Do algorithmically managed employees feel objectified and isolated? A serial mediation approach affecting work disengagement

Purpose Gig workers confront a number of cognitive challenges, including objectification, social isolation and feeling alienated from their jobs, despite the rising push for employers to embrace the idea of algorithmic management. Hence, this study aims to investigate the mediating role of objectification and workplace social isolation on the relationship between algorithmic management and work disengagement. Design/methodology/approach Based on the job demands–resources theory, this research hypothesizes the cognitive impact upon gig workers while they are controlled by algorithms. The data was collected from 417 gig workers from Delhi, NCR, India. The analysis was done through covariance-based structural equation modeling, which was used to examine the formulated theoretical model. Findings Results revealed that employee’s managed through algorithms had greater work disengagement. Objectification and workplace social isolation significantly mediated the relationship between algorithmic management and work disengagement. Furthermore, the serial mediation of the factors was also evaluated. Originality/value Although the impact of algorithmic management on diverse workplace behaviors and outcomes is, at present, becoming increasingly popular, there is very little actual data to support this idea. These results are extremely pertinent to managers because they offer much-needed guidance on how to deal with employee isolation and objectification – problems that might result from incorrect algorithm implementation – and promote a happier, healthier work environment. Moreover, these findings contribute to expanding existing literature by offering distinctive perspective on use of algorithms to manage employees, particularly in developing countries.

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Publication Details

Journal
International journal of organizational analysis
Published
2025-09-02
DOI
https://doi.org/10.1108/ijoa-03-2025-5287
Primary Topic
Digital Economy and Work Transformation
Type
article
Field-Weighted Citation Impact
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article

Do algorithmically managed employees feel objectified and isolated? A serial mediation approach affecting work disengagement

Meenal Arora, Amit Mittal, Nidhi Dhankar
International journal of organizational analysis
Digital Economy and Work Transformation
article

Do algorithmically managed employees feel objectified and isolated? A serial mediation approach affecting work disengagement

Meenal Arora, Amit Mittal, Nidhi Dhankar
article en

Abstract

Purpose Gig workers confront a number of cognitive challenges, including objectification, social isolation and feeling alienated from their jobs, despite the rising push for employers to embrace the idea of algorithmic management. Hence, this study aims to investigate the mediating role of objectification and workplace social isolation on the relationship between algorithmic management and work disengagement. Design/methodology/approach Based on the job demands–resources theory, this research hypothesizes the cognitive impact upon gig workers while they are controlled by algorithms. The data was collected from 417 gig workers from Delhi, NCR, India. The analysis was done through covariance-based structural equation modeling, which was used to examine the formulated theoretical model. Findings Results revealed that employee’s managed through algorithms had greater work disengagement. Objectification and workplace social isolation significantly mediated the relationship between algorithmic management and work disengagement. Furthermore, the serial mediation of the factors was also evaluated. Originality/value Although the impact of algorithmic management on diverse workplace behaviors and outcomes is, at present, becoming increasingly popular, there is very little actual data to support this idea. These results are extremely pertinent to managers because they offer much-needed guidance on how to deal with employee isolation and objectification – problems that might result from incorrect algorithm implementation – and promote a happier, healthier work environment. Moreover, these findings contribute to expanding existing literature by offering distinctive perspective on use of algorithms to manage employees, particularly in developing countries.

International journal of organizational analysis
Chitkara University (IN), Maharshi Dayanand University (IN)
Openalex Percentile: Top 69%
Digital Economy and Work Transformation
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