No One Is an Island: How Online Community Support Moderates the Dual Motivational Pathways From Perceived Algorithmic Management Practices to Service Performance

ABSTRACT Drawing on the self‐determination theory, this research examines the dual motivational mechanisms through which four dimensions of perceived algorithmic management practices (PAMP; i.e., matching, direction, evaluation, and discipline) influence service performance, as well as the moderating role of online community support (OCS). Two empirical studies were conducted: a scenario‐based experiment with ride‐hailing drivers (Study 1) and a hybrid‐sample field survey (Study 2). Results reveal that perceived algorithmic matching, direction, and evaluation enhance service performance via increased autonomous motivation, whereas perceived algorithmic discipline undermines service performance through reduced autonomous motivation. Meanwhile, controlled motivation links perceived algorithmic matching, evaluation, and discipline to reduced service performance, while perceived algorithmic direction positively contributes to service performance through diminished controlled motivation. Importantly, OCS amplifies the positive effects of perceived algorithmic matching and evaluation on service performance via autonomous motivation and attenuates their negative effects via controlled motivation. This study elucidates the complex motivational consequences of algorithmic management practices and identifies OCS as a critical social‐contextual moderator shaping app‐worker outcomes.

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Publication Details

Journal
Human Resource Management
Published
2026-02-23
DOI
https://doi.org/10.1002/hrm.70062
Primary Topic
Digital Economy and Work Transformation
Type
article
Field-Weighted Citation Impact
0.00
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article

No One Is an Island: How Online Community Support Moderates the Dual Motivational Pathways From Perceived Algorithmic Management Practices to Service Performance

Shuxia Zhang, Haoyu Zhang, Chao Liu, Jun Liu et al.
Human Resource Management
Digital Economy and Work Transformation
article

No One Is an Island: How Online Community Support Moderates the Dual Motivational Pathways From Perceived Algorithmic Management Practices to Service Performance

Shuxia Zhang, Haoyu Zhang, Chao Liu, Jun Liu, Zhipeng Zhang
article en

Abstract

ABSTRACT Drawing on the self‐determination theory, this research examines the dual motivational mechanisms through which four dimensions of perceived algorithmic management practices (PAMP; i.e., matching, direction, evaluation, and discipline) influence service performance, as well as the moderating role of online community support (OCS). Two empirical studies were conducted: a scenario‐based experiment with ride‐hailing drivers (Study 1) and a hybrid‐sample field survey (Study 2). Results reveal that perceived algorithmic matching, direction, and evaluation enhance service performance via increased autonomous motivation, whereas perceived algorithmic discipline undermines service performance through reduced autonomous motivation. Meanwhile, controlled motivation links perceived algorithmic matching, evaluation, and discipline to reduced service performance, while perceived algorithmic direction positively contributes to service performance through diminished controlled motivation. Importantly, OCS amplifies the positive effects of perceived algorithmic matching and evaluation on service performance via autonomous motivation and attenuates their negative effects via controlled motivation. This study elucidates the complex motivational consequences of algorithmic management practices and identifies OCS as a critical social‐contextual moderator shaping app‐worker outcomes.

Human Resource Management
Beijing Technology and Business University (CN), Wayne State University (US), Wuhan University of Technology (CN), Beijing Sport University (CN), University of Science and Technology Beijing (CN)
Openalex Percentile: Top 36%
Digital Economy and Work Transformation
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No One Is an Island: How Online Community Support Moderates the Dual Motivational Pathways From Perceived Algorithmic Management Practices to Service Performance — Shuxia Zhang, Haoyu Zhang, et al. · Human Resource Management (2026) | TGRS Research Map | TGRS