Automatic Substitution of Prioritization Methods Preserving Information Integrity

Companies face multi-criteria problems every day, such as prioritizing projects, investments, and suppliers. In this respect, the literature offers countless methods, some of which provide partial and flawed solutions. Therefore, identifying and replacing a flawed method with a more efficient one is fundamental. However, this replacement is not straightforward because each method has a different evaluation structure. More specifically, in this study, the Mapping method uses scoring evaluations, whereas the Analytic Hierarchy Process (AHP) uses pairwise comparisons. In other words, scoring evaluations are incompatible with pairwise comparison evaluations. This incompatibility prevents one method from being replaced by another without loss of information. This is a significant gap because the re-evaluation process is expensive, time-consuming, and may even be impossible if the experts are no longer available. This study presents a novel approach to automatically substitute prioritization methods without loss of information. The approach was applied to a real-world case involving forty-four Brazilian companies. The specific case shows the prioritization of four projects evaluated by scores, combined with three new projects evaluated by pairwise comparisons. The application of the approach offers specific and general contributions. For example, substituting prioritization methods without loss of information, such as the Mapping method with AHP. Flexibility in choosing the evaluation method that offers greater psychological comfort to the experts. Obtaining transitive pairwise comparison matrices independently of the number of new projects evaluated.

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Publication Details

Journal
Administrative Sciences
Published
2025-11-13
DOI
https://doi.org/10.3390/admsci15110442
Primary Topic
Multi-Criteria Decision Making
Type
article
Field-Weighted Citation Impact
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article

Automatic Substitution of Prioritization Methods Preserving Information Integrity

Iara Sibele Silva, Matheus Pereira Libório, Renato Dourado Maia, Marcos Flávio Silveira Vasconcelos D’Ângelo et al.
Administrative Sciences
Multi-Criteria Decision Making
article

Automatic Substitution of Prioritization Methods Preserving Information Integrity

Iara Sibele Silva, Matheus Pereira Libório, Renato Dourado Maia, Marcos Flávio Silveira Vasconcelos D’Ângelo, Petr Ekel, João Batista Mendes
article en

Abstract

Companies face multi-criteria problems every day, such as prioritizing projects, investments, and suppliers. In this respect, the literature offers countless methods, some of which provide partial and flawed solutions. Therefore, identifying and replacing a flawed method with a more efficient one is fundamental. However, this replacement is not straightforward because each method has a different evaluation structure. More specifically, in this study, the Mapping method uses scoring evaluations, whereas the Analytic Hierarchy Process (AHP) uses pairwise comparisons. In other words, scoring evaluations are incompatible with pairwise comparison evaluations. This incompatibility prevents one method from being replaced by another without loss of information. This is a significant gap because the re-evaluation process is expensive, time-consuming, and may even be impossible if the experts are no longer available. This study presents a novel approach to automatically substitute prioritization methods without loss of information. The approach was applied to a real-world case involving forty-four Brazilian companies. The specific case shows the prioritization of four projects evaluated by scores, combined with three new projects evaluated by pairwise comparisons. The application of the approach offers specific and general contributions. For example, substituting prioritization methods without loss of information, such as the Mapping method with AHP. Flexibility in choosing the evaluation method that offers greater psychological comfort to the experts. Obtaining transitive pairwise comparison matrices independently of the number of new projects evaluated.

Administrative SciencesVol. 15(11)
Pontifícia Universidade Católica de Minas Gerais (BR), Universidade Estadual de Montes Claros (BR)
Openalex Percentile: Top 60%
Multi-Criteria Decision Making
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