Determining Objective Characteristics of MCDM Methods under Uncertainty: An Exploration Study with Financial Data

A major difficulty in comparing and even choosing MCDM methods is the uncertainty of information about the consistent and unique characteristics of the results produced. The objective information content of the final scores produced by MCDM methods and their relevance to real life can give us an important idea about them. In this study, first of all, seven MCDM methods with different methodologies were applied to evaluate companies' financial performance. Then, the obtained MCDM scores were compared using two different objective verification mechanisms. The first validation criterion is the relationship of a MCDM method to real-life rankings (share price). The second criterion is the standard deviation (SD) technique used to discover the objective information content of MCDM final scores. According to the results of this study, PROMETHEE and FUCA definitely outperform other methods in terms of both SD values and strength of correlation with reference real-life rankings. Also, FUCA is methodologically simpler than other methods. However, it produced nearly identical results as the sophisticated PROMETHEE method.

Automated summary

The uncertainty of information about the characteristics of MCDM results makes it difficult to compare and choose MCDM methods. This study applied seven different methods to evaluate companies' financial performance and compared the scores using two validation mechanisms. The results show that PROMETHEE and FUCA outperform other methods with stronger correlation to real-life rankings and lower SD values.