Summary

The Uber app was created to make sure that people could get rides when and where they need, no matter what. We already know that 4 in 10 rides in Chicago start or end in underserved neighborhoods and we have heard story after story from riders around the world who have never been able to get a taxi to come to their neighborhood, and who now rely on Uber for reliable transportation.

So we decided to take it a step further and investigate the quality of service in those communities.  This study explores what, if any, relationship exists between a neighborhood’s economic well-being and the level of service that Uber’s network provides in that neighborhood.  We studied two related questions: 1) does a neighborhood’s median income predict the expected time before a driver appears after a request is made? and 2) does a neighborhood’s median income predict the likelihood that a request will go completely unfulfilled?

The results? Median income in a neighborhood has no meaningful relationship to Uber’s level of service in that neighborhood, including wait times and fulfillment rates.

Methodology: The wonky stuff

In order to investigate the relationship between local income and Uber’s level of service, we analyzed a data set that included:

  • median income by neighborhood

  • neighborhood in which each trip originated

  • whether or not each trip was ultimately fulfilled

  • the time between request and pickup for each completed trip

The relationship between a neighborhood’s income and the waiting time was determined by running an ordinary least squares regression of the form wait = a + b*income.  This regression was run on a large number of trips in 2014 in Chicago.  The relationship between a neighborhood’s income and the probability of a ride’s being fulfilled was determined with a similar specification, prob_unfulfilled = a + b*income.  This second regression was run on a single observation for each neighborhood of the percentage of trips that are not fulfilled as a percentage of all trip requests.

Results: The numbers

Median income is related to expected wait time by the formula

wait (in seconds) = 510 – .003 * median income (in dollars)

In other words, a $1,000 increase in a neighborhood’s median income is associated with 3 fewer seconds in expected wait time.  The data and regression line are shown graphically below.  

 

Median income is related to the probability of a ride going unfulfilled by the formula

prob_unfulfilled = .3 – .000003 * median income (in dollars)

In other words, an increase in median income of $1,000 is associated with an increase in the probability of fulfillment of .003 (ie, .3 percentage points).  The data and regression line are shown graphically below.