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Performance Appraisal within Human Resource Management: A Bibliometric Analysis of Structure and Evolution

Isabelle-Ana-Maria Vilsan et al.

Economics and Applied Informatics2025https://doi.org/10.35219/eai15840409544article
ABDC C
Weight
0.37

What the paper says

The purpose of this paper is to outline the position of employee performance appraisal (PA) within human resource management (HRM) and its recent evolution. Based on a bibliometric analysis of keywords, citations and co-occurrence networks conducted between 2020 and 2025, the results indicate a stable EP-HRM core, supported by three related directions: (i) the operational-processual dimension (training, career development, HR practices), (ii) employee outcomes (engagement, satisfaction, retention), (iii) the technological component (artificial intelligence – AI, data analytics). In 2025, the network is more integrated and structured; AI is solidly connected to HRM, but the link with PA remains incipient. We conclude that the field is conceptually consolidating, with a close connection between practices and organisational objectives, while the integration of digital tools in professional performance evaluation is still developing. Future research directions are suggested regarding standardisation, transparency, and evaluation of effects on organisational outcomes.

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https://doi.org/https://doi.org/10.35219/eai15840409544

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@article{isabelle-ana-maria2025,
  title        = {{Performance Appraisal within Human Resource Management: A Bibliometric Analysis of Structure and Evolution}},
  author       = {Isabelle-Ana-Maria Vilsan et al.},
  journal      = {Economics and Applied Informatics},
  year         = {2025},
  doi          = {https://doi.org/https://doi.org/10.35219/eai15840409544},
}

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Evidence weight

0.37

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.16 × 0.4 = 0.06
M · momentum0.53 × 0.15 = 0.08
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.