Differential Effects of Algorithmic Management Functions on Employee Helping Behavior: Evidence from High-Tech Manufacturing Firms in China

Abstract

Algorithmic systems increasingly perform managerial functions such as task allocation, performance-based pay, monitoring, and scheduling. Because these functions intervene in different aspects of work, their consequences for employee behavior may differ. This study examines the relationships between four algorithmic management functions and employee helping behavior in high-tech manufacturing firms in China. Using a two-wave, multi-source matched survey of 450 employees, the results show that task allocation and performance-based pay are positively associated with helping behavior, whereas monitoring and scheduling are negatively associated with helping behavior. Pairwise coefficient equality tests further show that task allocation and performance-based pay differ significantly from monitoring and scheduling, while the effects within each pair do not differ significantly. These findings indicate that algorithmic management is behaviorally heterogeneous. By distinguishing specific management functions, the study provides a more precise account of how digital management systems relate to informal employee cooperation in high-tech manufacturing and offers comparative implications for organizations in other emerging economies undergoing digital transformation.