Analysis of risk priorities for renewable energy investment projects using a hybrid IT2 hesitant fuzzy decision-making approach with alpha cuts

The aim of this study is to identify significant risks for the renewable energy investment projects. In this regard, a novel hybrid multi-criteria decision-making (MCDM) model has been proposed based on hesitant linguistic terms and alpha level sets. This model has three different phases. Firstly, the dimensions and criteria are defined regarding the renewable energy investment risks. In the second part, the significance levels of these factors are calculated with the help of hesitant interval type-2 fuzzy (IT2F) DEMATEL-based ANP (DANP). Finally, the types of investors by the risk awareness entitled high, moderate, and low are ranked while using hesitant IT2F QUALIFLEX. In all analysis, alpha level sets are taken into consideration. The results demonstrate that organizational effectiveness and cost efficiency are the most prominent factors for renewable energy investment. On the other side, moderate risk should be taken in these projects. It is recommended that the departments within the company should be compatible with each other for the renewable energy investment projects to be more successful. For this purpose, necessary actions should be taken to improve communication between departments. Another important point is that cost control should be done effectively to contribute to the performance of the renewable energy investment projects. (c) 2021 Elsevier Ltd. All rights reserved.

Automated summary

The study aims to identify significant risks in renewable energy investment projects and proposes a novel MCDM model. It highlights the importance of organizational effectiveness and cost efficiency, recommends moderate risk management, emphasizes the need for departmental collaboration, and stresses effective cost control for successful project performance.