How Work From Home Affects Collaboration: A Large-Scale Study of Information Workers in a Natural Experiment During COVID-19

• URL: http://arxiv.org/abs/2007.15584v1
• Date: Thu, 30 Jul 2020 16:43:26 GMT
• Title: How Work From Home Affects Collaboration: A Large-Scale Study of Information Workers in a Natural Experiment During COVID-19
• Authors: Longqi Yang, Sonia Jaffe, David Holtz, Siddharth Suri, Shilpi Sinha, Jeffrey Weston, Connor Joyce, Neha Shah, Kevin Sherman, CJ Lee, Brent Hecht, Jaime Teevan
• Abstract summary: COVID-19 pandemic caused information workers to rapidly shift to working from home. Can we isolate the effects of WFH on information workers' collaboration activities from all other factors? We find that the effect of WFH is moderated by individual remote collaboration experience prior to WFH.
• Score: 8.864997915833182
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: The COVID-19 pandemic has had a wide-ranging impact on information workers such as higher stress levels, increased workloads, new workstreams, and more caregiving responsibilities during lockdown. COVID-19 also caused the overwhelming majority of information workers to rapidly shift to working from home (WFH). The central question this work addresses is: can we isolate the effects of WFH on information workers' collaboration activities from all other factors, especially the other effects of COVID-19? This is important because in the future, WFH will likely to be more common than it was prior to the pandemic. We use difference-in-differences (DiD), a causal identification strategy commonly used in the social sciences, to control for unobserved confounding factors and estimate the causal effect of WFH. Our analysis relies on measuring the difference in changes between those who WFH prior to COVID-19 and those who did not. Our preliminary results suggest that on average, people spent more time on collaboration in April (Post WFH mandate) than in February (Pre WFH mandate), but this is primarily due to factors other than WFH, such as lockdowns during the pandemic. The change attributable to WFH specifically is in the opposite direction: less time on collaboration and more focus time. This reversal shows the importance of using causal inference: a simple analysis would have resulted in the wrong conclusion. We further find that the effect of WFH is moderated by individual remote collaboration experience prior to WFH. Meanwhile, the medium for collaboration has also shifted due to WFH: instant messages were used more, whereas scheduled meetings were used less. We discuss design implications -- how future WFH may affect focused work, collaborative work, and creative work.

Related papers

• From Pre-training Corpora to Large Language Models: What Factors Influence LLM Performance in Causal Discovery Tasks? [51.42906577386907]
  This study explores the factors influencing the performance of Large Language Models (LLMs) in causal discovery tasks. A higher frequency of causal mentions correlates with better model performance, suggesting that extensive exposure to causal information during training enhances the models' causal discovery capabilities.
  arXiv  Detail & Related papers  (2024-07-29T01:45:05Z)
• DOMINO: Visual Causal Reasoning with Time-Dependent Phenomena [59.291745595756346]
  We propose a set of visual analytics methods that allow humans to participate in the discovery of causal relations associated with windows of time delay. Specifically, we leverage a well-established method, logic-based causality, to enable analysts to test the significance of potential causes. Since an effect can be a cause of other effects, we allow users to aggregate different temporal cause-effect relations found with our method into a visual flow diagram.
  arXiv  Detail & Related papers  (2023-03-12T03:40:21Z)
• From 996 to 007: Challenges of Working from Home During the Epidemic in China [15.731773874712154]
  During the COVID-19 epidemic in China, millions of workers in tech companies had to start working from home (WFH) We used the opportunity to describe the effect of WFH at scale for a sustained period of time. As the lockdown was easing, we conducted semi-structured interviews with 12 participants from China working in tech companies.
  arXiv  Detail & Related papers  (2022-01-22T13:05:28Z)
• ExcavatorCovid: Extracting Events and Relations from Text Corpora for Temporal and Causal Analysis for COVID-19 [63.72766553648224]
  ExcavatorCovid is a machine reading system that ingests open-source text documents. It extracts COVID19 related events and relations between them, and builds a Temporal and Causal Analysis Graph.
  arXiv  Detail & Related papers  (2021-05-05T01:18:46Z)
• Everything Has a Cause: Leveraging Causal Inference in Legal Text Analysis [62.44432226563088]
  Causal inference is the process of capturing cause-effect relationship among variables. We propose a novel Graph-based Causal Inference framework, which builds causal graphs from fact descriptions without much human involvement. We observe that the causal knowledge contained in GCI can be effectively injected into powerful neural networks for better performance and interpretability.
  arXiv  Detail & Related papers  (2021-04-19T16:13:10Z)
• Towards Causal Representation Learning [96.110881654479]
  The two fields of machine learning and graphical causality arose and developed separately. There is now cross-pollination and increasing interest in both fields to benefit from the advances of the other.
  arXiv  Detail & Related papers  (2021-02-22T15:26:57Z)
• Impact on the Productivity of Remotely Working IT Professionals of Bangladesh during the Coronavirus Disease 2019 [3.509221192489875]
  The recent pandemic situation has forced the IT professionals of Bangladesh to adopt remote work. The aim of this study is to find out whether remote work can be continued even after the lockdown is lifted.
  arXiv  Detail & Related papers  (2020-08-26T15:58:22Z)
• A Tale of Two Cities: Software Developers Working from Home During the COVID-19 Pandemic [16.982574711079423]
  The COVID-19 pandemic has provoked an overnight exodus of developers that normally worked in an office setting to working from home. To find out how developers and their productivity were affected, we distributed two surveys. We find that there is a dichotomy of developer experiences influenced by many different factors.
  arXiv  Detail & Related papers  (2020-08-25T16:27:21Z)
• Exploring the Impact of COVID-19 Lockdown on Social Roles and Emotions while Working from Home [7.017240138853753]
  This research investigates the impact of COVID-19 on five researchers' work and private roles, happiness, and mobile and desktop activity patterns. Our analysis show that researchers tend to work more during COVID-19 resulting in an imbalance of work and private roles. This shows a resilient adaptation to the disruption caused by the pandemic.
  arXiv  Detail & Related papers  (2020-07-24T05:17:01Z)
• Effectiveness and Compliance to Social Distancing During COVID-19 [72.94965109944707]
  We use a detailed set of mobility data to evaluate the impact that stay-at-home orders had on the spread of COVID-19 in the US. We show that there is a unidirectional Granger causality, from the median percentage of time spent daily at home to the daily number of COVID-19-related deaths with a lag of 2 weeks.
  arXiv  Detail & Related papers  (2020-06-23T03:36:19Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.