Bayesian Analysis on Predictors of Employee Satisfaction at Debre Markos University: A Cross Sectional Study Design

Background: Human resource is considered as the most important resource to affect job performance in organizations. Hence, the effectiveness and efficiency of any organization cannot be achieved without effective management of its human resource. The aim of this study was to assess the satisfaction level and identify the significant predictors of employee satisfaction at Debre Markos University staff. Methods: Institutional based cross-sectional study was conducted among 560 academic and administrative staff working in Debre Markos University. Data was collected using self-administered structured questionnaires. Bayesian logistic regression analysis was employed on Gibbs sampler algorithm. Results: The overall level of job satisfaction was 36% and most (67.1%) of the employee were male and about 22.7% of them were satisfied. About, 60.9% of academic staff, 23.9% were satisfied and 37% were dissatisfied. Moreover, about 33.6% of the total respondents were administrative staff and 10.4% of them were satisfied. Conclusion: The overall job satisfaction level was low and most of employees were male and master’s holders. Among the job satisfaction related factors, salary, relationship, work environment, work itself, responsibility, promotion significantly influences the job satisfaction of workers since the 95% credible interval of these variables does not include zero (at least one category).