[Hongming Zheng] School of Economics and Management, Southwest Jiaotong University, Chengdu 610031, Sichuan Province, China;[Liqi Zhu] Center for Magnetic Resonance Imaging Research, Institute of Psychology, Chinese Academy of Sciences, Beijing 100101, China
Previous studies have demonstrated that reactions to unfair offers in the ultimatum game are correlated with negative emotion. However, little is known about the difference in neural activity between a proposer's decision-making in the ultimatum game compared with the dictator game. The present functional magnetic resonance imaging study revealed that proposing fair offers in the dictator game elicited greater activation in the right supramarginal gyrus, right medial frontal gyrus and left anterior cingulate cortex compared with proposing fair offers in the ultimatum game in 23 Chinese undergraduate and graduate students from Beijing Normal University in China. However, greater activation was found in the right superior temporal gyrus and left cingulate gyrus for the reverse contrast. The results indicate that proposing fair offers in the dictator game is more strongly associated with cognitive control and conflicting information processing compared with proposing fair offers in the ultimatum game.
To solve the uncertain multi-attribute group decision-making of unknown attribute weights, three optimal models are built to decide the corresponding ideal solution weights, standard deviation weights and mean deviation weights. The comprehensive attribute weights are gotten through the product of the above three kinds of weights. And each decision maker's weighted decision matrices are also received by using the integrated attribute weights. The closeness degrees are also gotten by use of technique for order preference by similarity to ideal solution (TOPSIS) through dealing with the weighted decision matrices. At the same time the group decision matrix and weighted group decision matrix are gotten by using each decision-maker's closeness degree to every project. Then the vertical TOPSIS method is used to calculate the closeness degree of each project. So these projects can be ranked according to their values of the closeness degree. The process of the method is also given step by step. Finally, a numerical example demonstrates the feasibility and effectiveness of the approach.