Another Empirical Application of the Similarity Confirmation Method in Evaluating the MADM Methods for a Type-selection Decision Case before Bulk Purchase
Zheng-Yun Zhuang, Shu-Chin Chang · 2021
A 'similarity confirmation method' (SCM) was recently proposed for comparing the final results obtained using different multi-attribute decision-making (MADM) models. In a 2018 study entitled 'Rank-based comparative research flow benchmarking the effectiveness of AHP-GTMA on aiding decisions of shredder selection by reference to AHP-TOPSIS', the rank order vectors (ROVs) obtained using AHP-GTMA and AHP-TOPSIS are treated as two statistical samples. So, the supporting evidence that 'the two samples are not (drawn) from non-identical populations' was found to further justify the similarity observed between them using traditional measures (e.g., difference, absolute distance and Euclidean distance), and this 'intangible statistics measure' used the Mann-Whitney U test. This thoughtprovoking concept inspired the proposal of the systematic SCM in 2019 (see the paper: 'The effectiveness of IF-MADM for group decisions: Methods and an empirical assessment for the selection of a senior centre'). In the SCM, another common K-S (Kolmogorov-Smirnov) test in data analytics was applied to show further evidence that 'the two samples are not (drawn) from non-identical distributions'. This provided more evidence regarding the similarity present between the results. In addition, the SCM allows more methods to be compared in a pair-wise manner. This property was applied to support the efficacy of the intuitionistic-fuzzy (IF-)MADM method because of the similarities rendered in the results between IF-MADM and other widely applied 'credible' methods (i.e., AHP and TOPSIS).