status has a mean value of 4.76 per cent
The findings of this analysis reveal that the implementation of Uber and Cabify services in the city of Madrid is related to a reduction of accidents with seriously injured or fatal victims at weekends and on public holidays, as well as in accidents related to alcohol and drugs

Summary

Introduction

The extraordinary progress in the field of Information and Communication Technologies (ICT), especially with regard to the internet (access to the network and the development of its potentialities), has reconfigured the way people access information, the way they offer goods and services, and the way in which people communicate [1,2,3] These important advances, in conjunction with the increase in the speed of internet connections, the advent of smartphones and the proliferation of smartphone applications, has profoundly reshaped the mechanisms underlying trade, consumption and social relations. These new business models employ collaborative platforms that facilitate that people, often private individuals, offer the temporary use of goods without modifying their ownership (for example, rooms in a house), or the service delivery, in exchange, or not, of a consideration They facilitate the exchange of underused goods, either by selling them or giving them away for free or by sharing space or time [4].

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