Review of the knowledge base of servant leadership in higher education research, 1998 to 2023.
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| Title: | Review of the knowledge base of servant leadership in higher education research, 1998 to 2023. |
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| Authors: | Adams, Donnie1,2 (AUTHOR) donnie.adams@unimelb.edu.au, Feng, Xueling3 (AUTHOR), Omar, Intan Marfarrina3 (AUTHOR) |
| Source: | Journal of Higher Education Policy & Management. Dec2025, Vol. 47 Issue 6, p629-648. 20p. |
| Subject Terms: | *Higher education, *Citation analysis, *Citation indexes, *Bibliometrics, Servant leadership, Leadership, Conceptual structures |
| Abstract: | Recent research has focused on leadership styles that are deeply rooted in people-centred behaviours and ethics, and particularly, servant leadership. This review aimed to identify the intellectual structure of servant leadership in higher education research in the last two decades, from 1998 through 2023, using bibliographic data to trace its development and characteristics within a broad perspective. The Scopus database was used to identify 50 relevant documents, with an author co-citation analysis on VOSviewer software employed to analyse them. The review findings unveiled important aspects of the knowledge base on servant leadership, namely the volume and geographic distribution, the intellectual structure and key scholars, and the conceptual structure, including topical foci, and commonly used concepts. This bibliometric review offers empirically based insights into the evolution, and current status of the literature on servant leadership in higher education research. It also provides directions for future research on servant leadership, identifying areas where further development, particularly in higher education, is needed. [ABSTRACT FROM AUTHOR] |
| Copyright of Journal of Higher Education Policy & Management is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Education Research Complete |
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