[Supporting Data and Software] Potential of on‑demand services for urban travel
doi:10.4121/b47f8a10-e237-4e18-8b65-57b146a8ff39.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/b47f8a10-e237-4e18-8b65-57b146a8ff39
doi: 10.4121/b47f8a10-e237-4e18-8b65-57b146a8ff39
Datacite citation style:
Geržinič, Nejc; van Oort, Niels; Oded Cats; Hoogendoorn-Lanser, Sascha; Hoogendoorn, S.P.(Serge) (2023): [Supporting Data and Software] Potential of on‑demand services for urban travel. Version 1. 4TU.ResearchData. dataset. https://doi.org/10.4121/b47f8a10-e237-4e18-8b65-57b146a8ff39.v1
Other citation styles (APA, Harvard, MLA, Vancouver, Chicago, IEEE) available at Datacite
Dataset
The files included below are part of the CriticalMaaS research on ride-hailing and on-demand transport services. In this study, passengers' preferences for commute and leisure trips in Dutch urban areas were analysed.
A mode choice stated preference survey was carried out in the Netherlands in February 2020, where respondents had to make a choice for bike, car, public transport or FLEX (on-demand service) for six commute trips (work/education) and six leisure trips (social/recreation) in an urban area.
More information about the research and the data can be found in the files below and the linked paper.
history
- 2023-03-23 first online, published, posted
publisher
4TU.ResearchData
format
*.py, *.html,*.csv,*.docx
associated peer-reviewed publication
Potential of on‑demand services for urban travel
funding
- CriticalMaaS (grant code 804469) European Research Council
organizations
TU Delft, Faculty of Civil Engineering and Geosciences, Department of Transport and Planning, Smart Public Transport Lab
DATA
files (5)
- 1,474 bytesMD5:
16422bdd2750657cdacda26710ae609d
README.txt - 10,652 bytesMD5:
4cef94ce9cb1ea18ed68dd46141a6a3d
final_choice_model.py - 1,687 bytesMD5:
0e135ff42ecc72a04724c77c0422045c
formatted_dataset.csv - 211,560 bytesMD5:
d62014b28165b7e94cc0d6b33a02e3e7
model_outcome.html - 298,394 bytesMD5:
ca3c55a7f92d2c05d79ef9ae72865434
survey_transcript.docx -
download all files (zip)
523,767 bytes unzipped