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Remote work and the COVID-19 pandemic: An artificial intelligence-based topic modeling and a future agenda
As remote work has become more common than ever throughout the COVID-19 pandemic, it has drawn special attention from scholars. However, the outcome has been significantly sporadic and fragmented. In our systematic review, we use artificial intelligence-based machine learning tools to examine the re...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Published by Elsevier Inc.
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9489997/ https://www.ncbi.nlm.nih.gov/pubmed/36156905 http://dx.doi.org/10.1016/j.jbusres.2022.113303 |
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author | Aleem, Majid Sufyan, Muhammad Ameer, Irfan Mustak, Mekhail |
author_facet | Aleem, Majid Sufyan, Muhammad Ameer, Irfan Mustak, Mekhail |
author_sort | Aleem, Majid |
collection | PubMed |
description | As remote work has become more common than ever throughout the COVID-19 pandemic, it has drawn special attention from scholars. However, the outcome has been significantly sporadic and fragmented. In our systematic review, we use artificial intelligence-based machine learning tools to examine the relevant extant literature in terms of its dominant topics, diversity, and dynamics. Our results identify-eight research themes: (1) Effect on employees at a personal level, (2) Effect on employees’ careers, (3) Family life and gender roles, (4) Health, well-being, and safety, (5) Labor market dynamics, (6) Economic implications, (7) Remote work management, (8) Organizational remote work strategies. With further content analysis, we structure the sporadic research into three overarching categories. Finally, for each category, we offer a detailed agenda for further research. |
format | Online Article Text |
id | pubmed-9489997 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Published by Elsevier Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-94899972022-09-21 Remote work and the COVID-19 pandemic: An artificial intelligence-based topic modeling and a future agenda Aleem, Majid Sufyan, Muhammad Ameer, Irfan Mustak, Mekhail J Bus Res Article As remote work has become more common than ever throughout the COVID-19 pandemic, it has drawn special attention from scholars. However, the outcome has been significantly sporadic and fragmented. In our systematic review, we use artificial intelligence-based machine learning tools to examine the relevant extant literature in terms of its dominant topics, diversity, and dynamics. Our results identify-eight research themes: (1) Effect on employees at a personal level, (2) Effect on employees’ careers, (3) Family life and gender roles, (4) Health, well-being, and safety, (5) Labor market dynamics, (6) Economic implications, (7) Remote work management, (8) Organizational remote work strategies. With further content analysis, we structure the sporadic research into three overarching categories. Finally, for each category, we offer a detailed agenda for further research. Published by Elsevier Inc. 2023-01 2022-09-21 /pmc/articles/PMC9489997/ /pubmed/36156905 http://dx.doi.org/10.1016/j.jbusres.2022.113303 Text en © 2022 Published by Elsevier Inc. Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active. |
spellingShingle | Article Aleem, Majid Sufyan, Muhammad Ameer, Irfan Mustak, Mekhail Remote work and the COVID-19 pandemic: An artificial intelligence-based topic modeling and a future agenda |
title | Remote work and the COVID-19 pandemic: An artificial intelligence-based topic modeling and a future agenda |
title_full | Remote work and the COVID-19 pandemic: An artificial intelligence-based topic modeling and a future agenda |
title_fullStr | Remote work and the COVID-19 pandemic: An artificial intelligence-based topic modeling and a future agenda |
title_full_unstemmed | Remote work and the COVID-19 pandemic: An artificial intelligence-based topic modeling and a future agenda |
title_short | Remote work and the COVID-19 pandemic: An artificial intelligence-based topic modeling and a future agenda |
title_sort | remote work and the covid-19 pandemic: an artificial intelligence-based topic modeling and a future agenda |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9489997/ https://www.ncbi.nlm.nih.gov/pubmed/36156905 http://dx.doi.org/10.1016/j.jbusres.2022.113303 |
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