Multi-Attribute Large-Scale Group Decision Making Method And Application In Mobile Health Application Selection

With the advancement of science and technology and the development of social media,the decision making environment and problems have become more and more complex.Traditional group decision making involving a small number of decision makers(DMs)is no longer able to cope with many real-life decision making problems.Large-scale group decision making has attracted more and more attention.Therefore,this paper studies large-scale group decision making problem,which mainly includes the following aspects:Firstly,in view of interactions between importances of criteria,a multi-attribute large-scale group decision making method based on interactions among criteria is proposed.Based on analytic hierrchy process,quality function deployment and 2-additive measure,a method that considers interactions is proposed to determine the weights of criteria.Meanwhile,the k-means clustering algorithm is improved to divide the large-scale DMs into several subgroups.Moreover,the 2-additive generalized Shapley aggregation operator is applied to aggregate the evaluation information to rank and select alternatives.Secondly,in order to reduce the disagreement among DMs,a multi-attribute large-scale group decision making method based on consensus analysis is proposed.Based on distance measure,a consensus measure index is proposed to obtain the consensus levels of DMs,subgroups,and group.Furthermore,a feedback iterative consensus mechanism is constructed,which provides personalized consensus modification recommendations for DMs and subgroups based on the different group consensus levels and the willingness of subgroups.Thirdly,in order to fully consider the fairness of consensus reaching process,a multi-attribute large-scale group decision making method based on the Gini coefficient is proposed.Considering the importance of minority opinions,the minority opinions subgroup is identified and its weight is adjusted.At the same time,based on the Gini coefficient,the group fairness index and subgroup fairness index are defined.Moreover,a multi-layer consensus adjusted optimization model is constructed to adjust the opinions of DMs fairly and reasonably.Finally,three multi-attribute large-scale group decision making methods proposed in this paper are applied to m Health app selection,and are compared with existing decision making methods to show the feasibility and superiority of proposed methods.