Using quantum spherical fuzzy decision support system as a novel sustainability index approach for analyzing industries listed in the stock exchange

This study aims to identify critical factors of the sustainability index (SI) and evaluate the industries listed in the stock exchange based on the performance of this index. For this purpose, a new fuzzy decision-making model has been created. Firstly, 12 different criteria for the SI are weighted by decision using trial and evaluation laboratory (DEMATEL) methodology based on quantum spherical fuzzy sets (QFS) with golden cut. Secondly, SI performances of the 10 industry alternatives are ranked by extended technique for order of preference: according to similarity through an ideal solution (TOPSIS) with QFS. The main novelty of this study is to identify significant sustainability criteria for the companies to join this index with an original fuzzy decision-making methodology. For this purpose, the analysis results help the companies to act without incurring extreme costs. It is determined that the usage of renewable energy has a significant impact on all other criteria, and while using clean energy, the companies get a chance to improve other criteria of SI. Additionally, based on the weighting results, the use of renewable energy is the most critical criterion to be included in SI. Similarly, recovery of the resources also has a significant contribution. Finally, the ranking results indicate that communication and IT is the most successful industry for SI. Hence, it would be appropriate for businesses to attach importance to the use of renewable energy. In this way, the carbon emission problem would be minimized, and the image of businesses will rise in the eyes of both consumers and investors. In this framework, companies can join microgrid energy management systems to handle high-cost problems of renewable energy investment projects. Owing to microgrid energy applications, the costs of using renewable energy can be shared with other companies, and since this situation can reduce the cost per unit, it will be possible to increase the use of renewable energy.