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Modelling the quality of work in the Italian social co-operatives combining NPCA-RSM and SEM-GME approaches

Enrico Ciavolino, Maurizio Carpita and Amjad Al-Nasser ()

Journal of Applied Statistics, 2015, vol. 42, issue 1, 161-179

Abstract: The objective of this paper is to describe and analyse with appropriate statistical models the links between work quality latent factors. Due to the complexity of the task, the analysis is carried out through a two-step approach: In the first step, we construct some multidimensional measures of the subjective quality of work, using nonlinear principal component analysis (NPCA) and Rasch analysis with the Rating Scale Model (NPCA-RSM); In the second step, we adopt a Structural Equation Model based on generalized maximum entropy (SEM-GME) to integrate the measures achieved with the previous step and to evaluate the relationships between the subjective work quality latent factors. Therefore, the novel aspects of this paper are the following: (i) The integration between the NPCA-RSM and SEM-GME, which allows reduction of the variables analysed and evaluation of the measurement errors; (ii) The formalization of a Job Satisfaction Model for the study of the relationships between the subjective work quality latent factors in the Italian social services sector.

Date: 2015
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