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

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Authors: Zhipeng Zhang, Shuxia Zhang, Chao Liu, Haoyu Zhang, Jun Liu
Cited by: 2
References: 81

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.

Fields of Study & Subjects

Digital Economy and Work Transformation AI in Service Interactions Sharing Economy and Platforms

Publication details

Journal / source
Human Resource Management
Publisher
Wiley
Volume
65
Issue
4
Pages
1075–1095
Publication date
23 February 2026
Language
EN