MAXC2: An Enhanced Iteration of the MAXC Method for Criterion Weight Determination

Do Duc Trung; Branislav Dudic; Bui Thi Thu Trang; Aleksandar Ašonja

doi:10.31181/dma412026166

Authors

Do Duc Trung Hanoi University of Industry, Hanoi, Vietnam https://orcid.org/0000-0002-3190-1026
Branislav Dudic Comenius University Bratislava, Faculty of Management, Bratislava, Slovakia https://orcid.org/0000-0002-4647-6026
Bui Thi Thu Trang Hanoi University of Industry, Hanoi, Vietnam https://orcid.org/0000-0002-5483-9966
Aleksandar Ašonja Faculty of Economics and Engineering Management, University Business Academy, Novi Sad, Serbia https://orcid.org/0000-0001-6667-1024

DOI:

https://doi.org/10.31181/dma412026166

Keywords:

Innovation, Weights, Standard deviation, SD method, LOPCOW method, LOPCOW-SD method

Abstract

Determining weights for criteria is a crucial task in multi-criteria decision-making (MCDM) problems. MAXC (MAXimum of Criterion) is an objective weighting method that calculates criterion weights based on the definition of maximum criterion values from the initial matrix and is known as a simple method in the calculation process. However, the data normalization method used in this method cannot be applied if the total value of a certain criterion across all alternatives equals zero. This study improves the MAXC method by creating a new version named MAXC2. MAXC2 improves upon MAXC by changing the normalization formula used in the MAXC method. When both methods are applicable, the maximum difference in the weights calculated by these two methods is only about 4.76%. When only MAXC2 can be used, the calculation of criterion weights using the MAXC2 method ensures high stability in the ranking of alternatives, with the minimum average Spearman correlation coefficient between ranking methods being 0.8667. MAXC2 overcomes the limitations of the MAXC method and can be considered a highly reliable method.

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