Does leading through algorithmic management impact the workers’ well-being: a systematic literature review and research agenda
Shefali Sharma et al.
What the paper says
Purpose This study conducts a systematic literature review (SLR) to examine the impact of algorithmic management on workers’ well-being, addressing a research gap that has predominantly focussed on fragmented aspect of this relation. Design/methodology/approach An SLR, thematic analysis, and TCCM framework have been applied to analyse and synthesize insights from 29 studies retrieved from the Scopus database. Findings The study develops a conceptual framework to explore how algorithmic management impacts employee well-being in platform-based digital labour systems. The findings identify critical gaps in underexplored regions and industries, emphasizing the need for tailored interventions to ensure healthy digital workplaces. This research highlights interventions to mitigate adverse effects of algorithmic management and promote employee well-being in platform firms. Originality/value The study broadens the intellectual limits of algorithmic management research by integrating multidisciplinary theories to examine its impact on employee well-being and work-life balance thereby making way for seamless implementation of work-life fit. It proposes tailored interventions and policies to address challenges like fairness, privacy, technostress in the contemporary digital workplaces.
Evidence weight
Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40
| F · citation impact | 0.50 × 0.4 = 0.20 |
| M · momentum | 0.50 × 0.15 = 0.07 |
| V · venue signal | 0.50 × 0.05 = 0.03 |
| R · text relevance † | 0.50 × 0.4 = 0.20 |
† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.