Workers’ Health under Algorithmic Management: Emerging Findings and Urgent Research Questions
Emilia F. Vignola (),
Sherry Baron,
Elizabeth Abreu Plasencia,
Mustafa Hussein and
Nevin Cohen
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Emilia F. Vignola: Department of Community Health and Social Sciences, City University of New York Graduate School of Public Health and Health Policy, 55 West 125th Street, New York, NY 10027, USA
Sherry Baron: Barry Commoner Center for Health and the Environment, Queens College, City University of New York, 311 Remsen Hall, 65-30 Kissena Blvd, Queens, NY 11367, USA
Elizabeth Abreu Plasencia: Barry Commoner Center for Health and the Environment, Queens College, City University of New York, 311 Remsen Hall, 65-30 Kissena Blvd, Queens, NY 11367, USA
Mustafa Hussein: Department of Health Policy and Management, City University of New York Graduate School of Public Health and Health Policy, 55 West 125th Street, New York, NY 10027, USA
Nevin Cohen: Department of Health Policy and Management, City University of New York Graduate School of Public Health and Health Policy, 55 West 125th Street, New York, NY 10027, USA
IJERPH, 2023, vol. 20, issue 2, 1-14
Abstract:
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.
Keywords: algorithmic management; platform work; gig economy; worker health; work stress (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2023
References: View complete reference list from CitEc
Citations: View citations in EconPapers (1)
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Persistent link: https://EconPapers.repec.org/RePEc:gam:jijerp:v:20:y:2023:i:2:p:1239-:d:1030818
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