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A hybrid decision support system with golden cut and bipolar q-ROFSs for evaluating the risk-based strategic priorities of fintech lending for clean energy projects

dc.authorid0000-0002-8072-031X
dc.authorid0000-0002-9858-1266
dc.contributor.authorWan, Qilong
dc.contributor.authorMiao, Xiaodong
dc.contributor.authorWang, Chenguang
dc.contributor.authorDinçer, Hasan
dc.contributor.authorYüksel, Serhat
dc.date.accessioned2023-01-13T06:42:49Z
dc.date.available2023-01-13T06:42:49Z
dc.date.issued2023
dc.departmentİstanbul Medipol Üniversitesi, İşletme ve Yönetim Bilimleri Fakültesi, Uluslararası Ticaret ve Finansman Bölümü
dc.description.abstractIn the last decade, the risk evaluation and the investment decision are among the most prominent issues of efficient project management. Especially, the innovative financial sources could have some specific risk appetite due to the increasing return of investment. Hence, it is important to uncover the risk factors of fintech investments and investigate the possible impacts with an integrated approach to the strategic priorities of fintech lending. Accordingly, this study aims to analyze a unique risk set and the strategic priorities of fintech lending for clean energy projects. The most important contributions to the literature can be listed as to construct an impact-direction map of risk-based strategic priorities for fintech lending in clean energy projects and to measure the possible influences by using a hybrid decision making system with golden cut and bipolar q-rung orthopair fuzzy sets. The extension of multi stepwise weight assessment ratio analysis (M-SWARA) is applied for weighting the risk factors of fintech lending. The extension of elimination and choice translating reality (ELECTRE) is employed for constructing and ranking the risk-based strategic priorities for clean energy projects. In this process, data is obtained with the evaluation of three different decision makers. The main superiority of the proposed model by comparing with the previous models in the literature is that significant improvements are made to the classical SWARA method so that a new technique is created with the name of M-SWARA. Hence, the causality analysis between the criteria can also be performed in this proposed model. The findings demonstrate that security is the most critical risk factor for fintech lending system. Moreover, volume is found as the most critical risk-based strategy for fintech lending. In this context, fintech companies need to take some precautions to effectively manage the security risk. For this purpose, the main risks to information technologies need to be clearly identified. Next, control steps should be put for these risks to be managed properly. Furthermore, it has been determined that the most appropriate strategy to increase the success of the fintech lending system is to increase the number of financiers integrated into the system. Within this framework, the platform should be secure and profitable to persuade financiers.
dc.description.sponsorshipOptimization and upgrading of Industrial structure in Henan Province ; Key Scientific Research Project of Colleges and Universities in Henan Provinceen_US
dc.identifier.citationWan, Q., Miao, X., Wang, C., Dinçer, H. ve Yüksel, S. (2023). A hybrid decision support system with golden cut and bipolar q-ROFSs for evaluating the risk-based strategic priorities of fintech lending for clean energy projects. Financial Innovation, 9(1). https://dx.doi.org/10.1186/s40854-022-00406-w
dc.identifier.doi10.1186/s40854-022-00406-w
dc.identifier.issn2199-4730
dc.identifier.issue1
dc.identifier.pmid36643686
dc.identifier.scopus2-s2.0-85145704349
dc.identifier.scopusqualityQ1
dc.identifier.urihttps://dx.doi.org/10.1186/s40854-022-00406-w
dc.identifier.urihttps://hdl.handle.net/20.500.12511/10299
dc.identifier.volume9
dc.identifier.wos000910116400001en_US
dc.identifier.wosqualityQ1
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.indekslendigikaynakPubMed
dc.institutionauthorDinçer, Hasan
dc.institutionauthorYüksel, Serhat
dc.language.isoen
dc.publisherSpringer Science and Business Media Deutschland GmbH
dc.relation.ispartofFinancial Innovationen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsAttribution 4.0 International*
dc.rightsinfo:eu-repo/semantics/openAccess
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/*
dc.subjectFintech Lending
dc.subjectRisk Management
dc.subjectClean Energy
dc.subjectFuzzy Logic
dc.subjectDecisionmaking Methods
dc.titleA hybrid decision support system with golden cut and bipolar q-ROFSs for evaluating the risk-based strategic priorities of fintech lending for clean energy projects
dc.typeArticle

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