Performance-Driven Climate, Overtime and Burnout in Digital Banking
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Date
2026-06-01
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Addis Ababa University
Abstract
Employee burnout is an increasing issue affecting the growing banking industry within sub-Saharan Africa. However, there is very little literature on how high-performance work environments contribute to burnout. Using the Job Demands-Resources framework, this research examines the pathways that connect a high-performance climate and employee burnout, and introduces power distance as a culture-based moderator. Data was collected via a cross-sectional quantitative survey with 217 full-time digital banking department employees at the Commercial Bank of Ethiopia (CBE), selected using a probabilistic simple random sampling methodology. The data was analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM). The study findings indicate that there is a statistically significant direct relationship between a high-performance climate and employee burnout. There was a statistically significant relationship between overtime norms and employee burnout; overtime norms are a significant predictor of employee burnout which points to compliance behaviors as a key job demand. Additionally, power distance was identified as a conditional moderator of the relationship between high-performance climate and overtime, whereby employees with high levels of power distance reached a ceiling level of overtime due to organizationally sanctioned obedience. Additionally, in-role performance and work engagement did not buffer or reduce employee burnout within the context of this research study. Lastly, a post-hoc analysis revealed that power distance indirectly influenced employee burnout through overtime norms. The study provides a vital empirical diagnosis of the Ethiopian financial sector, showing that cultural hierarchy functions as a structural demand and establishing a clear boundary for western organizational framework.
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Employee burnout, performance-driven climate, overtime norms, power distance, job-demand resource model, PLS-SEM, Ethiopian banking