Data underlying the conference paper: Interior design features predicting satisfaction with office workspace privacy and noise.
doi:10.4121/d09043de-63d4-47da-9360-2a6d04d5ebd3.v2
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/d09043de-63d4-47da-9360-2a6d04d5ebd3
doi: 10.4121/d09043de-63d4-47da-9360-2a6d04d5ebd3
Datacite citation style:
Colenberg, Susanne (2023): Data underlying the conference paper: Interior design features predicting satisfaction with office workspace privacy and noise. Version 2. 4TU.ResearchData. dataset. https://doi.org/10.4121/d09043de-63d4-47da-9360-2a6d04d5ebd3.v2
Other citation styles (APA, Harvard, MLA, Vancouver, Chicago, IEEE) available at Datacite
Dataset
choose version:
version 2 - 2023-05-31 (latest)
version 1 - 2023-05-30
Anonymous survey data on interior design features of office workspaces and user satisfaction with privacy and noise
history
- 2023-05-30 first online
- 2023-05-31 published, posted
publisher
4TU.ResearchData
format
*csv; *.pdf, *.txt, *.sav
associated peer-reviewed publication
Interior design features predicting satisfaction with office workspace privacy and noise
organizations
TU Delft, Faculty of Industrial Design Engineering, Department of Human-Centered Design.
DATA
files (5)
- 420,734 bytesMD5:
1f2fc13a95751473b2133d1081e5236a
Output regression analysis.pdf - 339,217 bytesMD5:
a1dfbec80f074a31aef922957c7be32e
Questionnaire workspace privacy.pdf - 1,678 bytesMD5:
7eef97a02d7de24fb1c7e5cf92c1849b
READ ME.txt - 87,069 bytesMD5:
429d5c4f1c7c7873293e8a9eb57c0d7d
Workspace privacy.csv - 177,749 bytesMD5:
7b017a8d52460adf72104219385ed01e
Workspace privacy.sav -
download all files (zip)
1,026,447 bytes unzipped