Using 'big data' to investigate the impacts of Uber on Yellow Taxis in New York

Authors: George Willis*, University of Birmingham, Emmanouil Tranos, University of Birmingham
Topics: Economic Geography, Transportation Geography, Quantitative Methods
Keywords: Uber, New York, big data, regression analysis, creative destruction
Session Type: Paper
Day: 4/5/2019
Start / End Time: 9:55 AM / 11:35 AM
Room: Tyler, Marriott, Mezzanine Level
Presentation File: No File Uploaded


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 Rogers' ‘Diffusion of Innovation’, this paper aims to investigate how Uber challenges the established taxis, focusing on yellow taxis in New York. This paper uses ‘big data’ made available through the Taxi & Limousine Commission (TLC) and NYTimes API to investigate to what extent Uber has impacted yellow taxis. Using regression analysis, we aim to find the impacts that Uber has had on trips by yellow taxis. Granger-Causality was also used to find if there was a Granger-Causal (or reverse) relationship between NYTimes articles and yellow taxi trips. This paper also aimed to investigate if an increase in the popularity of Uber would cause yellow taxis to increase their quality of service. However, we found that the framework of using complaints to assess quality is not successful in establishing an answer for this research question and suggest another framework is needed to fully understand these impacts.

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