A new hybrid decision framework for prioritizing funding allocation to Iran's energy sector

With the historic nuclear agreement now in effect, Iran's energy sector expects a new transformation to spark back into life. The government seeks to recover the years of backwardness by capital injections and attract foreign cash into the sector long starved of investment. In this respect, an appropriate and convenient resource allocation scheme in a long-term perspective is vital to keep Iran's position as a major energy supplier. This study develops a new hybrid multi-criteria decision-making model through integrating fuzzy Analytical hierarchy process with the Cumulative belief degree model to effectively evaluate energy alternatives for investment in Iran. Fuzzy analytical hierarchy process adds more benefits to the integrated model by providing the fuzzy pairwise comparison to identify weights of criteria while the Cumulative belief degree approach offers higher quality results of overall experts' opinions since it can deal with the missing values. STEEP analysis is also used to ensure capturing influential factors in five categories: social, technological, economic, environmental, and political. As a real application, the proposed methodology is applied to prioritize major energy resources for investment in Iran. Results indicate that natural gas is the ideal option for receiving the highest funding priority followed by solar and oil.