Balanced-scorecard-based evaluation of knowledge-oriented competencies of distributed energy investments

Abstract

Since the global warming problem threatens the whole world, it is understood that countries should develop energy policies that will increase their sustainable and clean energy investments. Compared to other alternatives, the high cost of renewable energy projects is an essential obstacle in this process. Therefore, priority should be given to developing distributed energy projects to minimize this problem. The scope of the present paper is to identify the most critical items that affect the performance of distributed energy projects to have knowledge-oriented competencies. In this way, companies can focus on more critical items to provide efficiency for distributed energy projects. As a result, clean energy usage is improved, and the global warming problem is handled more successfully. A novel decision-making model is generated to examine the competencies of the knowledge economy based on collaborative filtering and bipolar q-rung orthopair fuzzy sets (q-ROFSs) with the golden ratio. The analysis concludes that learning and growth are the most critical balanced scorecard perspectives. Moreover, it was also determined that information and communication technology is the most critical competency of the knowledge economy. Therefore, it would be appropriate for investors who plan to invest in distributed energy projects to form a research and development team. Hence, new technologies will be followed instantly. In this way, companies will be able to gain a cost advantage. In this context, improving distributed energy projects is important to increase efficiency in clean energy investments.