Innovative solution suggestions for financing electric vehicle charging infrastructure investments with a novel artificial intelligence-based fuzzy decision-making modelling

被引:2
|
作者
Kou, Gang [1 ]
Eti, Serkan [2 ]
Yuksel, Serhat [3 ,4 ]
Dincer, Hasan [3 ,4 ]
Ergun, Edanur [3 ]
Gokalp, Yasar [5 ]
机构
[1] Southwestern Univ Finance & Econ, Fac Business Adm, Sch Business Adm, Chengdu 611130, Peoples R China
[2] Istanbul Medipol Univ, IMU Vocat Sch, Istanbul, Turkiye
[3] Istanbul Medipol Univ, Sch Business, Istanbul, Turkiye
[4] Khazar Univ, Dept Econ & Management, AZ-1141 Baku, Azerbaijan
[5] Istanbul Medipol Univ, Sch Hlth, Istanbul, Turkiye
关键词
Electric vehicles; Charging; Infrastructure investments; Artificial intelligence; ENERGY TRANSITION; SYSTEM; PROJECTS;
D O I
10.1007/s10462-024-11012-w
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
The right methods for effective financing of electric vehicle charging infrastructure investments should be identified. However, in the literature, there is no consensus on which funding source would be right for these projects. There is a need for a new study to recommend the most appropriate financing strategy for these projects. Accordingly, the purpose of this study is to identify innovative solutions for financing electric vehicle charging infrastructure investments. A novel fuzzy decision-making model is introduced to reach this objective. Firstly, the weights of experts are calculated using dimension reduction. Secondly, Spherical fuzzy decision matrix is obtained. Thirdly, the criteria in charging infrastructure for electric vehicles are weighted using Spherical fuzzy criteria importance through intercriteria correlation (CRITIC). Fourthly, innovative solutions for financing electric vehicles charging infrastructure are ranked via Spherical fuzzy ranking technique by geometric mean of similarity ratio to optimal solution (RATGOS). The main contribution of this study is that effective strategies can be identified for financing electric vehicle charging infrastructure investments by establishing a novel decision-making model. Most of the existing models in the literature could not consider the weights of the experts. This condition is criticized by different scholar because these experts can have different qualifications. To satisfy this problem, in this study, dimension reduction algorithm with machine learning is taken into consideration to compute thee weights of the experts. The findings demonstrate that the most effective criterion in the innovative financial solution for the charging infrastructure of electric vehicles is determined as "potential income". According to the ranking results, it is also defined that the most sustainable solution among the innovative strategies for financing the charging infrastructure of electric vehicles is "blockchain technology".
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收藏
页数:32
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