case.

Uber's dynamic pricing algorithm

Back in early 2012, Uber's Boston team noticed a problem. On Friday and Saturday nights, around 1am, the company was experiencing a spike in "unfulfilled requests." The root cause was that drivers were clocking off the system to go home, just before the weekend partygoers were ready to venture home themselves. There was a supply-demand imbalance, and the result was a lot of very unhappy customers. So the Boston team had an idea. What if they offered the drivers a higher price to stay on the system longer (until around 3am)? Would more take-home dollars for drivers increase supply? In just two weeks they had a resounding answer. By offering more money to drivers, they were able to increase on-the-road supply of drivers by 70-80%, and more importantly eliminate two-thirds of the unfulfilled requests. The supply curve was highly elastic. Drivers were indeed motivated by price. Based on the results from the Boston experiment, Uber implemented its dynamic pricing policy to be used solely when demand is materially outstripping supply. Dynamic pricing changes are driven algorithmically when wait times are increasing dramatically, and "unfulfilled requests" start to rise. In essence, there are two functions of the increased price model. One is to increase supply. The second function of the price increase is to temporarily intentionally reduce demand. Through these two mechanisms, the company is able to (a) increase supply, (b) assure reliability, a key tenet of the company, and (c) maximize the number of completed rides. Uber's dynamic pricing model is rather straightforward. When demand outstrips supply, dynamic pricing algorithms increase prices to help the market reach equilibrium. Of course, these situations are always temporary, eventually supply outstrips demand, and the price falls back to normal. Nevertheless, the resulting 'price surges' at times of peak demand have often upset customers initially. Contrary to, for example, the hotel industry where customers are used to higher prices in times of high demand, the taxi industry has always operated with fixed prices. Travis Kalanick, the Uber CEO, has reacted by saying: '. . . because this is so new, it's going to take some time for folks to accept it. There's 70 years of conditioning around the fixed price of taxis.'. However, Uber has adjusted its dynamic pricing algorithm to accommodate people's sense of fairness. In 2013 Uber encountered a backlash when it increased its prices eightfold during storms in New York. In 2016 it capped its surge prices for its regular taxis at 3.5 times the normal fare when severe snowstorms hit New York. Sources: Bill Gurley, 'A Deeper Look at Uber's Dynamic Pricing Model', Above the Crowd, 11 March 2014 (http://abovethecrowd. com/2014/03/11/a-deeper-look-at-ubers-dynamic-pricing-model/); http://faculty.chicagobooth.edu/chris.nosko/research/ effects_of_uber%27s_surge_pricing.pdf and The Economist, 'Flexible figures: a growing number of companies are using"dynamic pricing"', 30 January 2016

Question

Uber's dynamic pricing algorithm is discussed with a focus on the adjustment of prices during peak demand ('surge pricing'). we have also discussed price adjustments using the economist's toolbox of supply and demand curves. Can you explain Uber's 'dynamic pricing' in terms of shifts of these curves?

Reference

For any given price the company calculates the amount of output that maximizes profits, and the optimal way (that is the values ofKandL) to produce this amount of output. This results for all firms in an industry in a supply curve.

On the other side, consumers maximize his utility. For any given price he calculates the amount he is going to buy. For all consumers this results in the demand curve.

Supply equals demand for one price only: at the intersection of the supply curve and the demand curve.

If there is a shift in demand (for example because new consumers enter the market), the price goes up. Producers will now produce more, and total demand will again equal total supply.