Department of Industrial Management, Ra.C., Islamic Azad University, Rasht, Iran
Abstract: (36 Views)
Governance sustainability plays a critical role in improving the performance of electricity management systems, particularly in countries facing structural energy challenges. This study develops a two-level Adaptive Neuro-Fuzzy Inference System (ANFIS) framework to assess the sustainability of governance in Iran’s electricity management system. The proposed model is structured around six governance sub-dimensions: energy policy, governance quality, institutional stability, energy security and diplomacy, crisis and demand management, and transparency and corruption. A structured questionnaire was designed based on the identified governance indicators and completed by 137 qualified energy experts. The collected data were divided into training, testing, and validation datasets, and Gaussian membership functions were applied within the ANFIS structure. The results indicate that energy policy has the highest contribution to governance sustainability (0.231), followed by crisis and demand management (0.196), energy security and diplomacy (0.182), institutional stability (0.164), governance quality (0.135), and transparency and corruption (0.092). At the indicator level, pricing policies, demand management, subsidy policies, political stability, energy policies, crisis preparedness, and economic stability obtained the highest relative weights. These findings suggest that improving governance sustainability in Iran’s electricity sector requires greater attention to pricing reform, subsidy adjustment, demand-side management, crisis preparedness, and institutional stability.
Javid M, Homayounfar M, Fadaei M. Governance-based sustainability assessment of Iran’s electricity energy management system: A two-level ANFIS approach. International Journal of Applied Operational Research 2026; 14 (4) :1-19 URL: http://ijorlu.lahijan.iau.ir/article-1-737-en.html