Análisis multiobjetivo y modelos de regresión. Una aplicación para analizar el bienestar de los estudiantes españoles

• SANDRA GONZALEZ-GALLARDO ^[1]
  1. [1] Universidad de Málaga

     Universidad de Málaga

     Málaga, España

     
• Localización: Rect@: Revista Electrónica de Comunicaciones y Trabajos de ASEPUMA, ISSN-e 1575-605X, Vol. 22, Nº. 2, 2021, págs. 77-97
• Idioma: español
• DOI: 10.24309/recta.2021.22.2.02
• Enlaces
  • Texto completo (pdf)
• Resumen
  • español

    En este trabajo se propone un nuevo entorno metodolgico en el que se combinan tcnicas economtricas y de optimizacin multiobjetivo con el propsito de resolver problemas socioeconmicos. Dicha metodologa consta de dos etapas, la primera consiste en desarrollar un modelo de regresin a partir del cual, en la segunda etapa, se construye un problema de optimizacin multiobjetivo. Una ventaja de esta combinacin es la posibilidad de introducir preferencias en la resolucin del problema. En concreto, se aplicar la metodologa propuesta para analizar el bienestar de los estudiantes espaoles usando cuatro ndices (positividad, motivacin, sentido de pertenencia y acoso escolar). El anlisis del bienestar est tomando cada vez mayor relevancia por su relacin con el rendimiento acadmico de los jvenes. Para ello, se realizan cuatro regresiones (una por ndice) en funcin de un conjunto de variables explicativas, con las que se construye un problema multiobjetivo para estudiar el conflicto entre dichos ndices. Los resultados obtenidos mediante programacin multiobjetivo intervalar no solo proporcionan informacin sobre cmo afecta la mejora de un ndice del bienestar al resto de los mismos, sino que tambin nos permite conocer el perfil del estudiante que alcanza unos niveles ptimos y equilibrados entre los distintos ndices.

  • English

    In this work, a novel approach is proposed in which econometric and multiobjective optimization techniques are combined with the aim of analysing socio-economic problems. This approach consists of two stages. Firstly, a regression model is carried out, from which, in the second stage, a multiobjective optimization problem is defined. An advantage of this combination is the possibility of introducing preferences of decision makers -desired values- for solving the problem. Particularly, we apply this approach to analyse the well-being of Spanish students through four indexes (positive feelings, motivation, sense of belonging, and bullying). In recent years, studying the students well-being has become very relevant because of its relation with their academic performance. Thus, four regressions are obtained (one per index) with respect to a set of explanatory variables, from which the multiobjective optimization problem is built. The results obtained using interval multi-objective programming provide us information both about how the improvement of one index can affect the values of the remaining ones, and also about the student’s profile who achieves an optimum balance among the well-being indexes.

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