By Sibin Sabu
Surge pricing has recently gained traction in policy circles in India. The governments of Maharashtra, Karnataka and Delhi have already put in place legislations regulating the practice.
The term ‘surge pricing’ might be new to some, but the idea should be a familiar one. Surge pricing is basically a market mechanism to reduce the gap between demand (number of people seeking a ride, for example) and supply (number of cab drivers offering rides).
What makes surge pricing in taxis different?
The term has come to be closely associated with the transportation sector since the foray of taxi aggregator services such as Uber and Ola. That said, Uber and Ola were not the first to introduce the idea of surge pricing in the transportation sector. Airlines have been doing it for a long time. The Indian Railways has its own version, the Tatkal booking system. It is also common for taxi services (autorickshaws, cabs etc) to hike their fare at night hours or during times of hartals.
So, why people do find surge pricing acceptable for airlines and the Indian Railways, but not for taxi services?
This could be due to two factors: (a) the dynamicity of the price fluctuation which is highly unpredictable and (b) because of the extent to which the public relies on these services.
In the case of airlines, surge pricing is predictable and there is a way around it. People can avoid the surge pricing effect by booking their tickets early.
Taxi fares are way too dynamic and uncertain. There is little knowledge on when surge pricing will kick in, and on whether it will increase or decrease. This increases the vulnerability of the public to this effect.
Reducing the dynamicity and unpredictability of pricing through standardization may be desirable for both consumers and taxi aggregators. Based on past trends, it is possible for taxi aggregators to identify and predict peak hours. The peak hours, and the charges for travelling in those hours, could then be made known to the public.
If people know beforehand how much it would cost them to travel on a particular hour of the day, they would plan accordingly. It would make them less vulnerable to surge pricing. This could serve the purpose of having surge pricing in place sans its major negatives and make it more acceptable.
Drawing parallels with Maximum Retail Price
In addition to removing the uncertainty in surge pricing, it would also be beneficial to place a cap on the maximum surge pricing that can be charged.
Leaving pricing completely to the supply-demand functions of the market may not always be desirable because transportation can at times be an essential service — such as during times of medical emergencies, terrorist attacks or even during a large festival. Fares would then increase to exorbitant proportions and the rationing mechanism through prices would be undesirable.
This is also a main reason why our policymakers have kept Maximum Retail Price (MRP) for the sale of goods. Having an MRP in place and advocating for surge pricing without a cap would be contradictory.
Surge pricing with a cap would be a better scenario as it would help in bridging supply and demand. It incentivizes drivers to ride even at night hours and to non-popular routes, thereby improving accessibility and mobility. This pricing mechanism also helps private transport to complement public transport systems better.
To put across the role and relevance of surge pricing, Uber and Ola could possibly consider repackaging surge pricing differently. Taxi cabs may put in place a cap on maximum surge price (MSP) and treat it as the equivalent to MRP.
Instead of charging higher prices, taxi cabs can charge negative surges at times of lower demand. Fare can be pivoted around the maximum that can be charged. For example, rather than communicating that double the fare has been charged, they could repackage it to convey that half the MSP (maximum surge price) has been charged, effectively indicating that a discount has been given on account of lesser demand relative to supply. This could help taxi aggregators communicate the function of demand and supply in pricing in a positive light.
There also needs to be greater clarity on the algorithm based on which surge pricing is levied. Professor Mudit Kapoor of the Indian Statistical Institute suggests that Uber and Ola could use the information at their disposal regarding an individual’s ride history and other personal details “to compute the willingness to pay at the level of the individual” — which may prompt them to indulge in price discrimination. It would be in the best interest of Uber and Ola to increase the transparency in their algorithm.
Lessons for public transportation
It would not be a bad idea if public buses differentiated prices during peak hours and non-peak hours. This could help generate additional revenue and control traffic congestion. Competition from other modes of transportation, sensitivity of the public to price rise and the capacity utilization of buses during peak hours are some important factors which need to be taken into consideration before implementing a differential pricing system in public transport.
Creating an Ola-like app for public transport would improve the reliability and convenience of public transportation systems, making them more competitive over the alternative of private transport. Registering public buses on Uber and Ola would be an even better idea.
Sibin Sabu is an academic associate at Indian School of Business, Hyderabad and specialises in Public Policy. He was earlier a researcher with Centre for Public Policy Research, a think-tank based in Cochin.