American Research Journal of Humanities and Social Sciences
Open Access

American Research Journal of Humanities and Social Sciences

ISSN (Online): 2378-7031

DOI: 10.46568/2378-7031

Review Article Vol. 10, Issue 3 2024 Open Access

From Training Rooms to Workplace Results: Assessing Capacity-Building Outcomes in Revenue Administration

Abstract

Effective training is essential for strengthening employee competence and improving institutional performance in revenue administration. When gaps in employees’ knowledge, practical skills, and work-related attitudes are not adequately addressed, the consequences may extend to the quality and efficiency of tax administration and revenue collection. This study examines the effectiveness of training delivered through the Ethiopian Ministry of Revenues Training Center, with particular attention to areas requiring improvement and possible measures for strengthening future programs. Training effectiveness was assessed through three dimensions: participant satisfaction, learning outcomes, and changes in workplace behavior. Data were gathered from employees who participated in training programs during 2021 using structured questionnaires. The data were analyzed through confirmatory factor analysis (CFA) and structural equation modeling (SEM). The findings indicate that limitations in training duration, the practical usefulness of training materials and modules, and the adequacy of the training environment may reduce the overall impact of the programs. The study recommends allocating sufficient time for training, developing materials that remain useful after participants return to their jobs, and ensuring that training facilities provide a clear, suitable, and supportive learning environment. The proposed Training Effectiveness (TREF) framework may also serve as a practical instrument for evaluating training initiatives across public and private sector organizations.

Keywords: Training Effectiveness; Employee Satisfaction; Learning Outcomes; Behavioral Change; Structural Equation Modeling; Confirmatory Factor Analysis.