From risks to rewards: A comprehensive guide to sustainable investment decisions in renewable energy using a hybrid facial expression-based fuzzy decision-making approach

Kou G., Pamucar D., DİNÇER H., YÜKSEL S.

Applied Soft Computing, vol.142, 2023 (SCI-Expanded) identifier

  • Publication Type: Article / Article
  • Volume: 142
  • Publication Date: 2023
  • Doi Number: 10.1016/j.asoc.2023.110365
  • Journal Name: Applied Soft Computing
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Applied Science & Technology Source, Compendex, Computer & Applied Sciences, INSPEC
  • Keywords: Neuro decision-making, Renewable energy, Sustainable investment decisions
  • Istanbul Medipol University Affiliated: Yes


There are some risks in renewable energy investments, such as legal, technology and financial issues. Hence, appropriate actions should be taken to minimize these risks. However, each of the measures to be taken for the management of risks creates new costs for businesses. Therefore, to ensure the financial sustainability of the projects, measures for the most important risks should be taken at the first stage. Because of this situation, it is vital to make a priority analysis for the risks faced by renewable energy projects so that it can be possible to increase the effectiveness of risk management. Accordingly, in this study, it is aimed to examine the risks and rewards regarding sustainable investment decisions for renewable energy projects. In this scope, a novel model is generated by integrating different techniques. In this process, the evaluations of six different experts are taken into consideration. First, missing evaluations for the sustainable investment decisions in renewable energy are estimated with neuro decision-making and collaborative filtering. Secondly, the weights of the risk factors of sustainable energy investments are computed with neuro quantum spherical fuzzy (QNSLF) DEMATEL with golden cut. Thirdly, reward alternatives for sustainable decision making are analyzed with Neuro QNSLF TOPSIS with golden cut. This study contributes to literature by determining the most important risks for renewable energy projects by an original decision-making model. Another important novelty of this study is that a new technique called neuro decision-making has also been developed. In this technique, the facial expressions of the experts who evaluate are taken into consideration. It is defined that technological changes have the greatest significance. Additionally, governmental incentives are found as the most essential reward to improve sustainable investments in renewable energy. Thus, for the effective management of these risks, appropriate actions should be taken. It is also obvious that the competitiveness of companies that fall behind this new technology will decrease. In this context, these enterprises need to take the necessary measures to manage the technology risk to be sustainable in the long term.