Instrumentos para el análisis de ordenaciones basadas en métodos multicriterio. Aplicación a las Universidades Iberoamericanas

Rodrigo Andrés Pardo; Carla Rojas Puebla; Vicente Liern

doi:10.24310/recta.26.1.2025.20777

Authors

Rodrigo Andrés Pardo Universidad de Valencia Spain https://orcid.org/0009-0003-3996-478X
Carla Rojas Puebla Universidad de Valencia Spain https://orcid.org/0009-0004-6148-1036
Vicente Liern Universidad de Valencia Spain https://orcid.org/0000-0001-5883-9640

DOI:

https://doi.org/10.24310/recta.26.1.2025.20777

Keywords:

UW-TOPSIS, Multiple-criteria decision analysis, SCIMAGO, Iberoamerican Universities

Abstract

Traditional multi-criteria decision-making methods can be adapted to uncertainty scenarios, allowing for rankings even when some model requirements are imprecise. In this work, we demonstrate another use of these methods: the Unweighted TOPSIS (UW-TOPSIS) method will be used to detect anomalies in rankings made with precise data. By applying UW-TOPSIS, each alternative is associated with an interval indicating its worst and best overall evaluation position in the ranking. To extract useful information from this range of possibilities, we introduce the intervention coefficient, which measures the similarity between the position of an alternative and its best possible situation.

The proposal is applied to the ranking of Ibero-American universities (including Andorra, Spain and Portugal) published by SCImago IBER for the five-year period 2018-2022. Different levels detected by the intervention coefficient are studied, and an alternative ranking method that better fits the data from the database itself is proposed.

Downloads

Download data is not yet available.

Publication Facts

This article

Author statements

Data availability

N/A

16%

External funding

N/A

32%

Competing interests

N/A

11%

This journal

Other journals

Articles accepted

4%

33%

Days to publication

19

145

Indexed in

—

Editor & editorial board: profiles
Academic society: N/A
Publisher: UMA Editorial. Universidad de Málaga

References

Acuña-Soto, C, Liern, V., Pérez-Gladish, B. (2021). Normalization in TOPSIS-based approaches with data of different nature: application to the ranking of mathematical videos, Annals of Operations Research, 296, 541-569.

https://doi.org/10.1007/s10479-018-2945-5

Hwang, C. L. & Yoon, K. (1981). Multiple Atribute Decision Making: Methods and Applications. New York: Springer-Verlag.

https://doi.org/10.1007/978-3-642-48318-9

Benítez, R., Liern, V. (2021). Unweighted TOPSIS: a new multi-criteria tool for sustainability analysis, International Journal of Sustainable Development & World Ecology, 28, 36-48.

https://doi.org/10.1080/13504509.2020.1778583

Bouslah, K., Liern, V., Ouenniche, J. & B. Pérez-Gladish, B. (2022). Ranking firms based on their financial and diversity performance using multiple-stage unweighted TOPSIS. International Transactions in Operational Research, available online, https://doi.org/10.1111/itor.13143.

Carlsson, C., Fullér, R. (2001). Fuzzy Reasoning in Decision Making and Optimization. PhysicaVerlag.

https://doi.org/10.1007/978-3-7908-1805-5

IREG (2023) Observatory on Academic Ranking and Excellence https://ireg-observatory.org/en/aboutus/ - Berlin principles (Recuperado el 14 de noviembre 2023).

Liern, V., Parada-Rico, S.E. y Blasco-Blasco, O. (2020). Construction of quality indicators based on pre-established goals: Application to a Colombian Public University, Mathematics 8 (7), 1075.

https://doi.org/10.3390/math8071075

Liern, V., Pérez-Gladish, B. (2022). An algorithmic method to Multiple criteria ranking method based on functional proximity index: un-weighted TOPSIS, Annals of Operations Research, 311, 1099- 1121.

https://doi.org/10.1007/s10479-020-03718-1

López-García, A., Liern, V., Pérez-Gladish, B. (2023). Determining the underlying role of corporate sustainability criteria in a ranking problem using UW-TOPSIS. Annals of Operations Research. https://doi.org/10.1007/s10479-023-05543-8.

Martínez Rizo, F. (2010). Los rankings de universidades: Una visión crítica. Revista de la educación superior. México.

Ouenniche, J., Pérez-Gladish, B., Bouslah, K. (2018). An out-of-sample framework for TOPSIS-based classifiers with application in bankruptcy prediction. Technological Forecasting and Social Change, 131, 111-116.

https://doi.org/10.1016/j.techfore.2017.05.034

Pinto-Delacadena, P.A., Liern,V., Acosta-Vargas, P, and Vinueza-Cabezas, A. (2024). A multicriteria approach to ranking Latin-American universities based on region-specific criteria. Technological Forecasting and Social Change 208, 123725.

https://doi.org/10.1016/j.techfore.2024.123725

Pardo-Quintanilla, R. (2023). Un instrumento para el análisis de ordenaciones. Aplicación a las universidades iberoamericanas. Trabajo de Fin de Máster. Universitat de València.

Pardo-Quintanilla, R., Rojas-Puebla, C., Liern, V. (2023). Asignación de ayudas a la investigación basado en técnicas multicriterio. Comunicación en ASEPUMA 2023.

Reyes C. (2016). Medición de la calidad universitaria en Chile: la influencia de los rankings. Calidad en la Educación, 44, 158-196.

https://doi.org/10.4067/S0718-45652016000100007

SCImago IBER (2023). https://www.scimagoiber.com/institutions.php (Recuperado el 2 de octubre de 2023).

SCImago Lab (2023). https://www.scimagolab.com/sobre-scimago/ (Recuperado el 2 de octubre de 2023).

SCImago IR (2023). https://www.scimagoir.com/methodology.php (Recuperado el 2 de octubre de 2023).

Webster, David S. (1983). "America's Higher-Ranked Graduate Schools, 1925-1982", en Change, May-June, pp. 13-24.

https://doi.org/10.1080/00091383.1983.10569969