Uber uses surge pricing to balance supply and demand, which is especially effective in case of emergencies and high-demand periods. Even though the dynamic price formation may seem to be unfair to customers, it ensures that they have a car to travel to the required destination while paying extra charge (“Why Uber is an economist’s dream”, 2016). Otherwise, they will be less likely to get a ride, and there would be no motivation for other users who request a taxi to drop out. At the same time, surge pricing stimulates supply since Uber drivers are likely to travel to the areas with high demand if they receive extra money (Cohen, Hahn, Hall, Levitt, & Metcalfe, 2016). The effectiveness of such an approach is evident in practice. After the concert of Ariana Grande, surge pricing allowed achieving a 100% completion rate, and the waiting time increased only moderately (A fare shake, 2016). Moreover, without the mentioned algorithm, the completion rate was less than 25%, and the waiting time was 2-8 minutes on New Year’s Eve in 2014.
The power of surge pricing should not be overestimated as the pre-emptive responses of drivers tend to improve, which would balance demand and supply. As for the fairness of such pricing, it is possible to suggest that those who have transportation alternatives are more sensitive to changes. The areas with little options can be characterized by more critical price increases, which seem to be unfair. Surge pricing that is based on machine-learning tools can be used in other businesses as well. For example, retailers can estimate the purchases of customers and predict their future needs to send them timely notifications and preparing the necessary products in stores.
References
Cohen, P., Hahn, R., Hall, J., Levitt, S., & Metcalfe, R. (2016). Using big data to estimate consumer surplus: The case of Uber (No. w22627). National Bureau of Economic Research. Web.
A fare shake. (2016). The Economist. Web.
Why Uber is an economist’s dream (Ep. 258). (2016). Web.