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  

作　　者：Qilong Wan Xiaodong Miao Chenguang Wang Hasan Dinçer Serhat Yüksel 

机构地区：[1]School of Economics and Management,Huanghuai University,Zhumadian 463000,China [2]School of Economics,University of Chinese Academy of Social Sciences,Beijing 102488,China [3]School of Business,Lingnan University,Hong Kong 999077,China [4]The School of Business,İstanbul Medipol University,34817 Beykoz,Istanbul,Turkey

出　　处：《Financial Innovation》2023年第1期319-343,共25页金融创新（英文）

基　　金：was the Key Scientific Research Project of Colleges and Universities in Henan Province“Research on the key role of Investment in the Optimization and upgrading of Industrial structure in Henan Province”(22A790014);National scientific research project cultivation fund project"Research on the Endogenous Mechanism,Performance Evaluation and Optimization Path of Science and Technology Finance Boosting China’s High quality Economic Development"(XKPY-2022030).

摘　　要：In 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 invest-ment.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 stra-tegic priorities of fintech lending for clean energy projects.The most important contri-butions 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 con-structing 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 find-ings 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 risk

关 键 词：Fintech lending Risk management Clean energy Fuzzy logic Decisionmaking methods 

分 类 号：F832[经济管理—金融学]