Strategic Leadership and Knowledge Sharing: A Data-Driven Bibliometric Analysis Using Scopus and WoS Databases (2001-2023)

Rayees Farooq et al.

Journal of Information and Knowledge Management2026https://doi.org/10.1142/s0219649226500085article
ABDC C
Weight
0.50

What the paper says

Strategic leadership is considered crucial for an organisation’s success, and with the emergence of a knowledge-based economy, exchanging knowledge to align with the firm’s strategic goals is necessary. This research comprehensively examines the intricate relationship between strategic leadership and knowledge-sharing through a data-driven bibliometric analysis. Through SPAR-4-SLR, the authors examined 83 journal publications indexed in the ABDC JQL 2022 from Scopus and Web of Science databases based on keywords from past studies. The findings map the intellectual structure and evolution of the domain. The results unveil key publications, authors, interrelationships, emerging topics, and theoretical contributions, providing a nuanced understanding of global annual publication trends.

Open paper page →

Cite this paper

https://doi.org/https://doi.org/10.1142/s0219649226500085

Or copy a formatted citation

@article{rayees2026,
  title        = {{Strategic Leadership and Knowledge Sharing: A Data-Driven Bibliometric Analysis Using Scopus and WoS Databases (2001-2023)}},
  author       = {Rayees Farooq et al.},
  journal      = {Journal of Information and Knowledge Management},
  year         = {2026},
  doi          = {https://doi.org/https://doi.org/10.1142/s0219649226500085},
}

Paste directly into BibTeX, Zotero, or your reference manager.

Flag this paper

Strategic Leadership and Knowledge Sharing: A Data-Driven Bibliometric Analysis Using Scopus and WoS Databases (2001-2023)

Flags are reviewed by the Arbiter methodology team within 5 business days.


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.