Bike-sharing systems are an emerging form of sharing-mobility in many cities worldwide. The travel patterns of users that take advantage of smart devices to ride a shared-bicycle in two large cities (Chicago and Budapest) have been investigated, looking at approximately two million transaction data associated with bike trips made over a three-month period in each location. Several aspects of user travel behavior - such as day and time of travel, frequency of usage, duration of usage, seasonal and peak/off-peak variations, major origin/destinations – have been included in this analysis.

The results show that in both cities the bike-sharing option is a male-dominated alternative, particularly welcomed by younger groups, and with the largest share of trips that takes place in the afternoon peak.

A proper usage of open-source big-data can help to learn lessons by successful vehicle shared models, applying the findings to other realities where these systems are still developing.