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
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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
Version 2 - 2023-05-31 (latest)
Version 1 - 2023-05-30
Usage statistics
339
views
296
downloads
Geolocation
The Netherlands
Time coverage 2021
Licence CC0
Interoperability
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.ResearchDataFormat
*csv; *.pdf, *.txt, *.savAssociated peer-reviewed publication
Interior design features predicting satisfaction with office workspace privacy and noiseOrganizations
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