Monday, November 17, 2014

Should Uber keep their dynamic pricing model?

Background :

Uber is a technology company currently operating as a market maker in the public transportation sphere. The company uses its own smart phone application to connect passengers with drivers with vehicles for hire; whereby customers use the app to request rides and track their reserved vehicle's location. Uber at present is being overwhelmed by criticism from various groups, including city officials, regulators and especially from taxi companies who are annoyed by increased competition and feel their business is threatened by another highly technological taxi company. The reason for this anxiety is how Uber operates. Uber has neither vehicles of its own nor its own drivers. It instead partners with limousine services  who can provide cars as well as drivers and work on contractual basis. My argument is that Uber will keep its brand strong by not abandoning their pricing model and that the price surges are necessary to sustain its business.

Price surges happen because of a high demand. These prices are often calculated by an algorithm that considers a variety of inputs such as fuel, distance, holidays, hour of the day, weather and many other factors. In contrast, a non surge price time is a period where supply and demand are almost at equilibrium. During these time periods, Uber passengers are paying the predetermined standard rates, which include minimum fares. Now, the primary challenge for Uber is striking that balance of demand to supply and doing it so without having full control of the supply side and be consistent with it. A similar analogy can be seen in liquidity providers in financial firms or otherwise known as the market makers.

During high demand period, let’s say, after a soccer game in downtown, there will be more people who will be looking to take a ride home. This creates a situation where there are few cars and more people and so eventually Uber cars go to those who pay much more. Uber declares this as basic economics, it is. However, Uber also claims this incentivize drivers and maximize the number of cars on the road (Uber, 2012). I tend to not agree; I argue that more, if not all Uber drivers are already on the streets to take advantage of these price surges that are sometimes go up to 6 times the standard fares. I believe the broader interpretation to this is that, it is a systematic way to preserve the integrity of the product’s brand more than the profit it takes from price on such events. This is because due to peak hours, the car supply is already at its upper limit. Given that Uber driver base is also limited, true demand has the potential to move beyond the available car supply entirely, creating market inefficiency unless drastic price increases are applied. When a passenger now opens his Uber mobile app and checks the price for going home, He can see there are Uber cars available but with a much higher price that he or others are not ready to pay for yet. On the other side of the market, the Uber drivers will be waiting in their empty cars to see who takes this price and go home. In effect, less passengers and Uber cars are actually on the road doing business. While this means less revenue for Uber  and getting home late for passengers, the Uber brand is up and running flawlessly waiting for market participants to lead themselves to equilibrium. So in essence it is relatively better for Uber that its customers found themselves with higher prices than not knowing if the Uber taxis will be available when they were most needed. It’s also important to suggest that “successful brands create strong, positive and lasting impressions through their communication and associated psychological feels and not only their functional use “(Paul & Chris,2013).

Uber has also another set of challenges. James argues “Uber is currently combating the sense that transportation is, in some sense, a public utility, and that it is offensive to charge people much more than they are used to paying” (James, 2014) and thus must be regulated. The problem is that regulations have a poor track record for improving efficiency or service. Instead regulation has a good record on improving things like safety and fairness. In my opinion, Uber is trying to provide customers all these: efficient services, safety and fairness. While the concepts and implementation of efficient services and safety can be articulated, fairness is delicate to put in the same measurement bar. What’s fair price to one individual may not be fair to another. Uber has been open about price prediction in cases of public events such as holidays, although I also think that it’s somehow a confirmation bias for customers - the tendency to look for and be provided with information that confirms what is already known (Nickerson, 1998). In light of this, it is then fair to pay to what one has also confirmed to himself or herself. The Uber dynamic pricing model in my views is not random or at least it should not be. If one has a history of paying more than the standard price, the price modeling algorithm should likely show patterns of prices that the customer is more comfortable in accepting, creating seemingly perfect price discrimination – paying for what one assumes is appropriate or fair for his own personal taste, and this in my views is a good thing.
As I stated in my first sentence, Uber is a technology company operating in the transportation sector for now and opportunities here are still are still untapped. Nevertheless, Uber is in a strategic position to venture into other forms of business such as logistics and from the very optimistic views of one of the Uber’s investors, this is worth as much as a trillion dollar (Bill Gurley, 2014).Thus, another reason why their dynamic pricing model should stay secret is, if once reveled in the transportation context, the details of which can adapted and be used against them by competitors, already established firms or new startups like Nimbl, which could make Uber  block itself out of a completely new market. 

Uber  (2012).”Clean and Straight forward Surge pricing” [18 Oct. 2014].
Paul,Chris & kelly. (2013). “Essentials of Marketing”, Oxford, London, 4th edition.  pp. 201.
James. (2014). “In praise of efficient price gouging” [18 Oct. 2014].
Nickerson, R. S. (1998).” Confirmation bias, A Ubiquitous phenomena in many guises.Review of General Psychology 2(2), 175–220. 
Bill Gurley. (2014).”Uber investor bill gurley defends valuation”[18 Oct. 2014]. 
Other links.

No comments:

Post a Comment