Análise de dados da Uber: um novo olhar sobre a habitabilidade e a mobilidade urbana

  • Gisliany Alves Departamento de Engenharia de Computação e Automação, Universidade Federal do Rio Grande do Norte, RN
  • Ivanovitch Silva Departamento de Engenharia de Computação e Automação, Universidade Federal do Rio Grande do Norte, RN
  • Luciana Lima Departamento de Demografia e Ciências Atuariais, Universidade Federal do Rio Grande do Norte, RN
Keywords: Data-Driven Approach, Uber, Liveability Indicators, Urbanization, Sustainable Urban Development

Abstract

In 2016, the UN defined policies to foster the Sustainable Development Goals, whose implementation depends on the supervision of indicators. In this scenario, liveability is a dimension that can be monitored by indicators for that purpose, as it combines fundamental attributes of sustainable development. However, the lack of consistent and up-to-date data makes this monitoring difficult, mainly in developing and less developed countries. Hence, as a contribution to this field, this work proposes a liveability indicator that combines traditional population-based data, namely the population census, and alternative sources, such as data from Uber. For estimating the indicator, data from Uber rides, precisely the Estimated Time to Arrive, were combined with classic socioeconomic indicators. The methodology includes Factor Analysis (FA), Exploratory Data Analysis (EDA), Exploratory Spatial Data Analysis (ESDA) and Regression Analysis. Among the main results, there was a spatial variation of Uber services and the liveability indicator. One of the main conclusions is that non-traditional data, such as those from the Uber platform, can describe social and mobility inequalities between different regions of the same city.
Published
2021-10-20
Section
Articles