Effect of Transparency of Algorithmic Performance Management on Proactive Work Behavior: Role of Motivation to Improve Performance and Psychological Ownership

Yining Cai and Chen Wang
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Yining Cai: School of Management, Shanghai University, China
Chen Wang: School of Management, Shanghai University, China

International Journal of Asian Business and Information Management (IJABIM), 2024, vol. 15, issue 1, 1-17

Abstract: Algorithm transparency, as an important factor in explaining the algorithm black box, is attracting increasing attention from scholars on the impact of algorithm system transparency on employee behavior. This study aims to investigate the effect of algorithmic performance management transparency on employees' proactive work behavior and constructs a moderated mediation model. The model was tested with a sample of 321 employees from five high-tech companies in China. The results suggest that transparency of algorithmic performance management promotes employee proactive work behavior via employees' motivation to improve performance, while the interaction between transparency of algorithmic performance management and psychological ownership weakens this influence mechanism. Therefore, this study reveals the positive effects of transparency in algorithmic performance management as well as its boundary conditions, providing theoretical and practical insights into the application of algorithms in organizations.

Date: 2024
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