Abstract
While social segregation is often assessed using static data concerning residential areas, the extent to which people with diverse background travel to the same destinations may offer an additional perspective on the extent of urban segregation. This study further contributes to the measurement of activity-based social segregation between multiple groups using public transport smart card data. In particular, social segregation is quantified using the ordinal information theory index to measure the income group mix at public transport journey destination zones. The method is applied to the public transport smart card data of Stockholm County, Sweden. Applying the index on 2017–2020 data sets for a selected week, shows significant differences between income groups’ segregation along the radial public transport corridors following the opening of a major rail project in the summer of 2017. The overall slight decrease in segregation over the years can be linked to declining segregation in the city center as a travel destination and its public transport hubs. Increasing zonal segregation is observed in suburban and rural zones with commuter train stations. This method helps to quantify social segregation, enriching the analysis of urban segregation and can aid in evaluating policies based on the dynamics of social life.
| Original language | English |
|---|---|
| Article number | 103642 |
| Journal | Journal of Transport Geography |
| Volume | 110 |
| DOIs | |
| Publication status | Published - 1 Jul 2023 |
Bibliographical note
Publisher Copyright:© 2023 The Author(s)
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
-
SDG 11 Sustainable Cities and Communities
Research Groups and Themes
- SPS Centre for Urban and Public Policy Research
- SPS Governance and Public Policy Research Centre
Keywords
- Ex-post transport appraisal
- Public transport
- Smart card data
- Social segregation
Fingerprint
Dive into the research topics of 'Measuring activity-based social segregation using public transport smart card data'. Together they form a unique fingerprint.Cite this
- APA
- Author
- BIBTEX
- Harvard
- Standard
- RIS
- Vancouver