Perception and expression-based dual expert decision-making approach to information sciences with integrated quantum fuzzy modelling for renewable energy project selection

Abstract

Choosing the right projects in renewable energy investments is very significant. Due to this issue, necessary improvements to the performance indicators of these projects should be made. However, every improvement made also leads to an increase in costs. There is a need for a priority analysis to find the most important factors affecting the selection of the right renewable energy projects. Accordingly, this study aims to evaluate critical determinants of renewable energy project selection and provide effective investment strategies for this situation with a new fuzzy decision-making model. First, the indicators of renewable energy project selection are analyzed by perception and expression-based quantum Spherical fuzzy M−SWARA. The weights of these determinants are also calculated by DEMATEL to check the reliability of the results. Secondly, the priorities of renewable energy project selection are ranked by considering perception and expression-based quantum Spherical fuzzy ELECTRE. This calculation is also made by TOPSIS methodology to measure the reliability of the findings. The main contribution of this manuscript is that perception and expression-based evaluation can be carried out in the proposed model. In this process, the facial expressions and emotions of the decision makers are considered so that the hesitancy of these people while answering these questions can be included in the evaluation process. Another important novelty is that a new decision-making model (M−SWARA) is also proposed. This new technique provides an opportunity to consider causality relationship between the criteria to reach the most significant ones. The weighting results are the same for both M−SWARA and DEMATEL approaches. This situation gives information that the findings are coherent and valid. Market analysis has the greatest value in both perception-based (0.272) and expression-based (0.259) evaluations. Owing to this analysis, it is possible to clearly understand the supply–demand balance in the market. The ranking results indicate that technical adequacy is the most significant priority alternative for the selection of the appropriate renewable energy alternatives.