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Remote work mindsets predict emotions and productivity in home office: A longitudinal study of knowledge workers during the Covid-19 pandemic

Howe, Lauren C; Menges, Jochen I (2022). Remote work mindsets predict emotions and productivity in home office: A longitudinal study of knowledge workers during the Covid-19 pandemic. Human - Computer Interaction, 37(6):481-507.

Abstract

Millions of employees across the globe, including a large proportion of knowledge workers, transitioned to remote work during the COVID-19 pandemic. As remote work continues to characterize work post-crisis, it is imperative to understand how employees adjust to remote work. The current research explores the extent to which knowledge workers hold a fixed mindset about remote work (e.g., that a person either is or is not suited to remote work and this cannot be changed) and tested how this mindset shaped well-being during coronavirus-related lockdown. In a longitudinal five-week study of 113 knowledge workers transitioning to remote work, we find that knowledge workers who endorsed a more fixed mindset about remote work experienced more negative and less positive emotion during remote work. The increased negative emotion prompted by fixed mindsets was associated with lesser perceived productivity among these knowledge workers in subsequent weeks. We conclude that understanding how fundamental beliefs (e.g., beliefs about the learnability of remote work) affect employee experiences can help create a brighter future as technology further enables remote work. Encouraging employees to view remote work as a skill that can be learned and developed could help people thrive in the new world of work.

Additional indexing

Item Type:Journal Article, refereed, original work
Communities & Collections:03 Faculty of Economics > Department of Business Administration
Dewey Decimal Classification:330 Economics
Scopus Subject Areas:Social Sciences & Humanities > Applied Psychology
Physical Sciences > Human-Computer Interaction
Scope:Discipline-based scholarship (basic research)
Language:English
Date:2 November 2022
Deposited On:27 Dec 2021 05:49
Last Modified:26 Dec 2024 02:39
Publisher:Taylor & Francis
ISSN:0737-0024
Additional Information:This is an Accepted Manuscript of an article published by Taylor & Francis in Human - Computer Interaction on 02.11.2022, available online: http://wwww.tandfonline.com/10.1080/07370024.2021.1987238.
OA Status:Green
Free access at:Publisher DOI. An embargo period may apply.
Publisher DOI:https://doi.org/10.1080/07370024.2021.1987238
Other Identification Number:merlin-id:21552
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