ACADEMIC LEADERSHIP AND ORGANISATIONAL SUPPORT IN MITIGATING JOB BURNOUT AMONG CHINESE UNIVERSITY LECTURERS: EVIDENCE FROM THE JD-R FRAMEWORK
DOI:
https://doi.org/10.22452/mojem.vol14no4.1Keywords:
Role Stress, Self-Efficacy, Perceived Organisational Support, Job Burnout, Job Demands-Resources Theory, Chinese University LecturersAbstract
Job burnout is an important issue faced by university lecturers today. However, there is limited research that explores the predictors of lecturers' burnout from an organizational perspective, where the focus has been on individual psychological factors. This study uses the Job Demands-Resources (JD-R) framework complemented with Conservation of Resources (COR) theory to examine the statistical relationships among role stress, self-efficacy, perceived organisational support, and job burnout among Chinese university lecturers. This cross-sectional study included responses from 328 full-time lecturers at various universities in China and used scales validated in previous studies. Results showed that role stress was positively associated with job burnout (β = 0.38, p < 0.001). Self-efficacy showed a significant indirect statistical association in the role stress-job burnout relationship (indirect effect = 0.07, 95% CI [0.02, 0.12]). Perceived organisational support significantly moderated the role stress-job burnout relationship (β = -0.16, p = .001), with a weaker positive association between role stress and burnout at higher levels of organisational support. Furthermore, perceived organisational support was positively associated with self-efficacy (β = 0.31, p < 0.001). Overall, the proposed model explained 34 per cent of the variance in job burnout. These findings position lecturer burnout as an educational management and organisational issue in which workload design, role clarity, institutional support, and management practices warrant attention. Meanwhile, academic leadership is interpreted as a possible organisational mechanism through which perceived support may be enacted rather than as a directly measured predictor.








