A UK study showed the following depreciation for BEVs bought in 2020 based on their 2023 market value:
I doubt it. They set the price based on how many requests for rides are received on their app, period. Uber could care less whether there are 10 or a 1000 Ubers on the road, if the demand for rides goes up so does the price. That’s how they make their money.
Would like to see any evidence that Uber surge pricing takes into account the number of active drivers.
Sure - but those figures aren’t for a “never driven” car - the amount of depreciation due solely to the passage of time rather than one that has been used an average amount. A typical car (meaning an ICE car that is used an average mount) will depreciate about 50% during the first four years of ownership. The BEV’s you note have depreciated somewhat more than that, but not so much more that you would attribute anything like losing half their value just to the advancement of technology. That’s why I limited my search to ultra-low mileage cars (less than 20K miles for a four-year old car) - and even then that’s still going to have sizable depreciation from use, not merely time.
I know that is what they say. I am just skeptical. The Washington Post article I linked above describes a study saying that surge pricing does not increase the number of drivers. What surge pricing does is redistribute drivers and reduce demand. It doesn’t appear to consistently increase supply.
If Uber was basing their pricing significantly on supply, I would think that the correlation between surge periods and an increase in drivers would be more consistent and obvious.
Yes, there is evidence that Uber’s surge pricing algorithm considers the number of active drivers. Surge pricing is designed to balance supply and demand by increasing prices when demand outstrips supply, which in turn incentivizes more drivers to become active.
Let’s look at that evidence. This is Figure 3 from your first link.
Note the difference between those checking the Uber app (red, representing the potential demand) and those actually requesting an Uber (blue, representing the actual demand). Note that the imposition of surge pricing does not increase the number requesting rides, even during the times when the supply of drivers has peaked (11PM). The primary benefit to Uber of the price surge is to control demand.
To put it another way, Uber doesn’t appear to be trying to optimize the number of drivers getting passengers. The surge price point seems to be designed to keep demand to where it was prior to the surge, presumably so that wait times do not increase too much.
This makes sense because in this business, demand is much more elastic than supply. The supply of drivers changes slower and to a smaller magnitude than the changes in demand that trigger surge pricing. Supply cannot react fast/high enough to control wait times, which is why surge pricing is designed to limit demand.
I don’t see any conclusions that differ from the 2015 studies. The conclusion in 2015 from my Washington Post link:
Your SSRN paper only looks at the behavior of active Uber drivers. There is no data that I could find for how many inactive become active due to the surge.
I also did not see any new info on whether surge pricing increased the number of Uber rides in the surge area (as opposed to just opening the Uber app). In 2015 it appeared that surge pricing did not increase the number of Uber rides from pre-surge levels. This suggests that the surge price point was designed more to reduce demand than increase the number rides by bringing in more drivers. Your links appear to be silent on this issue. If the primary impact is to reduce demand, then the effect on supply is mostly irrelevant.
Finally would note that your one research link was written by Uber employees so one has to be a bit skeptical about its objectivity. Would Uber publish a paper that reflected negatively on its policies?
