Investment strategies for renewable energy technologies and harvesting systems in airport operations using spherical fuzzy MCDM models
Abstract This study presents a novel evaluation framework for prioritizing investment strategies in sustainable airport energy systems by integrating advanced fuzzy decision-making techniques with artificial intelligence-based expert weighting. Specifically, it employs a hybrid Spherical Fuzzy CRITI...
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| Language: | English |
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Nature Portfolio
2025-07-01
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| Series: | Scientific Reports |
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| Online Access: | https://doi.org/10.1038/s41598-025-08480-7 |
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| author | Filiz Mizrak Didem Rodoplu Şahin |
| author_facet | Filiz Mizrak Didem Rodoplu Şahin |
| author_sort | Filiz Mizrak |
| collection | DOAJ |
| description | Abstract This study presents a novel evaluation framework for prioritizing investment strategies in sustainable airport energy systems by integrating advanced fuzzy decision-making techniques with artificial intelligence-based expert weighting. Specifically, it employs a hybrid Spherical Fuzzy CRITIC–RATGOS model to rank renewable energy alternatives based on economic feasibility, environmental impact, technological efficiency, scalability, and operational reliability. To address limitations associated with equal expert weighting, a Principal Component Analysis-driven dimension reduction technique is applied to calibrate expert influence based on professional background and consistency of evaluation. The model is applied to a real-world case study at Istanbul Airport, demonstrating that AI-optimized energy management, solar microgrids, and waste-to-energy conversion are the most promising investment alternatives. In contrast, although technologies such as piezoelectric harvesting show future potential, their current limitations reduce their immediate feasibility. Sensitivity analysis affirms the robustness and stability of the results across various weighting configurations. The proposed framework contributes to both theory and practice by offering a scalable, transparent, and replicable decision-support tool for airport authorities, policymakers, and energy planners aiming to align infrastructure development with global sustainability and decarbonization goals. |
| format | Article |
| id | doaj-art-b7f4dc7457f74aaeacacba844ca89d34 |
| institution | Kabale University |
| issn | 2045-2322 |
| language | English |
| publishDate | 2025-07-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Reports |
| spelling | doaj-art-b7f4dc7457f74aaeacacba844ca89d342025-08-20T04:01:36ZengNature PortfolioScientific Reports2045-23222025-07-0115112310.1038/s41598-025-08480-7Investment strategies for renewable energy technologies and harvesting systems in airport operations using spherical fuzzy MCDM modelsFiliz Mizrak0Didem Rodoplu Şahin1Logistics Management, Beykoz UniversityDepartment of Aviation Management, Faculty of Aviation and Space Sciences, Kocaeli UniversityAbstract This study presents a novel evaluation framework for prioritizing investment strategies in sustainable airport energy systems by integrating advanced fuzzy decision-making techniques with artificial intelligence-based expert weighting. Specifically, it employs a hybrid Spherical Fuzzy CRITIC–RATGOS model to rank renewable energy alternatives based on economic feasibility, environmental impact, technological efficiency, scalability, and operational reliability. To address limitations associated with equal expert weighting, a Principal Component Analysis-driven dimension reduction technique is applied to calibrate expert influence based on professional background and consistency of evaluation. The model is applied to a real-world case study at Istanbul Airport, demonstrating that AI-optimized energy management, solar microgrids, and waste-to-energy conversion are the most promising investment alternatives. In contrast, although technologies such as piezoelectric harvesting show future potential, their current limitations reduce their immediate feasibility. Sensitivity analysis affirms the robustness and stability of the results across various weighting configurations. The proposed framework contributes to both theory and practice by offering a scalable, transparent, and replicable decision-support tool for airport authorities, policymakers, and energy planners aiming to align infrastructure development with global sustainability and decarbonization goals.https://doi.org/10.1038/s41598-025-08480-7Aviation managementSustainable airport energyInvestment strategiesSpherical fuzzy CRITICSpherical fuzzy RATGOSRenewable energy in aviation |
| spellingShingle | Filiz Mizrak Didem Rodoplu Şahin Investment strategies for renewable energy technologies and harvesting systems in airport operations using spherical fuzzy MCDM models Scientific Reports Aviation management Sustainable airport energy Investment strategies Spherical fuzzy CRITIC Spherical fuzzy RATGOS Renewable energy in aviation |
| title | Investment strategies for renewable energy technologies and harvesting systems in airport operations using spherical fuzzy MCDM models |
| title_full | Investment strategies for renewable energy technologies and harvesting systems in airport operations using spherical fuzzy MCDM models |
| title_fullStr | Investment strategies for renewable energy technologies and harvesting systems in airport operations using spherical fuzzy MCDM models |
| title_full_unstemmed | Investment strategies for renewable energy technologies and harvesting systems in airport operations using spherical fuzzy MCDM models |
| title_short | Investment strategies for renewable energy technologies and harvesting systems in airport operations using spherical fuzzy MCDM models |
| title_sort | investment strategies for renewable energy technologies and harvesting systems in airport operations using spherical fuzzy mcdm models |
| topic | Aviation management Sustainable airport energy Investment strategies Spherical fuzzy CRITIC Spherical fuzzy RATGOS Renewable energy in aviation |
| url | https://doi.org/10.1038/s41598-025-08480-7 |
| work_keys_str_mv | AT filizmizrak investmentstrategiesforrenewableenergytechnologiesandharvestingsystemsinairportoperationsusingsphericalfuzzymcdmmodels AT didemrodoplusahin investmentstrategiesforrenewableenergytechnologiesandharvestingsystemsinairportoperationsusingsphericalfuzzymcdmmodels |