Akademik Veri Yönetim Sistemi
International Journal of Transport Economics, cilt.52, sa.3, ss.237-266, 2025 (SSCI, Scopus)
The risks must be effectively controlled for successful renewable energy investments. However, there are uncertainties in the literature on this issue. These deficiencies reduce the reliability of the audit processes. In this study, it is aimed to determine the most important factors to increase the effectiveness of risk-based audit processes in renewable energy projects to eliminate this deficiency. In this model, expert opinions are evaluated with the clustering algorithm, criteria are weighted with the simple weight calculation (SIWEC) technique and investment alternatives are ranked with the alternative ranking based on logical optimization network (ARLON) method. In addition, Pythagorean fuzzy sets are used to manage uncertainties more effectively. This study contributes to the literature by developing a new decision support model to determine key indicators in the risk-based auditing processes of renewable energy projects. The model developed in the study offers a more sensitive and holistic assessment compared to classical methods. By clustering expert groups, the effect of extreme opinions is reduced, and more objective results are obtained. The findings show that the most critical criteria in increasing the success of risk-based audits are the control of grid integration stability and the detection of potential weaknesses in regulatory frameworks.