Will Employees Still Speak up Under Algorithmic Management? The Differential Effects of Distinct Algorithmic Functions—Evidence from the Meituan Platform in China

Read full text
Authors: Wanliang Lin, Mingyu Zhang, Wenjia Zhang, Can Zhang
Cited by: 1
References: 54

Abstract

Employees’ voice is an important source of organizational learning and adaptive change. As algorithmic management is increasingly applied across organizational management processes, an urgent practical question arises: Does it affect employees’ participation in organizational improvement through voice? To address this challenge, drawing on signaling theory, this study examines the differential effects of distinct dimensions of algorithmic management on voice, while also considering work locus of control as a key moderating variable. We collected one-to-one matched data from 351 employees and their supervisors in a large Chinese platform-based enterprise. We tested the hypothesized theoretical model using structural equation modeling and bootstrapping procedures. The results show that algorithmic feedback enhances employees’ felt responsibility for constructive change, which in turn promotes employees’ voice. In contrast, algorithmic directing, algorithmic scheduling, and algorithmic monitoring undermine employees’ felt responsibility for constructive change and thereby inhibit voice. In addition, work locus of control moderates these relationships: employees with an external work locus of control strengthen the negative effects of algorithmic directing, algorithmic scheduling, and algorithmic monitoring, whereas employees with an internal work locus of control strengthen the positive effect of algorithmic feedback. These findings deepen our understanding of how different dimensions of algorithmic management shape voice and offer practical insights for fostering voice in contexts characterized by algorithmic management.

Fields of Study & Subjects

Digital Economy and Work Transformation AI and HR Technologies Cyberloafing and Workplace Behavior

Publication details

Journal / source
Systems
Publisher
MDPI AG
Volume
14
Issue
5
Pages
569–569
Publication date
16 May 2026
Language
EN