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Abstract
In this paper we examine the problem of setting-up a suitable indicator for the assessment of customer satisfaction. The proposed indicator is based on the nonlinear principal component analysis technique. Its properties are examined, and further analysis concerning its application to real data, the treatment of missing values and comparisons with other competitors is presented. Finally, findings with regard to data from an opinion survey are presented and discussed.
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Notes on contributors
P. A. Ferrari
Pier Alda Ferrari is Full Professor of Statistics at the Department of Economics, Business and Statistics at the Universita degli Studi di Milano, Italy. Her main research interests are: multivariate statistical analysis, multilevel models, applications of statistics to sociology and economics.
G. Manzi
Giancarlo Manzi is research fellow at the Department of Economics, Business and Statistics at the Universita degli Studi di Milano, Italy. His main research interests are: sample theory, multilevel models, Monte Carlo methods, resampling methods, applications of statistics to linguistics, business statistics.