Research Data Leeds Repository

Citation

Davis, Matthew C. and Hughes, Helen P. N. and Rees, Simon and Wu, Chiahuei and Gritt, Emma and Collis, Hannah and Fang, Linhao (2023) Adapting Offices Cross-Sector Office Worker Surveys. University of Leeds. [Dataset] https://doi.org/10.5518/1305

Dataset description

Snapshot surveys with a cross-industry group of UK office workers to understand how their experience of hybrid working had changed over time. Data were collected via Prolific Academic using online surveys at T1 (August 2021), T2 (December 2021) and T3 (August 2022). Participants were matched across each time point T1 n=1025, T2 n=759, T3 n=451. Data includes a range of demographics, actual and preferred work patterns, perceptions of physical workspace, hybrid work experiences and psychological outcomes (e.g., wellbeing, work-life balance).

Keywords:	Hybrid Working; Offices; Psychology
Subjects:	C000 - Biological sciences > C800 - Psychology > C810 - Applied psychology > C814 - Organisational psychology
Divisions:	Faculty of Business > Socio-Technical Centre (STC)
Related resources:	Location Type https://doi.org/10.48785/100/124 Publication https://doi.org/10.48785/100/125 Publication https://doi.org/10.1108/PR-01-2023-0011 Publication https://eprints.whiterose.ac.uk/199554/ Publication
License:	Creative Commons Attribution 4.0 International (CC BY 4.0)
Date deposited:	08 Mar 2023 15:27
URI:	https://archive.researchdata.leeds.ac.uk/id/eprint/1077
Additional details Additional details Creators or authors: Creators ORCID Other ID Email Primary affiliation Primary affiliation ID Primary affiliation ID type Secondary affiliation Secondary affiliation ID Secondary affiliation ID type Davis, Matthew C. https://orcid.org/0000-0003-1577-7544 University of Leeds https://ror.org/024mrxd33 ror Hughes, Helen P. N. https://orcid.org/0000-0001-8454-8206 University of Leeds https://ror.org/024mrxd33 ror Rees, Simon https://orcid.org/0000-0003-4869-1632 University of Leeds https://ror.org/024mrxd33 ror Wu, Chiahuei https://orcid.org/0000-0002-8011-6323 University of Leeds https://ror.org/024mrxd33 ror Gritt, Emma https://orcid.org/0000-0002-2369-4928 University of Leeds https://ror.org/024mrxd33 ror Collis, Hannah https://orcid.org/0000-0002-7654-5643 University of Exeter https://ror.org/03yghzc09 ror Fang, Linhao https://orcid.org/0000-0002-9615-9037 University of Leeds https://ror.org/024mrxd33 ror Type of data: Dataset Research funders: ESRC Grant numbers: ES/W001764/1 Publication date: 2023 Resource language: English Metadata language: English Research project title: Adapting offices to support COVID-19 secure workplaces and emerging work patterns Publisher: University of Leeds Contact email: m.davis@leeds.ac.uk Last Modified: 03 Sep 2024 08:11

Files

Documentation

readme [3kB] readme [3kB] readme [3kB] Security: Anyone File name: readme_Davis_1305.txt Content type: Documentation Mime-Type: text/plain License: Creative Commons Attribution 4.0 International (CC BY 4.0) File size: 3kB

Data

Adapting Offices Snapshot Variable List Spreadsheet - Publicly Available Dataset [35kB] Adapting Offices Snapshot Variable List Spreadsheet - Publicly Available Dataset [35kB] Adapting Offices Snapshot Variable List Spreadsheet - Publicly Available Dataset [35kB] Security: Anyone File name: Adapting_Offices_Snapshot_Variable_List_Spreadsheet_Publicly_Available_Dataset.xlsx Content type: Data Description: List of variables captured at each time point. Mime-Type: application/vnd.openxmlformats-officedocument.spreadsheetml.sheet License: Creative Commons Attribution 4.0 International (CC BY 4.0) File size: 35kB

Adapting Offices Publicly Available Snapshot Dataset - T1, T2 and T3 [3MB] Adapting Offices Publicly Available Snapshot Dataset - T1, T2 and T3 [3MB] Adapting Offices Publicly Available Snapshot Dataset - T1, T2 and T3 [3MB] Security: Anyone File name: Publically_Available_Snapshot_Dataset_T1_T2_and_T3.sav Content type: Data Description: Data set of matched individual level data across 3 timepoints of cross-industry office worker survey License: Creative Commons Attribution 4.0 International (CC BY 4.0) File size: 3MB