Unveiling perceptions on academic leadership effectiveness: PLS-SEM, FSQCA, and NCA approaches - S. M. Mahbubur Rahman; Ummah Tafsirun; Md. Faisal-E-Alam; Paulo Ferreira; Luís Loures; Rui Alexandre Castanho (PLoS ONE, 2025)
Academic leadership plays a critical role in fulfilling higher education institutions’ missions, fostering a competent workforce, and becoming a key driver in unlocking the potential to achieve sustainability goals. Within this context, the leadership effectiveness of academic deans is particularly significant. This study aims to identify the factors influencing the academic leadership effectiveness in public universities in Bangladesh. The study collected data from 318 faculty members of public universities. A combined methodology consisting of Partial Least Squares-Structural Equation Modeling (PLS-SEM), Fuzzy-Set Qualitative Comparative Analysis (fsQCA), and Necessary Condition Analysis (NCA) was utilized to analyze the collected data. The PLS-SEM results indicated that vision and goal setting (VG), management of the unit (MU), interpersonal relationships (IR), communication skills (CS), research/professional endeavors (PE), and quality of education in the unit (QEU) significantly influence deans’ leadership effectiveness. Further, five necessary and six sufficient conditions were discovered by fsQCA results, which also demonstrated the nonlinear and intricate interaction effects of the factors leading to leadership effectiveness (LE). Importantly, NCA findings revealed that all factors are essential for LE and have meaningful and substantial impact. Also, a minimum of 14.78% VG, 20.75% MU, 23.27% IR, 33.96% CS, 16.98% PE, and 10.06% QEU must be met to accomplish an 80% LE. Therefore, the findings provide useful insights for the higher education sector, university top management, potential academic leaders, and relevant stakeholders to improve leadership effectiveness at the tertiary education level. Moreover, this study is the first to explain the effectiveness of deans’ leadership through an expanded methodology that integrates both symmetric and asymmetric methods.