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Analysis of the relationship between urban dynamics and prevalence of remote work based on population data generated from cellular networks
The COVID-19 pandemic has accelerated the introduction of remote work as one way to ensure employee safety and reduce the amount of interpersonal contact while continuing business operations. Knowing the degree of prevalence of remote work and its establishment are considered to be important factors...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10656566/ https://www.ncbi.nlm.nih.gov/pubmed/37978335 http://dx.doi.org/10.1038/s41598-023-47513-x |
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author | Akatsuka, Hiroto Toyoda, Masashi |
author_facet | Akatsuka, Hiroto Toyoda, Masashi |
author_sort | Akatsuka, Hiroto |
collection | PubMed |
description | The COVID-19 pandemic has accelerated the introduction of remote work as one way to ensure employee safety and reduce the amount of interpersonal contact while continuing business operations. Knowing the degree of prevalence of remote work and its establishment are considered to be important factors in future policies and urban planning. We applied non-negative matrix factorization to population-change data obtained from a mobile phone network to extract the component of working people, and analyzed the changes pre- and post-pandemic. Using the Wilcoxon signed-rank test, we confirmed that the number of people working in office and residential districts has significantly changed at a significance level of 1% in urban areas centered around Tokyo and Osaka, the two largest cities in Japan. Time-series data show that the number of workers is decreasing in office districts and increasing in residential districts, suggesting increased prevalence of remote work due to the COVID-19 pandemic and that it has become established. In addition, in urban areas centered around Tokyo, we confirmed that there is a moderate correlation between the changes in the number of people working in office districts and the capital size of corporations in the same area. |
format | Online Article Text |
id | pubmed-10656566 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-106565662023-11-17 Analysis of the relationship between urban dynamics and prevalence of remote work based on population data generated from cellular networks Akatsuka, Hiroto Toyoda, Masashi Sci Rep Article The COVID-19 pandemic has accelerated the introduction of remote work as one way to ensure employee safety and reduce the amount of interpersonal contact while continuing business operations. Knowing the degree of prevalence of remote work and its establishment are considered to be important factors in future policies and urban planning. We applied non-negative matrix factorization to population-change data obtained from a mobile phone network to extract the component of working people, and analyzed the changes pre- and post-pandemic. Using the Wilcoxon signed-rank test, we confirmed that the number of people working in office and residential districts has significantly changed at a significance level of 1% in urban areas centered around Tokyo and Osaka, the two largest cities in Japan. Time-series data show that the number of workers is decreasing in office districts and increasing in residential districts, suggesting increased prevalence of remote work due to the COVID-19 pandemic and that it has become established. In addition, in urban areas centered around Tokyo, we confirmed that there is a moderate correlation between the changes in the number of people working in office districts and the capital size of corporations in the same area. Nature Publishing Group UK 2023-11-17 /pmc/articles/PMC10656566/ /pubmed/37978335 http://dx.doi.org/10.1038/s41598-023-47513-x Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Akatsuka, Hiroto Toyoda, Masashi Analysis of the relationship between urban dynamics and prevalence of remote work based on population data generated from cellular networks |
title | Analysis of the relationship between urban dynamics and prevalence of remote work based on population data generated from cellular networks |
title_full | Analysis of the relationship between urban dynamics and prevalence of remote work based on population data generated from cellular networks |
title_fullStr | Analysis of the relationship between urban dynamics and prevalence of remote work based on population data generated from cellular networks |
title_full_unstemmed | Analysis of the relationship between urban dynamics and prevalence of remote work based on population data generated from cellular networks |
title_short | Analysis of the relationship between urban dynamics and prevalence of remote work based on population data generated from cellular networks |
title_sort | analysis of the relationship between urban dynamics and prevalence of remote work based on population data generated from cellular networks |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10656566/ https://www.ncbi.nlm.nih.gov/pubmed/37978335 http://dx.doi.org/10.1038/s41598-023-47513-x |
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