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    A hybrid hesitant 2-Tuple IVSF decision making approach to analyze PERT-based critical paths of new service development process for renewable energy investment projects
    (IEEE-Institute of Electrical and Electronics Engineers Inc, 2021) Cheng, Fei; Lin, Minhua; Yüksel, Serhat; Dinçer, Hasan; Kalkavan, Hakan
    The purpose of this study is to evaluate PERT-based critical paths of new service development (NSD) process for renewable energy investment projects. In this context, a novel three-stage model has been proposed. In the first stage, 10 different steps in NSD process are weighted by considering 2-tuple hesitant interval-valued Spherical fuzzy IVSF DEMATEL approach. In the second stage, 26 different critical paths for NSD process are identified. Moreover, the third stage includes the ranking the renewable energy alternatives by path scenarios with 2-tuple hesitant IVSF TOPSIS. The findings demonstrate that idea screening and the formation of cross-functional team are the most significant criteria for the NSD process of renewable energy investments. Additionally, while considering all activities of NSD process, it is concluded that solar energy is the most appropriate renewable energy alternative. This result is also similar for considering the longest path by activity number, the longest path by duration and the shortest path by activity number. However, it is also determined that geothermal energy is the most ideal type of renewable energy to invest in while considering the shortest path by duration. Therefore, it is obvious that investors should primarily give importance to generate new products for solar energy projects. In this way, it can be easier for them to provide efficiency in their investments. On the other hand, if there is time constraint or a positive result is expected from the project in a short time, geothermal energy is the most suitable renewable energy type to invest.
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    Analysis of risk priorities for renewable energy investment projects using a hybrid IT2 hesitant fuzzy decision-making approach with alpha cuts
    (Pergamon-Elsevier Science Ltd, 2021) Zhou, Pengfei; Luo, Jie; Cheng, Fei; Yüksel, Serhat; Dinçer, Hasan
    The aim of this study is to identify significant risks for the renewable energy investment projects. In this regard, a novel hybrid multi-criteria decision-making (MCDM) model has been proposed based on hesitant linguistic terms and alpha level sets. This model has three different phases. Firstly, the dimensions and criteria are defined regarding the renewable energy investment risks. In the second part, the significance levels of these factors are calculated with the help of hesitant interval type-2 fuzzy (IT2F) DEMATEL-based ANP (DANP). Finally, the types of investors by the risk awareness entitled high, moderate, and low are ranked while using hesitant IT2F QUALIFLEX. In all analysis, alpha level sets are taken into consideration. The results demonstrate that organizational effectiveness and cost efficiency are the most prominent factors for renewable energy investment. On the other side, moderate risk should be taken in these projects. It is recommended that the departments within the company should be compatible with each other for the renewable energy investment projects to be more successful. For this purpose, necessary actions should be taken to improve communication between departments. Another important point is that cost control should be done effectively to contribute to the performance of the renewable energy investment projects.
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    Integer code series enhanced IT2 fuzzy decision support system with alpha cuts for the innovation adoption life cycle pattern recognition of renewable energy alternatives
    (IEEE-Institute of Electrical and Electronics Engineers Inc, 2021) Zhao, Yiqing; Cheng, Fei; Yüksel, Serhat; Dinçer, Hasan
    This study aims to evaluate the innovation adoption performance of the renewable energy alternatives. Within this context, a new model is created that consists of two different stages. Firstly, the decision combinations of innovation adoption life cycle patterns are identified by considering integer code series. On the other side, in the second stage, the innovation adoption life cycle performance of the renewable energy alternatives is ranked. In this framework, interval type-2 (IT2) fuzzy technique for order preference by similarity to ideal solution (TOPSIS) methodology is taken into consideration based on alpha cut levels. Moreover, a comparative evaluation is also conducted by considering IT2 fuzzy VIseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR). It is identified that the analysis results are quite coherent and reliable. The findings demonstrate that solar energy is the most appropriate renewable energy type to make innovation. Additionally, wind and geothermal energies are also other significant renewable energy types that have a great innovation potential. However, it is also concluded that biomass and hydroelectric energy have lower importance in comparison with the others. Another important point is that the ranking results are quite similar for different alpha cuts. This condition indicates that the analysis results are coherent and reliable. It is obvious that making investment to solar energy alternatives provides opportunity to adopt technologic innovation more easily. Therefore, it is recommended that investors should give priority to solar energy projects so that it can be more possible to increase the efficiency and the profitability of the investments.