Author
Abstract
Burnout and resilience have become central themes in the study of employee well-being, particularly in high-pressure professions like teaching. Burnout—characterized by emotional exhaustion, cynicism, and reduced efficacy—is driven by job demands such as emotional strain, work-family conflict, and role overload (Miltojević et al., 2021; Cao & Zhang, 2021; Lambert et al., 2024), while resilience, the capacity to adapt and recover, acts as a protective buffer (Sanhokwe & Takawira, 2022; Rizana et al., 2022). Guided by the Job Demands-Resources (JD-R) model and Dagodog’s Burnout–Resilience Model, this study employed a quantitative design using a validated self-administered questionnaire grounded in the JD-R model and the Resilience at Work (RAW) scale. A sample of at least 110 secondary and tertiary educators was recruited through quota and snowball sampling, with data analyzed via weighted means and path analysis. Ethical protocols were strictly followed, including informed consent and confidentiality. Findings reveal a complex dynamic: while challenge demands were most prevalent, emotional and time demands were the strongest predictors of burnout—especially emotional exhaustion—though burnout models showed low predictive power (R² = 1.7%–11.9%). In contrast, resilience models showed significantly stronger fits, particularly for stress management (R² = 46.3%) and well-being (R² = 36.7%), with personal resources like emotional intelligence and optimism (β > 0.5) emerging as key drivers. Motivational and job resources had moderate effects, whereas HR strategies performed poorly and received the lowest mean rating (3.30). The study concludes that although some job stressors are unavoidable, organizations can mitigate their effects by strengthening personal development programs and enhancing key support systems to cultivate a more resilient, engaged, and productive workforce.
Suggested Citation
Krizz Ian Dagodog, 2025.
"Burnout and Resilience among Academic Staff: Insights for Human Resource Management through Path Analysis,"
Journal of Business and Management Studies, Al-Kindi Center for Research and Development, vol. 7(3), pages 78-93, May.
Handle:
RePEc:alk:jbms00:v:7:y:2025:i:3:id:9386
DOI: 10.32996/jbms.2025.7.3.8
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