PUI2017 Extra Credit Project Proposal
Vehicular urban mobility and the introduction of ride-sharing
<Emily Hansen, ekh331, ekh331>
Problem Description: The proposed project aims to evaluate the relationship, if any, that exists between New York City Yellow Cab and Citi Bike trips before and after the introduction of major urban mobility events. Such events considered include the debut of ride-sharing services such as Uber and Lyft, carpooling services such as UberPOOL. The goal is to evaluate, via a series of Mann-Whitney U tests, any empirical change in ridership usage, controlled for population, that may be the result of changing public perception of urban mobility or the beginnings of the re-branding process for certain modes of transportation. Origin and destination aggregates will be analyzed in the event of significant ridership number changes and considered with socioeconomic data of their respective regions in order to discuss whose ridership is most changing.
The questions the research aims to address is as follows: are given samples of ridership data before and after these major events representative of different populations? If so, can we identify "tipping points" in urban mobility functionality? Geographically, who is representing taxis, public transportation, and ride-sharing, and how has that representation changed temporally with the advent of new transportation services?
Data: The data planned to be utilized for this project include records from the New York City Taxi and Limousine Commission detailing taxi trip records, Citi Bike trip data, and historical data representative of major transportation market renovation. The data is suitable for this project because their records, including features such as trip duration, location, and distance traveled, can be plotted in time series once filtered to reflect the time periods of interest.
Analysis: The data can be visualized high-level as a series of time series plots surrounding the periods of interest. In order to determine if there was a significant change in ridership behavior (from any number of trip features) as a result of major events, a series of KS-tests or Mann-Whitney U Tests can be performed on the data to tell whether the populations choosing to take a certain method of transportation have evolved.
References: Recent studies have speculated that ride-sharing services such as Uber are changing the way the taxi systems work in urban areas. Socially, the introduction of Uber has led to a decrease in complaints about taxi usage, but the magnitude of this decrease has not been contextualized (Wallsten 2015). Riders have reportedly taken well to Uber over taxis: as of October 2017, New Yorkers take more Ubers now than they do taxis and extending their range far into the boroughs where yellow cabs are scarcely seen (Muoio 2017).
Deliverable: The intended deliverable is a statistical conclusion about the different methods of transportation as a way to quantify with increased confidence the impact of major transportation-related events in the city. Also included will be descriptive statistics and plots to better visualize changes, or lack thereof, in ridership features.
Extensions: If time permits, the bike sharing, taxi-riding, and ride-sharing city of Chicago may also be studied and the relative impacts of transportation events between it and New York City compared. Chicago's Data Portal has analogous transportation data available at a smaller scale.
Bibliography:
Gaskell, A. (26 January 2017). Study Explores the Impact of Uber On The Taxi Industry. Retrieved from
https://www.forbes.com/