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A two-step procedure to analyse users' satisfaction

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Author Info
Pieralda Ferrari (University Milan)
Laura Pagani (University of Udine)
Carlo Fiorio (University of Milan)

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Abstract

In this paper an integrated use of Nonlinear Principal Component Analysis (NLPCA) and Multilevel Models (MLM) for the analysis of satisfaction data is proposed. The basic hypothesis is that observed ordinal variables describe different aspects of a latent continuous variable that depends on individual and contextual covariates. NLPCA is used to measure the level of a latent variable and MLM are adopted for detecting individual and environmental determinants of the level. By using the Eurobarometer survey data, this approach is applied to analyse the European users' satisfaction with services of general interest after the recent privatisation and liberalisation policies.

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Publisher Info
Paper provided by Universitá degli Studi di Milano in its series UNIMI - Research Papers in Economics, Business, and Statistics with number 1068.

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Date of creation: 17 Mar 2008
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Handle: RePEc:bep:unimip:1068

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Related research
Keywords: Nonlinear Principal Component Analysis; Multilevel Models; satisfaction; privatisation and liberalisation policies;

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This page was last updated on 2009-11-21.

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