Associate Professor Zhang Zhipeng of the School of Economics and Management (SEM) at the University of Science and Technology Beijing (USTB) has published a research article as first author in Human Resource Management, a leading international management journal included in the Financial Times’ list of 50 leading business-school journals (FT50).
As the platform economy continues to expand, algorithmic management has become a central means by which online labor platforms manage workers. However, its effects on platform workers’ service performance are complex, and the underlying mechanisms remain insufficiently understood. To address this gap, the study draws on self-determination theory and examines perceived algorithmic management practices across four dimensions: matching, direction, evaluation, and discipline. The research comprises two empirical studies: a scenario-based experiment involving ride-hailing drivers and a field survey involving both ride-hailing drivers and food-delivery riders.
The findings reveal two distinct motivational pathways through which algorithmic management affects service performance. First, perceived algorithmic matching, direction, and evaluation enhance service performance by strengthening autonomous motivation, whereas perceived algorithmic discipline undermines performance by reducing autonomous motivation. Second, perceived algorithmic matching, evaluation, and discipline reduce service performance by increasing controlled motivation, while perceived algorithmic direction improves performance by reducing controlled motivation.
The study further identifies online community support as an important moderating factor. Specifically, online community support strengthens the positive effects of algorithmic matching and evaluation on service performance through autonomous motivation, while mitigating their negative effects through controlled motivation. These findings clarify the conditions under which algorithmic management practices shape platform workers’ service performance.
The study makes three key academic contributions. First, it conceptualizes algorithmic management as a multidimensional construct and demonstrates how its different dimensions affect workers’ motivation in distinct ways, extending research on algorithmic management and emerging forms of employment. Second, it establishes the mediating roles of autonomous and controlled motivation, shedding light on the mechanisms underlying the relationship between algorithmic management and service performance. Third, it incorporates online community support into the analytical framework, moving beyond a predominant focus on the characteristics of algorithmic systems to highlight the importance of social context. In practical terms, the findings offer actionable insights for platform companies seeking to optimize algorithmic management practices, foster online community support, and improve workers’ service performance.
Human Resource Management, published by Wiley, is a leading international academic journal dedicated to advancing theoretical and empirical research in human resource management. Its areas of interest include strategic human resource management, employee behavior and organizational effectiveness, diversity and inclusion, and emerging theories and methods in the field. The journal is included in the Financial Times’ FT50 list of leading business-school journals and is recognized for its rigorous peer-review standards and contribution to advancing research in management.
Zhang Zhipeng is an associate professor and master’s supervisor at USTB SEM and a visiting scholar at the University of Huddersfield in the United Kingdom. In 2024, he was selected for the second cohort of the Beijing Social Science Fund’s Young Academic Leaders program. His research focuses on organizational behavior in human–technology interaction, value allocation involving data as a new factor of production, and the protection of workers’ rights in emerging forms of employment. He has led research projects funded by the National Natural Science Foundation of China, the Ministry of Education’s special fund for philosophy and social sciences, and Beijing’s natural science and social science research programs.
His research has been published in leading international journals, including Human Resource Management, Journal of Organizational Behavior, Journal of Business Ethics, and Journal of Vocational Behavior, as well as leading Chinese journals such as Management World, Acta Psychologica Sinica, and Nankai Business Review. He has also provided management simulation training for organizations including CITIC Group, China National Offshore Oil Corporation (CNOOC), Aviation Industry Corporation of China (AVIC), China Huadian Corporation, Tianjin TEDA Group, Shandong Hengyuan Technology, and Weifang Bank. In addition, he has advised companies including ThunderSoft, Beijing Rui'an Technology, Qiya Group, and Transfar Group on corporate culture, talent development, and related management issues.
