Among the exploratory techniques, the Principal Component Analysis has the best properties in the study of the relations between the original variables, but in the customer satisfaction applications it provides all positive correlations (first component is an average or a sum of the scores).This feature entails trivial results of little interest that cannot help to take decisions, or even less, rotations (varimax, etc.) that can improve the interpretation of data structure. The aim of this paper is to highlight, via a comparison of methods, the role of the Simple Component Analysis to improve the interpretability, over and above the lack some desirable property (variance explained, etc.).This comparison will be supported by an application to real data about Patient satisfaction in the Naples’ public hospitals.

simple component analysis as an alternative to principal component analysis and related exploratory methods for the evaluation of customer satisfaction

MILONE, Gabriella;D'AMBRA, LUIGI
2009

Abstract

Among the exploratory techniques, the Principal Component Analysis has the best properties in the study of the relations between the original variables, but in the customer satisfaction applications it provides all positive correlations (first component is an average or a sum of the scores).This feature entails trivial results of little interest that cannot help to take decisions, or even less, rotations (varimax, etc.) that can improve the interpretation of data structure. The aim of this paper is to highlight, via a comparison of methods, the role of the Simple Component Analysis to improve the interpretability, over and above the lack some desirable property (variance explained, etc.).This comparison will be supported by an application to real data about Patient satisfaction in the Naples’ public hospitals.
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11588/363527
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