Exploring the emerging research themes on algorithmic management: a bibliometric analysis approach

Purpose The research aims to map and quantify the academic literature on algorithmic management from a bibliometric viewpoint, as well as to present a thorough analysis of the future research development trends in the current domain. Design/methodology/approach In total, 715 articles were extracted from the Scopus database (till February, 2024). The study uses bibliometrics, performance and science mapping analysis to depict publication trends, productive authors, journals and co-occurrence of keywords. Findings The analysis revealed a substantial rise in the publications from 2019 onwards. Additionally, the most influential paper focusing on global gig economy was cited 724 times. The top contributing countries were the United States followed by the United Kingdom and Spain. Nieborg D.B. was the most productive author and Graham M. was the most frequently cited author. Moreover, keyword co-occurrence analysis revealed five additional themes. The theoretical foundations were emphasised by content analysis and keyword co-occurrence analysis, uncovered new trends and offered direction for further investigation. Practical implications The outcomes of this article have important implications for academics looking to explore this area further, for policymakers establishing algorithmic management within organisations for employee welfare, and for practitioners creating algorithmic management codes. Originality/value This paper offers a thorough and in-depth bibliometric examination of the literature on algorithmic management. The paper outlines the comprehensive literature review of journal articles and suggested future research agenda on algorithmic management.