Designing a Learning-Oriented Performance Evaluation Model in the Power Industry

Abstract

Performance evaluation in infrastructure industries is not merely a control instrument for measuring past results; rather, it plays a decisive role in organizational learning, continuous improvement, and the enhancement of accountability. However, empirical evidence indicates that performance evaluation systems in Iran’s power industry are predominantly grounded in traditional, static, and result-oriented approaches and pay limited attention to organizational learning capacities. The present study was conducted with the aim of designing an indigenous model for performance evaluation based on the learning organization approach in Iran’s power industry. In terms of purpose, this research is applied, and in terms of methodology, it is qualitative and was carried out using the grounded theory strategy. Data were collected through semi-structured interviews with experts and managers in the power industry and were analyzed through open, axial, and selective coding. The findings led to the identification of the core category of “learning-oriented performance management” and the articulation of its causal, contextual, and intervening conditions, as well as its strategies and consequences. The results indicate that accountability pressures, productivity requirements, and performance transparency, alongside structural and cultural constraints, play a key role in shaping learning-oriented performance evaluation. The proposed model can be used as a practical framework for reforming and enhancing performance evaluation systems in power industry organizations.