Data underlying the publication: 'Global gains and local pains: spatial justice in the planning discourse on hinterland logistics'

doi: 10.4121/f7ac0c2c-94d8-4aab-9803-ed5f601012e1.v1
The doi above is for this specific version of this dataset, which is currently the latest. Newer versions may be published in the future. For a link that will always point to the latest version, please use
doi: 10.4121/f7ac0c2c-94d8-4aab-9803-ed5f601012e1
Datacite citation style:
Nefs, Merten; KiesKompas ; Tilburg ; Horst aan de Maas (2024): Data underlying the publication: 'Global gains and local pains: spatial justice in the planning discourse on hinterland logistics'. Version 1. 4TU.ResearchData. dataset. https://doi.org/10.4121/f7ac0c2c-94d8-4aab-9803-ed5f601012e1.v1
Other citation styles (APA, Harvard, MLA, Vancouver, Chicago, IEEE) available at Datacite
Dataset

This PhD thesis chapter is a revised version of a conference paper for the Association of European Schools of Planning (AESOP) 2022 in Tartu, Estonia:


Nefs, M. (2022). Beyond Global Gains and Local Pains - spatial inequality of hinterland logistics. In Aesop (Ed.), AESOP 2022 Tartu: Spatial Justice (Aesop, pp. 249–256). Aesop.


This dataset contains three parts:

  1. Data retrieved from election information website KiesKompas, concerning party positions on development of distribution centres in The Netherlands, in the 2023 Provincial elections. This part includes code to treat and visualise the data.
  2. List of selected and screened newspaper articles on development of distribution centres in two case provinces in the Netherlands (articles available upon request).
  3. List of selected and screened municipal council decisions, in Tilburg and Horst aan de Maas, concerning development of distribution centres, along with the original memos (retrieved from the municipal websites).
history
  • 2024-01-12 first online, published, posted
publisher
4TU.ResearchData
format
PDF, JSON, R, XLSX, CSV, PNG
organizations
TU Delft, Faculty of Architecture and the Built Environment

DATA

files (5)