Journal of Student Research 2018

44 Journal Student Research This study examined the effect of the presence of Uber on taxi fares. To perform the analysis, I first gathered taxi fares in several cities, for rides of various distances. Then, I examined the difference of these fares in markets where Uber was present and operating, to those where Uber was not in operation or was banned. Empirical results suggest that the presence of Uber reduces the average one-mile, five-mile, and 10-mile fare, after adjusting for regional bias. The use of ride-sharing platforms has substantially increased since 2009. These ride-sharing platforms have proven to create considerable tension with existing regulatory frameworks, even though consumers have an increasing interest in their use (Gevero, Durante, & Alves, 2016). Several studies have examined ride-sharing platforms, the dynamic pricing structures, the barriers to entry, and the effect of a disruptive competitor (Chen, 2016; Swelbar & Wittman, 2013; Wallsten, 2015). However, there is no research examining the direct impact of ride-sharing presence on taxi fare. Uber introduced a dynamic pricing scheme that capitalizes on imbalances in supply and demand of rides during peak transportation times. The dynamic pricing model, i.e., surge pricing, is made up of two components: (1) to increase the supply of drivers by incentivizing them to provide additional rides, and (2) to intentionally reduce demand temporarily using price discrimination. Surge pricing is a salient and criticized feature of Uber (and other ride-sharing platforms) because passengers are required to pay a surcharge fee in addition to the original fare. Surge pricing has proven to be effective for ride-sharing platforms but cannot be applied to the taxi industry. Taxi drivers provide services at regulated prices and cannot temporarily change prices due to fluctuations in supply and demand. Changes in price happen infrequently, and thus taxi drivers are limited in their opportunities to attract customers while remaining competitive with ride-sharing platforms (Wallsten, 2015). Taxi services are subjected to various regulations, e.g., entry restriction, price control, in most urban areas. These regulations impose high barriers to entry in the taxi industry. 1 To become a taxi driver in New York City, drivers must secure a taxi medallion, which serves as a special license from the city. Each year the city distributes a fixed number of medallions 1 Regulations may impact the empirical results, due to regulation stickiness. Stickiness oc curs when a price regulation is in place and restricts fares from being altered in response to competition. In the analysis, stickiness of pricing was not visible, which could be due to the cross-sectional data set. The results predict a lower bound estimation. The use of panel data in future analysis may allow for stickiness to appear. Additionally, the inclusion of additional control variables to account for market regulations would be beneficial. Literature Review