@inproceedings{adbf003d4fb544bbbf03ab8a353c7e55,
title = "Exploring shared-bike travel patterns using big data: Evidence in Chicago and Budapest",
abstract = "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, with analysis of approximately two million transaction data records 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, with the largest share of trips occurring in the afternoon peak. Appropriate usage of open-source big-data provides important lessons for successful vehicle sharing models, allowing the application of the findings to other cities and mobility options where these systems are still developing.",
keywords = "Big data, Bike-sharing systems, Mobility, User travel behavior",
author = "Ali Soltani and Tam{\'a}s M{\'a}trai and Rosalia Camporeale and Andrew Allan",
year = "2019",
doi = "10.1007/978-3-030-19424-6_4",
language = "English",
isbn = "9783030194239",
series = "Lecture Notes in Geoinformation and Cartography",
publisher = "Springer-Verlag",
pages = "53--68",
editor = "Stan Geertman and Qingming Zhan and Andrew Allan and Christopher Pettit",
booktitle = "Computational Urban Planning and Management for Smart Cities",
note = "16th International Conference on Computers in Urban Planning and Urban Management, CUPUM 2019 ; Conference date: 08-07-2019 Through 12-07-2019",
}