Last weekend, I was in Chennai and I keep using taxi-hailing apps a lot when I am outside Bangalore. About half the time, I was offered rides with surge pricing, ranging from 1.4x through 2.5x of the base fare. And in some cases, for rides in the middle of a hot afternoon, I was offered an upgrade from a “mini” to “sedan”. Riding through the upgraded sedan, I was flipping through the news article, and found an article on Uber’s surge pricing lawsuit (see http://www.bloomberg.com/news/articles/2016-03-31/uber-antitrust-lawsuit-over-pricing-green-lighted-by-judge).
On Monday, 4th April 2016, the Economic Times, Bangalore Edition carried this piece about the Karnataka Government regulation of ride-hailing service (see http://economictimes.indiatimes.com/small-biz/startups/karnataka-nixes-surge-pricing-by-taxi-hailing-apps-like-ola-uber/articleshow/51678792.cms). In a nutshell, this regulation caps surge prices, encourages drivers to operate for multiple services (multi-home), and relaxes norms for drivers to affiliate with a ride-sharing platform.
I was left wondering, what would be the implications for the lawsuit in a duopoly market like India, where OLA and Uber compete. Would the economics be any different? In this post, we will understand surge pricing and its economics, in conditions of a duopoly, and the implications of the lawsuit in India.
What is surge pricing? How does Uber justify it?
The Uber website explains surge pricing thus: (https://help.uber.com/h/6c8065cf-5535-4a8b-9940-d292ffdce119).
“Uber rates increase to ensure reliability when demand cannot be met by the number of drivers on the road.
Our goal is to be as reliable as possible in connecting you with a driver whenever you need one. At times of high demand, the number of drivers we can connect you with becomes limited. As a result, prices increase to encourage more drivers to become available.
We take notifying you of the current pricing seriously. To that end, you’ll see a notification screen in your app whenever there is surge pricing. You’ll have to accept those higher rates before we connect you to a driver.”
The core argument is that surge pricing incentivises more drivers to be available during times of high demand. At the core of this argument is that Uber cannot “mandate” drivers to be available when the demand is likely to be higher, and therefore has to “incentivise” them. Just like tipping the driver to be available. The difference is that the amount of the tip is pre-defined. The effects of surge pricing are well documented in the case study by Chicago Booth School faculty here.
There are two challenges: who pays for the incentive – is the charge on the riders justified? Do drivers like this?
Riders’ perspective on surge pricing
A lot of riders (at least in India) do not like the haggling and negotiating with taxis and autorikshaws for a ride both on price and whether they do want to go to your destination. Most of us using public transport in India are familiar with the famous rant “I have to come back from there empty”. Uber and OLA implicitly promised to eliminate it with its fixed and transparent pricing. Add to that, the ease of hailing a cab to your doorstep/ boarding point, thanks to the mobile app and navigation tools available for both the driver and the rider. In that sense, cab-hailing apps should have their loyalist converts. However, when surge pricing is applied, a typical rider would think twice before confirming the same – she is confronted with the same behaviour the autorikshaw driver on the street would have told her – “this is my price, take it or leave it.” In a sense, it brings out the haggler in the rider, just that now the firm is haggling, and the rider is not even sure the driver benefits out of it (more on the drivers’ perspective later).
The second thing that puts off the rider requesting the ride is the number of cabs available on the map before the surge pricing announcement is made. If surge pricing was indeed designed to get more drivers available, what is happening to all these cabs stationed around my pickup point? Here is where customers begin their multi-homing behaviour (having/ using multiple apps at the same time). She would immediately try the other app – OLA or Uber to see if there is surge pricing there.
It hurts when there is an emergency or a discomfort, like having small children/ elders waiting with you; a flight/ train to take; having to reach for a meeting on time; making another person wait on the other side; or a combination of the above. In effect she is made to negotiate, haggle, bargain for a ride. She does feel she is being taken for a ride, literally.
What does all this result in – a poor experience to begin with, resulting in lower driver ratings. Poor driver, he is being penalised because sufficient number of other drivers were not available. Yes, he may make more money, but at the end of the day, the overall economics may not make sense. Surge pricing acts as a “moment of truth” for the rider, and she resets her expectations. When I am paying 2.1x times the normal fare, I expect the driver to be extra courteous, cab to be clean, and even the traffic to be lighter. On the contrary – surge pricing happens mostly during peak hours when everyone is either getting to work or back home, and on the road; and traffic is likely to be very heavy. All this plays on the riders’ minds and they are lowering the drivers’ ratings.
Drivers’ perspective on surge pricing
A typical driver joined the Uber system (Uber or UberX) with the intention of leveraging her/ his car for monetary gains. Compared to a taxi license, which is highly regulated (check out how to get a cabbie license in London, or what the dominant political parties think of cabbies in Mumbai), or a company employment that can be highly restrictive in terms of business, driving your car for Uber or OLA provides a combination of independence and profitability. At the core of the decision is the value of economic choice the driver has – he can choose when to “switch on”, or become available for a ride, and therefore, how many number of rides and how many hours of the day he wants to ride. This economic choice is also guided by the incentives provided by the cab-hailing firms to the drivers on the number of rides they take per day. Given the very low market penetration in India, most drivers multi-home, i.e., they sign up for both Uber and OLA. And make consolidated economic choices, viz., distributing the amount of time/ number of rides for the two firms so that they can maximise the incentives.
Surge pricing for drivers mimics the pre-disruption world. When there is high demand, I charge more. In fact, OLA (in India) has mandated that drivers should be available through the peak period to be able to earn incentives. While the peak period varies across cities, it is still such a large window that drivers could balance the demand across both the firms (Uber and OLA). And drivers make the choice of going online to that system where surge pricing is high. Even though they do not know in real time when and how much surge pricing is applicable, once the rider has accepted the ride, they would know. And with experience (and a little experimentation), it is easy to estimate. So, if it is likely that OLA would have higher surge pricing rates than Uber, the drivers would shift to OLA, thereby decreasing the supply available for Uber, triggering surge pricing in Uber. While the increased number of cabs for OLA should eventually bring down the surge pricing, it is not quick enough, as multi-homing riders (with both their apps running) are choosing the ride with the lower surge price.
Elasticity of demand and supply in a duopoly
This brings us to the question of how truly “elastic” is the supply, give the duopoly in India? Unlike in markets where there is just Uber and competition is poor, India suffers from a duopoly where the drivers’ multi-homing artificially increases/ decreases supply in one system. And when the riders are also multi-homing, the system stabilises and behaves like a monopoly, albeit with some time lags (than a monopoly market).
Would a flat peak-time pricing work? It may, but given the technology and its ability to discover real-time demand and supply, surge pricing is any day superior algorithm to peak-time pricing. Fixed peak-times are things of the past, when people went to work at the same time in the morning and returned back home around the same time in the evening. Flexible working hours, working from home, working for overseas customers in different time-zones … peak-times are stretched throughout the day in urban metropolises like Bangalore and Mumbai.
The law-suit [Meyer v. Kalanick, 1:15-cv-09796, U.S. District Court, Southern District of New York (Manhattan)]
The law suit against Uber’s CEO, Mr. Kalanick (note, the suit is against the CEO, and not the firm Uber) claims three things:
- Uber is not just a technology company, selling apps, but a transportation company
- Drivers are employees and not independent contractors
- Price fixing by the CEO of Uber, while using fixed prices despite using non-competing independent contractors as drivers
The arguments against these charges by Uber and its CEO are that Uber is just an aggregator, and the drivers as independent service providers have wilfully entered into an economic arrangement to agree to the policies set by Uber to find good quality and quantity of riders. Implying that without a platform like Uber, drivers would find it difficult to discover good quantity and quality of riders. And vice versa for riders. The transportation contract is between the rider and the driver. If this were to be entirely true, then the rider should have absolute choice of drivers/ cabs, as well as drivers to have absolute choice of which rider to take. Given that Uber make the match, and provide you “one” driver-rider combination, this true contract is questionable.
Drivers as independent contractors may be defensible with the argument that drivers have the choice when to login to the service. They may choose to switch off when they want, after fulfilling some minimum conditions. If they were employees, the firm would mandate more than a set of minimum conditions and behaviours; and would not provide the driver with the absolute economic choice provided in the current arrangement. It is to Uber’s economic policies that they have signed up to, and that explains why drivers with different economic expectations can co-exist in a single platform.
The price fixing charge is defensible with the argument that since drivers are independent contractors, it is important to “incentivise” them rather than “mandate” them to be available in peak demand times. To argue that these drivers do not compete is flawed, as the extent of surge pricing is determined by the supply of drivers in relation to the demand. In order to be available on Uber, each driver must maintain certain service quality, and do a certain number of rides. There is definitely competition amongst the drivers – they would want to be available where demand is likely to be higher than supply; and be there before other drivers. For accusing Uber of price fixing under anti-trust laws, Meyer should establish that in spite of varying demand and supply, Uber maintains the same price, coordinating with independent contractors (drivers) who do not compete.
Here is where surge pricing comes to Uber’s rescue – it is their most effective defence against price fixing charge.
Implications in India
The Indian law is uncertain, to say the least, on the regulation of platforms. The (in)famous case of a Uber male driver raping a female rider in Delhi is a case in point. Uber was first banned by the Delhi Government, the ban revoked by the High Court, only for the Delhi Government to subsequently not approve its application. Uber and OLA then went back to court and the courts agreed to revoke the ban when they promised to replace diesel cars with CNG vehicles. What this means in terms of legality is that Uber and OLA are in fact, undertaking on behalf its independent contractors.
The courts and everyone else in India would be waiting for the judgment of the class action suit in the USA on how this market pans out. Given the size of the Indian market, classifying drivers as employees, and Uber and OLA as transportation companies would kill the platform business model. While I do not believe that it would not go that extreme, interesting times lie ahead on how the courts and regulators interpret the developments.
Platform Business Firms 