Hesitant linguistic term sets-based hybrid analysis for renewable energy investments
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CitationWang, S., Liu, Q., Yüksel, S. ve Dinçer, H. (2019). Hesitant linguistic term sets-based hybrid analysis for renewable energy investments. IEEE Access, 7, 114223-114235. http://doi.org/10.1109/ACCESS.2019.2935427
The aim of this study is to evaluate different renewable energy investments alternatives. Within this framework, six different criteria are chosen to represent financial and non-financial dimensions. Additionally, five renewable energy investment alternatives (biomass, hydropower, geothermal, wind and solar) are selected. Fuzzy AHP and fuzzy DEMATEL methods are considered to weight these criteria whereas alternatives are ranked by using fuzzy TOPSIS and fuzzy VIKOR approaches. The findings show that fuzzy AHP and fuzzy DEMATEL methods also give coherent results. It is concluded that environmental effects and earnings are the most significant criteria. Moreover, wind and solar are the most attractive renewable energy investment alternatives. Therefore, it is recommended that governmental incentives should be widely used for effective location selection of both energy alternatives. This situation could be also attractive for foreign investors in renewable energy market. In addition, large-scale investments should be handled by merger and acquisition to increase overall performance. Hence, it can be possible to raise earnings, improve capital adequacy and enhance organizational capacity with the extensive investments. Furthermore, easy access to the sources and good contract conditions should also be provided for this purpose so that it can be much easier to attract the attention of these investors. Also, customer expectations should be understood effectively with a detailed analysis. With the help of this issue, appropriate products can be presented according to customer needs and it significantly contributes to the success in renewable energy investment.