Expanding a(n) (electric) bicycle-sharing system to a new city: Prediction of demand with spatial regression and random forests

Sergio Guidon, Daniel J. Reck and Kay Axhausen

Journal of Transport Geography, 2020, vol. 84, issue C

Abstract: Bicycle-sharing systems have experienced strong growth in the last two decades as part of a global trend that started in the 1990s and accelerated after 2005. Early bicycle-sharing systems were provided primarily as a public service by cities. Today, major international bicycle-sharing companies are emerging and seeking to expand their operations to new cities.

Keywords: E-bike sharing; Bicycle sharing; Demand prediction; Vehicle sharing; Spatial regression; Random forests (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (8)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0966692319307136

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:jotrge:v:84:y:2020:i:c:s0966692319307136

DOI: 10.1016/j.jtrangeo.2020.102692

Access Statistics for this article

Journal of Transport Geography is currently edited by Frank Witlox

More articles in Journal of Transport Geography from Elsevier
Bibliographic data for series maintained by Catherine Liu ().