While fascinating, this analysis seems to fall apart on two major fronts.
1. It seems to completely discount surge pricing, which would likely change these numbers significantly.
2. It assumes that taxi and Uber behavior is very similar, but this seems pretty dubious for 2 major reasons:
a. In dense areas it's far more convenient to use a taxi than an Uber (you can hail one in a minute or two), while in less populated areas it's far more convenient to get an Uber. This would definitely skew Uber significantly towards longer, speedier trips.
b. Uber likely sees a greater proportion of utilization from airport rides. For an expensive trip like that, people are more price conscious and most New Yorkers know it's usually much cheaper to take Uber. When juxtaposed against the prospect of waiting in line for a ~$60 + tip taxi ride, the immediacy of a $63 Uber looks very appealing. Additionally, I imagine Uber is seeing disproportionate growth amongst tourists (who might already be using Uber elsewhere but are intimidated by hailing NYC taxis).
Nope, he does not. If he'd studied the blog post he's linked to, it is clear that surge rates can go a few multiples at busy periods, which would make an outsized contribution to total fares even at 10-15% occurrence.
If you look at the service area on the ubernyc page, it goes way beyond the city limits (even a fixed price to the hamptons). Again, even if the percentage of these rides are low, it isn't hard to see how average trip length or average fare would be moved up significantly.
I read the article - even though it's written well, it makes a lot of hypotheticals based on hazy assumptions that seem to lead well to a result that the author probably wanted to put forward. Not the best article if you want an objective analysis on the issue.
Did you look at the spreadsheet he linked to in the footnote where he calculates the cumulative effect of surge pricing? Where would you like to quibble with the math?
Daily weighting is made up without any real insight into operations. Furthermore, whatsthefare says that it bases its own approximations on relatively sparse data from user's use of their systems, not realtime monitoring on a service that's probably prone to constant change.
I think I mostly find it incorrect to essentially take a pin-hole view at the data through 5-6 averages, and extrapolate it towards a somewhat biased result.
Even if you drastically change the daily weightings you don't move the overall output very much at all.
As for the other data they describe their collection methodologies, and the numbers they produce are in line with trends that Uber has indicated. You're certainly free to produce a dataset of your own but until you do that this one doesn't seem especially bad or anything.
1. It seems to completely discount surge pricing, which would likely change these numbers significantly.
2. It assumes that taxi and Uber behavior is very similar, but this seems pretty dubious for 2 major reasons:
a. In dense areas it's far more convenient to use a taxi than an Uber (you can hail one in a minute or two), while in less populated areas it's far more convenient to get an Uber. This would definitely skew Uber significantly towards longer, speedier trips.
b. Uber likely sees a greater proportion of utilization from airport rides. For an expensive trip like that, people are more price conscious and most New Yorkers know it's usually much cheaper to take Uber. When juxtaposed against the prospect of waiting in line for a ~$60 + tip taxi ride, the immediacy of a $63 Uber looks very appealing. Additionally, I imagine Uber is seeing disproportionate growth amongst tourists (who might already be using Uber elsewhere but are intimidated by hailing NYC taxis).