Evidence map›Paper›PMID 36968661›Full record

ArticleProcedia computer science2023

Is the Structure of "Regular Working Days" about to Dissolve? Changes in Employees' Time-Use Patterns Working in Enterprise Collaboration Systems During the COVID-19 Pandemic.

Nathalie Scharf, Laura Lükemann, Petra Schubert, Susan Williams, Anja Abendroth, Antje Schwarz

Abstract read
In one paragraph

Article in Procedia computer science, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Nathalie ScharfCenter for Enterprise Information Research, University of Koblenz, Universitätsstr. 1, 56070 Koblenz, Germany.
Laura LükemannBielefeld University, Universitätsstr. 25, 33615 Bielefeld, Germany.
Petra SchubertCenter for Enterprise Information Research, University of Koblenz, Universitätsstr. 1, 56070 Koblenz, Germany.
Susan WilliamsCenter for Enterprise Information Research, University of Koblenz, Universitätsstr. 1, 56070 Koblenz, Germany.
Anja AbendrothBielefeld University, Universitätsstr. 25, 33615 Bielefeld, Germany.
Antje SchwarzBielefeld University, Universitätsstr. 25, 33615 Bielefeld, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The measures taken during the COVID-19 pandemic have strengthened Work from Home and the use of digital communication technologies and digital collaboration. The resulting flexibility in terms of control over time and place of work can support workers in improving their work-life balance. In this paper, we investigate whether workers using digital communication technologies made use of this flexibility and changed the distribution of their work hours across the week and day. To answer this question, we investigate the use of an Enterprise Collaboration System in 2019-2022. Using real-world data, a MS Power BI dashboard was created following the steps suggested by the Social Collaboration Analytics Framework (SCAF). The dashboard shows that the system use increased during the COVID-19 pandemic. Furthermore, an expansion of work on weekends and outside of regular working hours can be observed. Although, timely adjustments of use-patterns were highest in the beginning of the pandemic, long-term trends could be observed as well. The results indicate that knowledge workers used digital collaboration technologies to restructure working days, according to their specific personal and business needs while working from home. The paper is a valuable starting point in the context of a long-term interdisciplinary research project on the digitalisation of the workplace.

Indexed as

COVID-19CSCWDashboardEnterprise Collaboration SystemsTime-Use PatternsWork from Home (WFH)Working Hours

Identifiers

PMID36968661
PMCPMC10030180

What OpenQuestion holds

Textmetadata
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.