Background and Objective: The main purpose of the current research is to identify the impact of algorithmic management for human resource management in the gig economy with a meta-synthesis approach.
Methodology: This study follows a developmental, qualitative, and documentary design. Using an analytical-descriptive approach, the research implemented Sandelowski and Barroso’s seven-stage meta-synthesis for systematic data collection and analysis. In order to identify the consequences, researchers systematically search for research related to these consequences in 6 scientific databases: Science Direct, Emerald, Wiley, Sage, Taylor & Francis, and the Scopus citation database between 2010 and 2024. In the initial investigations, 120 sources were found, and after screening and validation and using the CASP tool, finally 24 articles were analyzed.
Findings: The findings of the present study show that a total of 2 main consequences of algorithmic management in the field of human resource management in the gig economy have been identified, including negative consequences and positive consequences, and 36 sub-consequences.
Conclusion: The findings show that algorithmic management in the field of human resource management has both positive and negative aspects. On the positive side, organizations have improved and enhanced some of these activities by using algorithmic processes to automate human resource management activities in relation to the organization, employees, and customers. On the negative side, the data-driven approach dehumanizes work, and algorithms take over roles that have traditionally been the preserve of human resource professionals.