Multidimensional item response theory models for dichotomous data in customer satisfaction evaluation

Abstract

In this paper, multidimensional item response theory models for dichotomous data, developed in the fields of psychometrics and ability assessment, are discussed in connection with the problem of evaluating customer satisfaction. These models allow us to take into account latent constructs at various degrees of complexity and provide interesting new perspectives for services quality assessment. Markov chain Monte Carlo techniques are considered for estimation. An application to a real data set is also presented.

Keywords:

• item response theory
• customer satisfaction
• dichotomous variables
• MCMC
• MIRT

Acknowledgements

The authors acknowledge financial support from the European Social Fund Grant (FSE), Regione Lombardia and the valuable suggestions of two anonymous referees who have greatly helped to improve this work.