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Ridership estimation of a new LRT system: Direct demand model approach

Konstantinos L. Kepaptsoglou, Antony Stathopoulos, Matthew G. Karlaftis

2016-12-10articleJournal of Transport Geography37 citationsclosed

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Transportation Planning and Optimization transportation and logistics systems Transportation and Mobility Innovations

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Stored only when both papers are in the corpus — 37 citations exist upstream.

References

2004Factors influencing light-rail station boardings in the United States

2011Transit ridership forecasting at station level: an approach based on distance-decay weighted regression

2007Transit-Oriented Development's Ridership Bonus: A Product of Self-Selection and Public Policies

2011An analysis of Metro ridership at the station-to-station level in Seoul

2013Analysis of Metro ridership at station level and station-to-station level in Nanjing: an approach based on direct demand models

2006Evaluating rail transit benefits: A comment

2014Transit ridership estimation with network Kriging: a case study of Second Avenue Subway, NYC

2008Trip end models of local rail demand in England and Wales

Cited by

2018Evaluating the Ability of Transit Direct Ridership Models to Forecast Medium-Term Ridership Changes: Evidence from San Francisco

2019Geographically Modeling and Understanding Factors Influencing Transit Ridership: An Empirical Study of Shenzhen Metro

2022Simple pre-post analysis overestimates the impacts of new public transit services on ridership: Evidence from a quasi-experimental study of new bus rapid transit in Columbus, Ohio, USA

2017Transportation Network Companies

Details

Year2016

Typearticle

VenueJournal of Transport Geography

Languageen

Files0 public / 0

Identifiers

doi10.1016/j.jtrangeo.2016.12.004

openalex_workW612458659

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