  The rise of Uber as the global alternative taxi operator has attracted a lot
of interest recently. Aside from the media headlines which discuss the new
phenomenon, e.g. on how it has disrupted the traditional transportation
industry, policy makers, economists, citizens and scientists have engaged in a
discussion that is centred around the means to integrate the new generation of
the sharing economy services in urban ecosystems. In this work, we aim to shed
new light on the discussion, by taking advantage of a publicly available
longitudinal dataset that describes the mobility of yellow taxis in New York
City. In addition to movement, this data contains information on the fares paid
by the taxi customers for each trip. As a result we are given the opportunity
to provide a first head to head comparison between the iconic yellow taxi and
its modern competitor, Uber, in one of the world's largest metropolitan
centres. We identify situations when Uber X, the cheapest version of the Uber
taxi service, tends to be more expensive than yellow taxis for the same
journey. We also demonstrate how Uber's economic model effectively takes
advantage of well known patterns in human movement. Finally, we take our
analysis a step further by proposing a new mobile application that compares
taxi prices in the city to facilitate traveller's taxi choices, hoping to
ultimately to lead to a reduction of commuter costs. Our study provides a case
on how big datasets that become public can improve urban services for consumers
by offering the opportunity for transparency in economic sectors that lack up
to date regulations.
