Eficiencia de depuradoras bajo incertidumbre: DEA con tolerancias

• Ramón Sala Garrido ^[1] ; María Molinos Senante ^[1] ; Francesc Hernández Sancho ^[1]
  1. [1] Universitat de València

     Universitat de València

     Valencia, España

     
• Localización: Anales de ASEPUMA, ISSN-e 2171-892X, Nº. 19, 2011
• Idioma: español
• Enlaces
  • Texto completo (pdf)
• Resumen
  • español

    A media que el número de Estaciones Depuradoras de Aguas Residuales (EDARs) ha ido incrementando, las cuestiones económicas asociadas a su gestión han adquirido más importancia. La evaluación de la eficiencia constituye una herramienta muy útil para la reducción de costes. Para ello, la metodología Data Envelopment Analysis (DEA) se constituye una metodología muy apropiada. Sin embargo, una de las críticas más comunes de los modelos DEA es que no proporciona información sobre la incertidumbre. Para superar esta limitación, evaluamos la eficiencia mediante un modelo DEA con tolerancias tanto para los inputs como los outputs. Los resultados muestran que los índices de eficiencia de las EDARs cambian cuando se incorporan modificaciones de datos. Además, realizamos una clasificación de las EDARS en base a su eficiencia, lo que nos permite identificar las instalaciones con las mejores prácticas, que servirán como referencia para reducir al mínimo los costos de explotación de otras plantas.

  • English

    As the number of wastewater treatment plants (WWTPs) has increased, the economics associated with their management have become more relevant. The efficiency assessment is therefore a useful tool for cost reduction. For this purpose, Data Envelopment Analysis (DEA) is a highly suitable technique. However, one of the most common criticisms of DEA models is that information on uncertainty estimates is not provided. To overcome this limitation, we assess efficiency by using a DEA model with statistical tolerances for both inputs and outputs. The results show that WWTP efficiency scores change when data modifications are incorporated. Moreover, WWTPs are ranked in terms of efficiency, allowing the identification of facilities with the best practices, which will serve as a reference for minimizing operating costs at other plants. This empirical application illustrates that the combination of the DEA model with uncertainty assessments provides more robust results, leading to more reliable conclusions than traditional DEA.

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