Customer preference and station network in the London bike-share system
File(s)
Accepted version
Author(s)
He, Pu
Zheng, Fanyin
Belavina, Elena
Girotra, Karan
Type
Journal Article
Abstract
We study customer preference for the bike-share system in the city of London. We estimate a structural demand model on the station network to learn the preference parameters and use the estimated model to provide insights on the design and expansion of the bike-share system. We highlight the importance of network effects in understanding customer demand and evaluating expansion strategies of transportation networks. In the particular example of the London bike-share system, we find that allocating resources to some areas of the station network can be 10 times more beneficial than others in terms of system usage and that the currently implemented station density rule is far from optimal. We develop a new method to deal with the endogeneity problem of the choice set in estimating demand for network products. Our method can be applied to other settings in which the available set of products or services depends on demand.
Date Issued
2021-03-01
Date Acceptance
2020-02-03
Citation
Management Science, 2021, 67 (3), pp.1392-1412
ISSN
0025-1909
Publisher
Institute for Operations Research and Management Sciences
Start Page
1392
End Page
1412
Journal / Book Title
Management Science
Volume
67
Issue
3
Copyright Statement
© 2020, INFORMS.
Identifier
https://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000632021900004&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=a2bf6146997ec60c407a63945d4e92bb
Subjects
bike sharing
Business & Economics
customer preference
empirical research
Management
Operations Research & Management Science
Science & Technology
Social Sciences
structural estimation
Technology
Publication Status
Published
Date Publish Online
2020-08-05