Identifying the Transit Needs of Socioeconomic Groups by Evaluating the Relationship between a Network's Supply and Demand: A Case Study of the City of Amsterdam

Master Thesis (2020)
Author(s)

B.H. Drybrough (TU Delft - Civil Engineering & Geosciences)

Contributor(s)

O Cats – Graduation committee member (TU Delft - Transport and Planning)

Niels van Oort – Graduation committee member (TU Delft - Transport and Planning)

M Kroesen – Graduation committee member (TU Delft - Transport and Logistics)

Machiel Kouwenberg – Graduation committee member (Vervoerregio Amsterdam)

Faculty
Civil Engineering & Geosciences
Copyright
© 2020 Ben Drybrough
More Info
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Publication Year
2020
Language
English
Copyright
© 2020 Ben Drybrough
Graduation Date
25-11-2020
Awarding Institution
Delft University of Technology
Programme
Civil Engineering | Transport and Planning
Faculty
Civil Engineering & Geosciences
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Abstract

An inclusive and sustainable transport network allows people the opportunity to access their daily needs. When there is a discrepancy between someone’s transport needs and their supplied network, they are at the risk of experiencing transport poverty. This study looks to define the transport needs for clusters of neighbourhoods of different socioeconomic and demographic characteristics in Amsterdam, The Netherlands by evaluating the relationship between the network’s supply and demand. Neighbourhoods are grouped through their characteristics using a Latent Class Clustering Analysis into likewise clusters. Supply and demand indicators are designed for each neighbourhood using GTFS and smart card ridership data. The effect of a neighbourhood’s cluster on the relationship is analyzed through an interaction effects linear regression. It was found that improvements to the supply indicators had a positive relationship with the overall demand of the network. However, this is consistent for all defined clusters of Amsterdam which is contrary to the expectations of the analysis. It was assumed that the supply indicators, reflecting convenience and efficiency of the network, would be needed variably for different socioeconomic groups of Amsterdam. These findings provide valuable insights into the current needs of Amsterdam residents, the state of the public transit network, and how transport planners should focus future infrastructure improvements. Insights are also gathered on how transport poverty research may be improved through statistical clustering techniques and using data in order to measure the use of the network.

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