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Nova scientia

versión On-line ISSN 2007-0705

Resumen

ALTAMIRANO-CORRO, Antonio  y  PENICHE-VERA, Rebeca del Rocío. Measuring the institutional efficiency using data envelopment analysis and artificial neural networks: The case of Mexican colleges of engineering. Nova scientia [online]. 2014, vol.6, n.12, pp.356-378. ISSN 2007-0705.

Introduction: This paper proposes an approach to measure the institutional efficiency combining data envelopment analysis (DEA) with artificial neural networks (ANN). The proposed approach is applied to Mexican colleges of engineering as a case of study. Both methods are frequently used independently, on a global level in areas such as: Government, business, industry, health care and education. Method: The contribution of this work is to present a methodology to measure the efficiency of Mexican colleges of engineering training a neural network with the information generated from the DEA. For the evaluation of the efficiency of the 51 colleges of engineering the indicators extracted from the Programa Integral de Fortalecimiento Institucional (PIFI 2008-2009) Integrated Program of Institutional Strengthening were used. Results: The results were very good, the methodology works fine, introducing the values of the PIFI we can determine the educative efficiency level using the trained neural network. Conclusion: The immediate impact is that applying this methodology we can measure institutional efficiency in private and public institutions.

Palabras llave : operations research; data envelopment analysis; artificial neural networks; efficiency.

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