Job Satisfaction and Gender in Italy: A Structural Equation Modeling Approach

Giorgio Piccitto (), Hans M. A. Schadee () and Gabriele Ballarino ()
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Giorgio Piccitto: University of Bologna
Hans M. A. Schadee: University of Milan
Gabriele Ballarino: University of Milan

Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, 2023, vol. 169, issue 3, No 3, 775-793

Abstract: Abstract The aim of this study was to propose a reliable measurement model for the concept of job satisfaction in Italy and to test its measurement invariance across gender. We used the 2003 and 2009 Italian National Statistical Office (ISTAT) Family and Social Subjects (FSS) data, containing information on 8 dimensions of job satisfaction. The best-fitting model was a four-factor one, including the dimensions of intrinsic, rewards, timing and socio-contextual job satisfaction. Multi-group analysis supported the measurement invariance across gender. Additionally, we evaluated the role of several job and individual characteristics as determinants of job satisfaction for men and women. While for a number of them the patterns of association with job satisfaction were similar over genders, some differences also did emerge.

Keywords: Job satisfaction; Gender; Structural equation modeling; Italian labor market (search for similar items in EconPapers)
Date: 2023
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DOI: 10.1007/s11205-023-03187-6

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