Quantum fuzzy decision-making for analyzing the service progress life cycle of renewable energy innovation investments

dc.authorid0000-0002-8072-031X
dc.authorid0000-0002-9858-1266
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.issued2024
dc.departmentİstanbul Medipol Üniversitesi, İşletme ve Yönetim Bilimleri Fakültesi, Uluslararası Ticaret ve Finansman Bölümü
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.
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.2024.111884
dc.identifier.doi10.1016/j.asoc.2024.111884
dc.identifier.issn1568-4946
dc.identifier.issn1872-9681
dc.identifier.scopus2-s2.0-85196812187
dc.identifier.scopusqualityQ1
dc.identifier.urihttp://dx.doi.org/10.1016/j.asoc.2024.111884
dc.identifier.urihttps://hdl.handle.net/20.500.12511/12696
dc.identifier.volume163
dc.identifier.wos001266783800001en_US
dc.identifier.wosqualityQ1
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.institutionauthorDinçer, Hasan
dc.institutionauthorYüksel, Serhat
dc.language.isoen
dc.relation.ispartofApplied Soft Computingen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/openAccess
dc.subjectM-SWARA, TOPSIS
dc.subjectNew Service Development
dc.subjectQuantum Logic
dc.subjectRenewable Investments
dc.titleQuantum fuzzy decision-making for analyzing the service progress life cycle of renewable energy innovation investments
dc.typeArticle

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