Methods For Probabilistic Linguistic Mulitple Attribute Group Decision Making:Application To The Selection Of Financial Technologies

“No technology,no finance” has become the consensus of the banking industry.With the continuous development of science and technology,it is urgent to promote financial innovation with science and technology and help the banking industry achieve transformation and development.The banking industry are faced with the pains of slow cross-border transfer,slow service approval,weak risk management,high customer service costs and single product solidification.Thereby,if banking industry want to survive in the increasingly fierce competition,banks must subvert the pain point to adapt to the economic and financial development in the future and comprehensively promote industry transformation.“Finance Technology”(Fintech)has become a new gene for the transformation of the banking industry.One of the effective ways to transform the banking industry is to cooperate with financial technology companies.However,among the many good or bad financial technology companies,how to choose the most suitable and best financial technology company and achieve strategic cooperation with them to achieve a win-win situation,which is a multi-attribute decision-making problem.The basis of the multi-attribute decision-making problem is the evaluation information of the evaluated object.Due to the inherent complexity of the objective things and the hesitation of human beings,the decision-makers often cannot only quantitatively describe the evaluation information of the evaluated objects.However,decision makers always tend to express evaluation information in natural language.Probabilistic linguistic term set(PLTS)can comprehensively summarize the decision maker's preference information,hesitation degree and ambiguity of things.In order to make fair and effective decisions,multiple decision makers are involved in the decision process.Therefore,it is of great research significance to study probabilistic linguistic the multi-attribute group decision making(MAGDM)problem and apply it to the selection of financial technology companies.The PLTS is a useful tool to express decision makers'(DMs')evaluations in the technology company selection.This paper proposes two probabilistic linguistic MAGDM models for solving multi-attribute group decision problems and applies them to the selection of financial technology companies.Firstly,the possibility degree of PLTSs are defined.Then a possibility degree algorithm is designed for ranking PLTSs;Secondly,a Euclidean distance measure and correlation coefficient between PLTSs are presented and extended to probabilistic linguistic matrices.Then based on Archimedean t-norm and s-norm,some operational laws and aggregating operators for PLTSs are defined,including a generalized probabilistic linguistic Hamacher weighted averaging(GPLHWA)operator,a generalized probabilistic linguistic Hamacher ordered weighted averaging(GPLHOWA)operator,a generalized probabilistic linguistic Hamacher weighted geometric(GPLHGA)operator and a generalized probabilistic linguistic Hamacher ordered weighted geometric(GPLHOGA)operator are developed,and the basic properties of the operators are discussed in detail.Based on the above basic theoretical research,a multi-attribute group decision making model based on probabilistic linguistic degree and a multi-attribute group decision making model based on probabilistic linguistic correlation coefficients are proposed.In Model 1,the attribute weights is determined based probabilistic linguistic degree and DMs' weights is determined based probabilistic linguistic matrix distance measure,the ranking order of alternatives is generated by improving ELECTRE.In Model 2,the attribute weights is determined based probabilistic linguistic correlation coefficient measure and DMs' weights is determined based probabilistic linguistic matrix correlation coefficient measure,the ranking order of alternatives is generated by improving PROMETHEE.Finally,a Fintech example is analyzed to show the effectiveness of the proposed method.Furthermore,the sensitivity analysis and comparative analyses are conducted to illustrate its rationality and advantages.