One basic rule of pricing is that it is impossible for all buyers to have the same consumer surplus (the difference between what a buyer values the item at and what he paid). This is because each buyer values the item differently, and is thus willing to pay a different price for it. People who value the item more end up having a higher consumer surplus than those who value it less (and are still able to afford it).
Dynamic pricing systems (such as what we commonly see for air travel and hotels) try to price such that such a surplus is the same for all consumers, and equal to zero, but they never reach this ideal. While the variation in consumer surplus under such systems is lower, it is impossible for it to come to zero for all, or even a reasonable share of, customers.
So what effectively happens is that customers with a lower consumer surplus end up subsidising those with a higher consumer surplus. If the former customers didn’t exist, for example, the clearing price would’ve been higher, resulting in a lower consumer surplus for those who currently have a higher consumer surplus.
Sometimes the high surplus customer and the low surplus customer need not be different people – it could be the same person at different times. When I’m pressed for time, for example, my willingness to pay for a taxi is really high, and I’m highly likely to gain a significant consumer surplus by taking a standard taxi or ride-hailing marketplace ride then. At a more leisurely time, travelling on a route with plenty of bus service, I’d be willing to pay less, resulting in a lower consumer surplus. It is important to note, however, that my low surplus journey resulted in a further subsidy to my higher surplus journey.
When it comes to markets with network effects (whether direct, such as telecommunications, or indirect, like any two-sided marketplace), this surplus transfer effect is further exacerbated – not only do low-surplus customers subsidise high-surplus customers by keeping clearing price low, but network effects mean that by becoming customers they also add direct value to the high surplus customers.
So when you are pleasantly surprised to find that Uber is priced low, the low price is partly because of other customers who are paying close to their willingness to pay for the service. When you pay an amount close to the value you place on the service, you are in turn subsidising another customer whose willingness to pay is much higher.
This transfer of consumer surplus can be seen as an instance of bundling, but from the seller’s side. Since a seller cannot discriminate effectively among customers (even with dynamic pricing algorithms such as Uber’s surge pricing), the high-surplus customers come bundled with the low-surplus customers. And from the seller’s perspective, this bundling is optimal (see this post by Chris Dixon on why bundling works, and invert it).
So the reason I thought up this post is that there has been some uncertainty about ride-hailing marketplaces in Bangalore recently. First, drivers went on strike alleging that they weren’t being paid fairly by the marketplaces. Then, a regulator decided to take the rulebook too literally and banned pooled rides. As i write this, a bunch of young women I know are having a party, and it’s likely that they’ll need these ride-hailing services for getting home.
Given late night transport options in Bangalore, and the fact that the city sleeps early, their willingness to pay for a safe ride home will be high. If markets work normally, they’re guaranteed a high consumer surplus. And this will be made possible by someone, somewhere else, who stretched their budget to be able to afford an Uber ride.
Think about it!
Cross-posted at RQ