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Workers’ Health under Algorithmic Management: Emerging Findings and Urgent Research Questions
Algorithms are increasingly used instead of humans to perform core management functions, yet public health research on the implications of this phenomenon for worker health and well-being has not kept pace with these changing work arrangements. Algorithmic management has the potential to influence s...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9859016/ https://www.ncbi.nlm.nih.gov/pubmed/36673989 http://dx.doi.org/10.3390/ijerph20021239 |
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author | Vignola, Emilia F. Baron, Sherry Abreu Plasencia, Elizabeth Hussein, Mustafa Cohen, Nevin |
author_facet | Vignola, Emilia F. Baron, Sherry Abreu Plasencia, Elizabeth Hussein, Mustafa Cohen, Nevin |
author_sort | Vignola, Emilia F. |
collection | PubMed |
description | Algorithms are increasingly used instead of humans to perform core management functions, yet public health research on the implications of this phenomenon for worker health and well-being has not kept pace with these changing work arrangements. Algorithmic management has the potential to influence several dimensions of job quality with known links to worker health, including workload, income security, task significance, schedule stability, socioemotional rewards, interpersonal relations, decision authority, and organizational trust. To describe the ways algorithmic management may influence workers’ health, this review summarizes available literature from public health, sociology, management science, and human-computer interaction studies, highlighting the dimensions of job quality associated with work stress and occupational safety. We focus on the example of work for platform-based food and grocery delivery companies; these businesses are growing rapidly worldwide and their effects on workers and policies to address those effects have received significant attention. We conclude with a discussion of research challenges and needs, with the goal of understanding and addressing the effects of this increasingly used technology on worker health and health equity. |
format | Online Article Text |
id | pubmed-9859016 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-98590162023-01-21 Workers’ Health under Algorithmic Management: Emerging Findings and Urgent Research Questions Vignola, Emilia F. Baron, Sherry Abreu Plasencia, Elizabeth Hussein, Mustafa Cohen, Nevin Int J Environ Res Public Health Review Algorithms are increasingly used instead of humans to perform core management functions, yet public health research on the implications of this phenomenon for worker health and well-being has not kept pace with these changing work arrangements. Algorithmic management has the potential to influence several dimensions of job quality with known links to worker health, including workload, income security, task significance, schedule stability, socioemotional rewards, interpersonal relations, decision authority, and organizational trust. To describe the ways algorithmic management may influence workers’ health, this review summarizes available literature from public health, sociology, management science, and human-computer interaction studies, highlighting the dimensions of job quality associated with work stress and occupational safety. We focus on the example of work for platform-based food and grocery delivery companies; these businesses are growing rapidly worldwide and their effects on workers and policies to address those effects have received significant attention. We conclude with a discussion of research challenges and needs, with the goal of understanding and addressing the effects of this increasingly used technology on worker health and health equity. MDPI 2023-01-10 /pmc/articles/PMC9859016/ /pubmed/36673989 http://dx.doi.org/10.3390/ijerph20021239 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Review Vignola, Emilia F. Baron, Sherry Abreu Plasencia, Elizabeth Hussein, Mustafa Cohen, Nevin Workers’ Health under Algorithmic Management: Emerging Findings and Urgent Research Questions |
title | Workers’ Health under Algorithmic Management: Emerging Findings and Urgent Research Questions |
title_full | Workers’ Health under Algorithmic Management: Emerging Findings and Urgent Research Questions |
title_fullStr | Workers’ Health under Algorithmic Management: Emerging Findings and Urgent Research Questions |
title_full_unstemmed | Workers’ Health under Algorithmic Management: Emerging Findings and Urgent Research Questions |
title_short | Workers’ Health under Algorithmic Management: Emerging Findings and Urgent Research Questions |
title_sort | workers’ health under algorithmic management: emerging findings and urgent research questions |
topic | Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9859016/ https://www.ncbi.nlm.nih.gov/pubmed/36673989 http://dx.doi.org/10.3390/ijerph20021239 |
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