Navigating the maze: the effects of algorithmic management on employee performance

Mengzhe Liu, Yuanyuan Lan, Zhen Liu, Mingyue Liu and Yuhuan Xia ()
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Mengzhe Liu: Hunan Agricultural University
Yuanyuan Lan: Qingdao University
Zhen Liu: Shandong University
Mingyue Liu: Qingdao University
Yuhuan Xia: Shandong University

Palgrave Communications, 2024, vol. 11, issue 1, 1-10

Abstract: Abstract Recent computer science advancements are now integrated into the workplace, where management increasingly uses algorithm systems. However, despite numerous studies focusing on the impact of algorithms on employees, research on employee creative and adaptive performance remains relatively scarce. To address this research gap, we applied the ability-motivation-opportunity (AMO) theory and developed a moderated mediation model to examine how algorithmic management affects employee creative and adaptive performance. We administered a survey questionnaire within an information technology service firm in northern China and collected valid responses from 327 employees. We then analyzed the gathered data using SPSS 27.0 and Mplus 8.3 to test the proposed hypotheses. The research findings revealed a potential negative impact of algorithmic management on employee creative and adaptive performance. Specifically, we found that algorithmic management inhibits employees’ improvisation capability, resulting in decreased creative and adaptive performance. Furthermore, we discovered that algorithmic dependence can magnify the negative impact of algorithmic management on improvisation capability. This study offers fresh perspectives on algorithmic management’s impact on employee creative and adaptive performance, contributing to the existing literature. This research delves into the theoretical and practical significance of these findings.

Date: 2024
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DOI: 10.1057/s41599-024-03453-z

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