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dc.contributor.authorKou, Gang
dc.contributor.authorPamucar, Dragan
dc.contributor.authorDinçer, Hasan
dc.contributor.authorYüksel, Serhat
dc.date.accessioned2024-07-05T06:15:15Z
dc.date.available2024-07-05T06:15:15Z
dc.date.issued2024en_US
dc.identifier.citationKou, G., Pamucar, D., Dinçer, H. ve Yüksel, S. (2024). Quantum fuzzy decision-making for analyzing the service progress life cycle of renewable energy innovation investments. Applied Soft Computing, 163. http://dx.doi.org/10.1016/j.asoc.2024.111884en_US
dc.identifier.issn1568-4946
dc.identifier.urihttp://dx.doi.org/10.1016/j.asoc.2024.111884
dc.identifier.urihttps://hdl.handle.net/20.500.12511/12696
dc.description.abstractInnovative and effective solutions can be produced by using advanced technologies to increase renewable energy innovation investments. However, many actions taken to increase these investments may cause the costs of enterprises to reach an unmanageable level. As a result, a priority analysis is needed to identify the most critical issues, but in literature, there are limited studies in the literature regarding this issue. Accordingly, the purpose of this study is to evaluate the service progress life cycle of renewable energy innovation investments. A novel model is presented in this process while integrating different approaches. First, the service progress life cycle of renewable innovation investments is weighted. In this scope, two-generation technology S-curve and facial action coding system-based Quantum Spherical fuzzy M-SWARA are considered. Secondly, the renewable innovation investment alternatives are ranked. In this framework, the integer patterns and facial action coding system-based Quantum Spherical fuzzy TOPSIS are taken into consideration. Additionally, these investment alternatives are also ranked by using VIKOR technique to test the validity of the proposed model results. Moreover, a sensitivity analysis is conducted by considering 8 different cases so that coherency of the results can be tested. The main contribution of this manuscript is the consideration of the FACS system to increase both the originality and effectiveness of the proposed model and the development of new technique named M-SWARA. Additionally, conducting a priority evaluation helps to identify the efficient investment strategies to increase renewable energy innovation. It is defined that the same findings can be achieved by both TOPSIS and VIKOR techniques. Furthermore, sensitivity analysis also indicates the same rankings as well. It is understood that the proposed model provides coherent and reliable findings. The findings denote that maturity is the most critical stage of the service progress life cycle of the renewable energy investments. Moreover, advanced technologies are found as the best alternative of the renewable innovation investments for the service progress life cycle. Hence, it is recommended that R&D activities should be prioritized for the provision of advanced technologies in the renewable energy sector. For this purpose, research centers, universities, private sector companies and government institutions can work for the development of innovative and advanced technologies.en_US
dc.language.isoengen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectM-SWARA, TOPSISen_US
dc.subjectNew Service Developmenten_US
dc.subjectQuantum Logicen_US
dc.subjectRenewable Investmentsen_US
dc.titleQuantum fuzzy decision-making for analyzing the service progress life cycle of renewable energy innovation investmentsen_US
dc.typearticleen_US
dc.relation.ispartofApplied Soft Computingen_US
dc.departmentİstanbul Medipol Üniversitesi, İşletme ve Yönetim Bilimleri Fakültesi, Uluslararası Ticaret ve Finansman Bölümüen_US
dc.authorid0000-0002-8072-031Xen_US
dc.authorid0000-0002-9858-1266en_US
dc.identifier.volume163en_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.identifier.doi10.1016/j.asoc.2024.111884en_US
dc.institutionauthorDinçer, Hasan
dc.institutionauthorYüksel, Serhat
dc.identifier.scopus2-s2.0-85196812187en_US
dc.identifier.scopusqualityQ1en_US


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