The Customer Satisfaction in a Reduced Rank Regression Framework

In this paper we propose a methodology for the estimation of customer satisfaction conceived as a latent variable specified in the American Customer Satisfaction Index (ACSI) structural model. The current proposal puts forward: the approaches of structural equations, since it involves the dual problem of indeterminacy of the latent scores and the normality assumed; the PLS approach, because of its drawbacks (shown in depth in the paper). The ACSI model will be estimated in a reduced rank regression (RRR) framework, showing that under a non restrictive hypothesis, shared by PLS, the structural model can be viewed as a RRR model between two blocks of manifest variables. Finally, in the paper an application is shown to assess the students' satisfaction in respect to the service of a big real estate agency, operating in the houses-to-let market, in Bologna (Italy) for 2002.