Comparative evaluation of multicriteria methods versus the traditional approach in the prioritization of public projects in Mexico

Resumen

Objective: To compare the performance of the basic method used by Mexican public entities with various advanced multicriteria decision-making (MCDM) methods, aiming to prove that the latter are better suited to evaluate the competitive allocation of public resources.

Design/Methodology/Approach: The performance of six MCDM methods and two variants of the Weighted Sum Method (WSM) were assessed as part of the prioritization of 100 simulated projects, replicating the 2017 model of the Programa de Apoyo para Productores en Zonas de Atención Prioritaria (FAPPA). The analysis, conducted using R, included a linearity validation of rankings to measure the variability in ranking.

Results: The model currently used in public programs (WSM without normalization) has low discriminative capacity, with 98% ties between proposals. In contrast, methods that incorporate normalization reduced this percentage to 41%, with variations depending on the algorithm used. In contrast, the model currently used in public programs (WSM without normalization) exhibits low discriminative capacity, with 98% ties between proposals. In contrast, methods incorporating normalization reduced this percentage to 41%, with variations depending on the algorithm used. Evaluation based on Distance from Average Solution (EDAS) and Complex Proportional Assessment (COPRAS) recorded the rankings with the highest concordance (R² = 0.92), whereas Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) and WSM recorded the lowest results (R² = 0.23). Clear differences in stability, discrimination, and complexity were recorded. Multi-Objective Optimization on the basis of Ratio Analysis (MOORA) stood out based on its balance between accuracy and simplicity.

Study Limitations/Implications: The study is limited to 100 FAPPA proposals, which may limit the generalisation of the results. Findings/Conclusions: The comparison of multicriteria methods for public allocation emphasizes normalization, while the algorithmic structure influences proposal discrimination. Well-evaluated projects were consistently identified, reinforcing the validity of the model. Method selection should balance accuracy and feasibility to enhance transparency and equity.