Abstract

This article focuses on the application of the principal component analysis (PCA) method to evaluate the competitiveness of scientific production in Mexican universities, based on the identification and classification of a set of indicators, grouped into seven dimensions and 18 criteria. Specifically, the method was performed in the educational institutions included in the category of state public universities (33 in total), over a period of five years (2007-2011), and ultimately identified only seven criteria as principal components, resulting in a scale of positions that indicate the index of relative potential (IPR in Spanish). Thus, the levels of opportunity for each university in relation to their group are defined, and the university that showed the highest competitiveness is identified and it in turn becomes a quality parameter.

Abstract

AbstractThis article focuses on the application of the principal component analysis (PCA) method to evaluate the competitiveness of scientific production in Mexican universities, based on the identification and classification of a set of indicators, grouped into seven dimensions and 18 criteria. Specifically, the method was performed in the educational institutions included in the category of state public universities (33 in total), over a period of five years (2007-2011), and ultimately identified only seven criteria as principal components, resulting in a scale of positions that indicate the index of relative potential (IPR in Spanish). Thus, the levels of opportunity for each university in relation to their group are defined, and the university that showed the highest competitiveness is identified and it in turn becomes a quality parameter.