ArticleFrontiers in psychology2025
The double-edged sword effect of algorithmic management on work engagement of platform workers: the roles of appraisals and resources.
Article in Frontiers in psychology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
3 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Algorithmic management in the global gig economy: an interdisciplinary systematic literature review and critical discourse analysis.Frontiers in sociology · 2026Pooled it
- From algorithmic efficiency to cascading health burdens: a text-mining study of online food delivery riders in the platform economy.Frontiers in public health · 2026Article
- Algorithmic management and employee innovation: unveiling the mediating mechanisms of perceived fit, perceived control and job crafting.Frontiers in psychology · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Purpose: This study aims to explore how food delivery workers' perceptions of threat and challenge mediate the influence of algorithmic management on their work engagement, and to examine the moderating roles of emotional stability and perceived organizational support (POS) in this process. Design/methodology/approach: The present research conceptualized and validated a framework to investigate the double-edged sword influence of algorithmic management on work engagement, highlighting its potential to be both beneficial and detrimental. Drawing from a sample of 292 delivery workers working in two major food delivery platforms in China, this study employed SPSS 20.0 and MPLUS 7.4 for the statistical examination of the hypotheses. Findings: The findings reveal that threat appraisal serves as a negative mediator between algorithmic management and work engagement, while challenge appraisal served as a positive mediator in this relationship. Emotional stability and perceived organizational support (POS) acted as moderators of these effects, indicating that when algorithmic management was perceived more as a challenge than a threat, it was more likely to enhance the engagement behavior at work. Practical implications: This study uncovers algorithmic management's dual effects. Employees with high emotional stability and organizational support (POS) who view it as a challenge (not threat) show stronger work engagement. Managers should cultivate these psychological resources to enhance technology adoption success. Originality/value: This study advances the algorithmic management literature by investigating its dual effects on food delivery workers' work engagement. We uncover the underlying mediating mechanisms and demonstrate how emotional stability and perceived organizational support (POS) moderate these relationships.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.