Transformational Leadership and Organizational Commitment: A 2024 Analytical Scoping Review of Empirical Evidence

This analytical scoping review examines the empirical relationship between transformational leadership and organizational commitment in studies published exclusively in 2024. A total of 17 empirical studies were systematically identified, selected, and analyzed to map current methodological and thematic trends. The review reveals that Indonesia emerged as the leading context, contributing the majority of studies, indicating a strong regional interest in leadership research within Southeast Asia. Across the selected papers, Structural Equation Modelling using Partial Least Squares (SEM-PLS) was the most widely adopted analytical technique, reflecting researchers’ preference for robust, variance-based modelling approaches suitable for complex organizational constructs. Overall, the evidence consistently supports a positive association between transformational leadership and organizational commitment, with several studies highlighting mediating roles such as job satisfaction, psychological empowerment, and work engagement. This scoping review not only synthesizes the current empirical landscape but also identifies methodological gaps, geographical concentrations, and emerging patterns that can guide future research on leadership and commitment dynamics.

Authors

Publication Details

Journal
International Journal of Academic Research in Business and Social Sciences
Published
2025-12-03
DOI
https://doi.org/10.6007/ijarbss/v15-i12/27125
Primary Topic
Employee Performance and Leadership
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Transformational Leadership and Organizational Commitment: A 2024 Analytical Scoping Review of Empirical Evidence

Suleman Muhammad Khan, Norashikin Mahmud, Maria Fayyaz
International Journal of Academic Research in Business and Social Sciences
Employee Performance and Leadership
article

Transformational Leadership and Organizational Commitment: A 2024 Analytical Scoping Review of Empirical Evidence

Suleman Muhammad Khan, Norashikin Mahmud, Maria Fayyaz
article en

Abstract

This analytical scoping review examines the empirical relationship between transformational leadership and organizational commitment in studies published exclusively in 2024. A total of 17 empirical studies were systematically identified, selected, and analyzed to map current methodological and thematic trends. The review reveals that Indonesia emerged as the leading context, contributing the majority of studies, indicating a strong regional interest in leadership research within Southeast Asia. Across the selected papers, Structural Equation Modelling using Partial Least Squares (SEM-PLS) was the most widely adopted analytical technique, reflecting researchers’ preference for robust, variance-based modelling approaches suitable for complex organizational constructs. Overall, the evidence consistently supports a positive association between transformational leadership and organizational commitment, with several studies highlighting mediating roles such as job satisfaction, psychological empowerment, and work engagement. This scoping review not only synthesizes the current empirical landscape but also identifies methodological gaps, geographical concentrations, and emerging patterns that can guide future research on leadership and commitment dynamics.

International Journal of Academic Research in Business and Social SciencesVol. 15(12)
Openalex Percentile: Top 55%
Employee Performance and Leadership
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.