Purpose This study aims to identify research trends and map the academic structure in the field of employee performance over the past five years. Given the increasing complexity of organizations and post-pandemic work dynamics, bibliometric mapping is necessary to understand the evolution of themes, the contributions of key literature, and the future directions of knowledge development. Design/Methodology/Approach A total of 2,044 articles published between 2020 and 2025 are collected from the Scopus database. The article selection process adheres to the PRISMA 2020 guidelines to ensure transparency and methodological rigor. Analysis is conducted using Bibliometrix R and VOSviewer, employing performance analysis and science mapping techniques. Visualization results include trending topics, a word cloud, the most globally cited documents, and network visualizations identifying the primary thematic clusters within the literature. Findings The findings indicate that research topics are shifting from general issues toward contemporary themes such as digital leadership, work well-being, and organizational adaptation to global changes. Seven primary clusters are identified, reflecting a multidisciplinary approach encompassing structural, psychological, and contextual dimensions. Additionally, articles with high normalized citation scores demonstrate that significant contributions come from practical and cross-sectoral studies. Originality/value The novelty of this study lies in mapping the intellectual structure and research trends of employee performance using Bibliometrix R and VOSviewer, focusing on the post-pandemic period (2020-2025). It uniquely employs trending topics and normalized citation analysis to identify emerging themes and influential publications in contemporary research.
Building similarity graph...
Analyzing shared references across papers
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Maryadi Maryadi
University of Brawijaya
Hamidah Nayati Utami
University of Brawijaya
Arik Prasеtya
University of Brawijaya
F1000Research
University of Brawijaya
Building similarity graph...
Analyzing shared references across papers
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Maryadi et al. (Fri,) studied this question.
synapsesocial.com/papers/68e79cf2ed88661f66c2e246 — DOI: https://doi.org/10.12688/f1000research.165774.2