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Mapping talent management excellence: a bibliometric exploration of influential authors, institutions, and clusters

Neema Gupta et al.

International Journal of Services Economics and Management2026https://doi.org/10.1504/ijsem.2026.151934article
AJG 1
Weight
0.50

What the paper says

Research studies on talent management have shown momentum progress in the last two decades and need analysis for identifying the major research works conducted and the changes during these years. The study aimed to assess documents published on talent management (TM) by using the bibliometric tool. The study assessed 638 documents published over two decades (2001 to 2021), extracted from the Scopus database. The findings tell that talent management persists in a broad area of study, although the study comes especially from European and North American nations. The little presentation from developing nations (Portugal, Pakistan and Saudi Arabia) shows that more study is required based on TM. The study determined three research clusters: concept development in the research area of talent management, the role of TM in SHRM, global talent challenges and management. Finally, the future research scopes suggested in this review study will provide a direction to future researchers.

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https://doi.org/https://doi.org/10.1504/ijsem.2026.151934

Or copy a formatted citation

@article{neema2026,
  title        = {{Mapping talent management excellence: a bibliometric exploration of influential authors, institutions, and clusters}},
  author       = {Neema Gupta et al.},
  journal      = {International Journal of Services Economics and Management},
  year         = {2026},
  doi          = {https://doi.org/https://doi.org/10.1504/ijsem.2026.151934},
}

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Mapping talent management excellence: a bibliometric exploration of influential authors, institutions, and clusters

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Evidence weight

0.50

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

F · citation impact0.50 × 0.4 = 0.20
M · momentum0.50 × 0.15 = 0.07
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.