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Dynamic surge pricing for ride-hailing services like Uber have been infamous since it’s inception in 2012. While most riders are mildly annoyed by it, some politicians have gone so far as to say that it should be illegal. As a curious PM, I dig deeper into the contention that surge pricing is not only beneficial for the rider, but also a necessity in marketplaces like Uber.
How to keep Drivers and Riders happy?
Uber is a two sided marketplace where drivers and riders freely opt into the service. To promote the usage of the service, Uber needs a strategy to incentivize the riders and the drivers. As a frequent user of the service myself, the most important factor for me to book a ride is that the pickup time should be less. Hence Uber needs to minimize the pickup times to keep a rider happy.
Drivers on the platform will be happy when they can maximize their time spent in earning. A driver only earns money when the rider is in the car i.e. time spent in waiting to connect with a rider and the time spent in traveling to pick them up is not rewarded.
A market without Incentives
Later in the article, I will talk about how Uber can determine the exact surge multiplier using principles of microeconomics. However, lets first look at the effects of surge pricing. The number of requests that are made on the Uber app are directly correlated to the ETA for the car. This is evident from the following data:
As the Ariana Grande concert got over, the requests for Uber rides went up and so did the ETA for the car. In this example, surge pricing was in effect. The right most graph shows the completion rate i.e. number of ride requests that were completed. With increase in demand for Uber, the ETA for a car shot up to 4 minutes which is still acceptable. The completion rate is still around 100% which means almost all the requested rides were completed.
On the other spectrum is an example when surge pricing was not in effect. This is the 2015 New Year’s eve in NYC.
As you can see, the increase in the demand for Uber directly corresponds with the increase in ETA for the car. However, in this example, the ETA went up drastically to over 9 minutes. This led to a horrible completion rate of 20%. Both examples have been described in detail in a 2015 case study.
So what really happened? Because there was no surge pricing, there was no incentives for the drivers to spend their New Year night driving in the city therefore the supply of cars was low. Additionally, because there was no increase in the price, everyone requested a ride without any hesitation. The imbalance in supply and demand with no instruments to create an equilibrium ultimately resulted in a poor completion rate.
Using Microeconomics to create incentives
Surge pricing is not a new concept. Airlines and hotels have used it for decades. What Uber did differently is they implemented a patented algorithm that would calculate a surge price every 5 minutes unlike hotels that may change their prices seasonally.
The cost of a ride is a component of the distance of the ride (miles) and time spent on the ride (minutes). The cost is then multiplied by a surge factor during peak hours to determine the total cost of the ride. Surge pricing is based on a very simple concept in economics – Supply vs Demand. This concept also helps Uber determine the exact surge multiplier that will help create equilibrium in the marketplace i.e. Supply = Demand.
Supply-Demand Crash Course
The supply-demand graph shows us two important things as it relates to Uber:
- Law of Demand
- When the price of a ride goes up, people will book lesser rides
- When the prices of a ride goes down, people will book more rides
- Law of Supply
- When the price of a ride goes up, drivers will provide more rides
- When the price of a ride goes down, drivers will provide less rides
As you can see in the above example, there is a point in the graph where the supply curve meets the demand curve. This is called the point of allocative efficiency. In the most simplest terms, maximum number of riders and drivers will be satisfied when the cost of the Uber ride is $50. To take it one step further, this is the point where consumer surplus and producer surplus can be maximized and the supply of drivers providing rides will perfectly follow the demand of riders requesting a ride.
What happens at the end of a concert?
At the end of large-scale events like concerts, there is a sudden increase in the number of people opening up the Uber app leading to an increase in the number of requests. This causes a surge in the demand for cars. This can be seen in the below graph as the Demand curve moves from D to D+.
At this point, the supply has yet changed i.e. number of cars around the arena is still the same as it was 30 mins ago. This causes the allocative efficiency to increase i.e. maximum number of riders and drivers will now be satisfied if the price of a ride goes up to $67. In the mind of the consumer, the value of the ride has increased because they see a huge number of people wanting to get the same car. Note that the miles or the time of the ride has not at all been impacted. Uber uses this opportunity to incentivize the drivers and increase the supply of cars in the area. Firstly, they notify the riders that there is a 1.35 X surge (67/50).
At this point, all the riders willing to pay for the ride will book the Uber. Those who are unwilling to pay the surge price will drop out of the app and look for alternate means of transport. This is one way in which Uber tries to create equilibrium – by reducing the demand.
Secondly, Uber will let drivers know that there is a surge price going on outside the concert arena. This will incentivize more drivers to provide rides and hence this is the second way in which Uber creates equilibrium – by increasing supply.
What happens an hour after the concert?
An hour after the concert, most people would have left the vicinity of the arena. However, the drivers will still be around waiting for their next ride. Now the demand for rides goes back to normal but the supply has increased drastically. This can be seen by the shift in the Supply curve denoted by S+.
The increase in supply now brings the allocative efficiency down to $32. This will indicate to the drivers that the surge is over and rides are now cheaper than what they would normally be. The drivers will therefore leave the area bringing the supply back to normal. At the end of it all, Uber was able to efficiently allocate its resources and supply rides when demand was high and reduce the supply once the demand for cars went down.
Conclusion
Through this all, ETA for the rides was low because drivers flocked to the area where surge pricing was going on. This allowed them to quickly pick up the riders. The good customer experience incentivizes the riders to continue using Uber as their regular ride-hailing service. On the flip side, the time spent in searching for a ride and the overall pickup time was low hence the drivers are incentivized to continue driving with Uber. Now you know why its absolutely essential for Uber to invest time and money in getting it’s surge pricing algorithms right.
To understand more about supply-demand curve or allocative efficiencies, checkout these videos below.
To understand Uber’s surge pricing in detail, here is an informative video