Affiliations: [a]
School of Business Administration, Northeastern University, Shenyang, Liaoning, China
| [b]
School of Management, Northeastern University at Qinhuangdao, Qinhuangdao, Hebei, China
Abstract: Many businesses and organizations consider group decision making (GDM) to be an important decision-making strategy for dealing with complex decision-making difficulties. Although it is acknowledged that the difference in decision makers’ assessment scales has a significant impact on decision results, how to eliminate the difference in decision makers’ evaluation scales in the decision-making process has not been investigated further. In this research, the non-consensus of MAGDM is studied considering the difference of expert evaluation scale, and an improved two-stage multi-attribute group decision making method (MAGDM) is proposed. The example and comparative analysis of annual bonus allocation in engineering businesses validate the effectiveness and operability of this system. Simultaneously, the approach is improved to handle the MAGDM problem of tiny samples, and the method’s problem of inadequate information is illustrated by numerical examples. The research presented in this work gives a practicable approach and idea for investigating the eradication of decision-maker evaluation scale disparities in MAGDM, and it demonstrates the importance of decision-maker evaluation scale differences in theoretical research and practical management.
Keywords: Multi-attribute group decision making (MAGDM), expert evaluation scale, relative entropy, massive alternatives, normal distribution
