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Using ‘Big Data’ to understand the impacts of Uber on taxis in New York City

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  • Willis, George
  • Tranos, Emmanouil

Abstract

Uber has coupled their ability to dodge regulation with their ride-haling app, to grow from a Silicon Valley start-up, to a global powerhouse challenging established taxis in over 700 Metropolitan areas. Through the lens of Schumpter’s ‘Creative Destruction’ and Roger’s ‘Diffusion of Innovation’, this paper aims to investigate how Uber challenges the established taxis, focusing on yellow taxis in New York City. To capture Uber’s popularity we employ innovative new data from the New York Times API. We couple these data with data about taxi usage and quality of service from the New York City Taxi & Limousine Commission. We then employ well established time-series modelling techniques in order to test if and how Uber affected the well established taxi market in New York City. Our results illustrate the disruptive nature of Uber in terms of leading to a decrease in traditional taxi rides, but also to a behavioural change of customers raising more complaints about taxi services.

Suggested Citation

  • Willis, George & Tranos, Emmanouil, 2020. "Using ‘Big Data’ to understand the impacts of Uber on taxis in New York City," SocArXiv 25fxs_v1, Center for Open Science.
    • Handle: RePEc:osf:socarx:25fxs_v1
    DOI: 10.31219/osf.io/25fxs_v1
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    References listed on IDEAS

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    1. Cheung, Yin-Wong & Lai, Kon S, 1995. "Lag Order and Critical Values of the Augmented Dickey-Fuller Test," Journal of Business & Economic Statistics, American Statistical Association, vol. 13(3), pages 277-280, July.
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