This paper proposes a multidimensional and fuzzy set approach for measuring occupa tional mismatch, testing human capital theory and social closure theory. We propose to use a fuzzy indicator in the range [−1, 1] for each item to quantify the extent of occupational mismatch, which is then used in a factor analysis to identify two dimensions: coherence and satisfaction. Our findings suggest that the multidimensional and fuzzy set approach provides an informative and accurate picture of overqualification, so to disentangle prop erly the components of job satisfaction and coherence. The fuzzy indicator approach allows for a more nuanced understanding of the concept of occupational mismatch, by accounting for the imprecision and uncertainty inherent in the measurement of this construct. Overall, our study contributes to a better understanding of overqualification and provides a useful methodology for its measurement. The range of the fuzzy indicator highlights the complex ity of occupational mismatch and can inform future research in this area.

Betti, G., Gagliardi, F., Ghellini, G., Lombardi, G. (2024). Overqualification unreveled: a multidimensional and fuzzy set analysis. QUALITY & QUANTITY, 1-19 [10.1007/s11135-024-02005-6].

Overqualification unreveled: a multidimensional and fuzzy set analysis

Betti, Gianni
;
Gagliardi, Francesca;
2024-01-01

Abstract

This paper proposes a multidimensional and fuzzy set approach for measuring occupa tional mismatch, testing human capital theory and social closure theory. We propose to use a fuzzy indicator in the range [−1, 1] for each item to quantify the extent of occupational mismatch, which is then used in a factor analysis to identify two dimensions: coherence and satisfaction. Our findings suggest that the multidimensional and fuzzy set approach provides an informative and accurate picture of overqualification, so to disentangle prop erly the components of job satisfaction and coherence. The fuzzy indicator approach allows for a more nuanced understanding of the concept of occupational mismatch, by accounting for the imprecision and uncertainty inherent in the measurement of this construct. Overall, our study contributes to a better understanding of overqualification and provides a useful methodology for its measurement. The range of the fuzzy indicator highlights the complex ity of occupational mismatch and can inform future research in this area.
2024
Betti, G., Gagliardi, F., Ghellini, G., Lombardi, G. (2024). Overqualification unreveled: a multidimensional and fuzzy set analysis. QUALITY & QUANTITY, 1-19 [10.1007/s11135-024-02005-6].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11365/1278874